Ricardo Valerdi

Interests

Teaching

Systems engineering, cost estimation, sports analytics

Research

Systems engineering, cost estimation, sports analytics

Courses

Scholarly Contributions

Books

• Valerdi, R., Friedman, G., & Marticello, D. (2011). Diseconomies of Scale in Systems Engineering. Air University.
• Valerdi, R. (2009). Systems Engineering Cost Estimation with COSYSMO. Blackwell Science Limited.

Chapters

• Bukhari, H. J., Valerdi, R., & Ward, D. (2014). Quantifying risk of acquisition portfolios. In Digital Enterprise Design & Management(pp 143--143). Springer International Publishing.
• Gorod, A., White, B. E., Ireland, V., Gandhi, S. J., Sauser, B., Cizaire, C., & Valerdi, R. (2014). Heathrow Terminal 5: Cost Management for a Mega Construction Project. In Case Studies in System of Systems, Enterprise Systems, and Complex Systems Engineering(pp 731--749). CRC Press.
• Latner, A., & Valerdi, R. (2011). Feature Performance Metrics for Software as a Service Offering. In Improving Complex Systems Today(pp 151--158). Springer London.
• Valerdi, R., & Fernandes, B. (2011). Underestimation in the “When It Gets Worse Before it Gets Better” Phenomenon in Process Improvement. In Improving Complex Systems Today(pp 3--10). Springer London.

Journals/Publications

• Boehm, B., Lane, J. A., Kern, P. M., Jost, A. C., Thayer, R. H., Leach, R. J., Valerdi, R., Ross, A. M., & Rhodes, D. H. (2016). Systems Engineering CrossTalk. crosstalk, 801, 775--5555.
• Cisneros, J. A., & Valerdi, R. (2016). An{'a}lisis Cuantitativo y Cualitativo para Determinar la Cultura Intr{'i}nseca de la Norma Mexicana NMX-I-59/NYCE-2005..
• Cisneros, J. A., Valerdi, R., & Oca, C. M. (2016). Adopci{'o}n de Tecnolog{'i}as de Desarrollo de Software Considerando la Brecha Cultural Existente entre la Cultura Organizacional y la Cultura Intr{'i}nseca de una Tecnolog{'i}a..
• Collar, E., & Valerdi, R. (2016). Role of Software Readability on Development Cost. Massachusetts Institute of Technology.
• Conboy, B. F., Valerdi, K. P., & Stol, L. M. (2016). Lean Enterprise Software and Systems.
• Dimitrov, I. Z., Hess, J. T., & Perkins, L. N. (2016). Healthcare Reborn.
• Dorey, M. S., Oehmen, J., & Valerdi, R. (2016). Enhancing Cost Realism through Risk-Driven Contracting.
• Downes, C. G., Chung, P. W., Morris, A., Yang, K., Chen, Y., Lu, Y., Zhao, Q., Hess, J. T., Valerdi, R., Mane, M., & others, . (2016). 5th International Conference on System of Systems Engineering (SoSE 2010).
• Giombea, M., Valerdi, R., & Wagner, S. (2016). The influence of software quality requirements on the suitability of software cost es{c{S}}ma{c{S}}on methods.
• Honour, E. C., & Valerdi, R. (2016). Toward an Ontology for Measuring Systems Engineering Return on Investment (SE-ROI).
• Madachy, R., & Valerdi, R. (2016). University of Southern California-Center for Systems and Software Engineering Massachusetts Institute of Technology--Systems Engineering Advancement Research Initiative madachy@ usc. edu, rvalerdi@ mit. edu.
• Pan, X., Valerdi, R., & Kang, R. (2016). Procedia Computer Science.
• Russac, J., Jones, C., Garmus, D., Alm{'e}n, P., Malkiewicz, H., Mayer, L., Morris, P., Pandey, N., Buglione, L., Chemuturi, M., & others, . (2016). The IFPUG Guide to IT and Software Measurement.
• Torrance, C. (2016). Systems Engineering Sizing in the Age of Acquisition Reform.
• Turner, R., & Pyster, A. (2016). The Graduate Software Engineering Reference Curriculum: A Joint Industry, Government and Academic Project.
• Valerdi, R. (2016). Handbook of Industrial and Systems Engineering.
• Valerdi, R. (2016). SIE 464-564 Cost Estimation.
• Valerdi, R., & Roedler, G. J. (2016). Harmonizing Systems and Software Cost Estimation.
• Valerdi, R., & Ryan, T. R. (2016). Total Cost of Ownership (TOC). Operations Research for Unmanned Systems, 207--232.
• Xu, L., Chaudhry, S. S., Fan, Y., Fanti, M. P., Lee, J., Li, L., Vernadat, F., Zhang, C., Awad, E., Chen, Y., & others, . (2016). Enterprise Information Systems Editorial Board 2011.
• Yang, Z. R., Everson, R., & Yin, H. (2016). IDEAL 2004: intelligent data engineering and automated learning(Exeter, 25-27 August 2004). Lecture notes in computer science.
• Cizaire, C., & Valerdi, R. (2015). 25 Heathrow Terminal 5.
• Pe{~n}a, M., & Valerdi, R. (2015). Characterizing the impact of requirements volatility on systems engineering effort. Systems Engineering, 18(1), 59--70.
• Ryan, T. R., & Valerdi, R. (2015). Costing for an Autonomous Future: A Discussion on Estimation for Unmanned Autonomous Systems. Procedia Computer Science, 44, 547--557.
• Valerdi, R. (2015). Pioneers of Parametrics: Origins and Evolution of Software Cost Estimation. Journal of Cost Analysis and Parametrics, 8(2), 74--91.
• Valerdi, R., Dabkowski, M., & Dixit, I. (2015). Reliability Improvement of Major Defense Acquisition Program Cost Estimates—Mapping DoDAF to COSYSMO. Systems Engineering, 18(5), 530--547.
• Dabkowski, M., Valerdi, R., & Farr, J. (2014). Exploiting architectural communities in early life cycle cost estimation. Procedia Computer Science, 28, 95-102.
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  Abstract: System architectures evolve over time Accordingly, the dynamic properties of architectures reflect how systems respond to change, and this response ultimately impacts cost In prior work we make an explicit connection between the architectural diagrams of Model-Based Systems Engineering (MBSE), parametric cost estimation, and network science Specifically, by treating the DoD Architecture Framework (DoDAF) Systems View 3 (SV3) as an adjacency matrix, we assess how the addition of a new subsystem to an immature architecture might grow the existing network With the subsequent application of parametric cost modeling, we translate anticipated growth into expected cost, thereby quantifying the impact of change This paper refines that approach In particular, by using the Girvan-Newman algorithm, the SV3 is initially divided into groups of subsystems such that the number of interfaces is dense within and sparse between groups Based on this division into "architectural communities" and the prevalence of bridging ties, interfaces generated by the addition of a new subsystem can be faithfully integrated into the existing architecture, adding validity to our growth mechanism This procedure is illustrated in detail with an example that highlights the importance of this refinement, and it is incorporated within a Monte Carlo simulation that allows the distribution of future costs to be estimated and assessed © 2014 The Authors. Published bv Elsevier B.V.
• De Zhou, Z., Valerdi, R., Zhou, S. M., & Wang, L. (2014). Guest editorial special section on IoT. IEEE Transactions on Industrial Informatics, 10(2), 1413--1416.
• II, D. T., Reidy, B., Valerdi, R., Gudagi, A., Kurra, H., Al-Nashif, Y., Hariri, S., & Sheldon, F. (2014). Improving cyber resiliency of cloud application services by applying Software Behavior Encryption (SBE). Procedia Computer Science, 28, 62-70.
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  Abstract: The objective of this work is to define and measure cyber resiliency of the "cloud" in a Moving Target Defense (MTD) environment that applies the Software Behavior Encryption (SBE) method Implementation of SBE has shown to increase vulnerability tolerance in a particular software system by introducing software diversity and redundant version shuffling to obfuscate the system to attackers With this in mind, this paper nominates attack surface, confidentiality, integrity, availability, and survivability as the critical components of cyber resiliency, and a notional example is provided to demonstrate the components application and aggregation © 2014 The Authors. Published by Elsevier B.V.
• Jones, M., Webb, P., Summers, M., Baguley, P., & Valerdi, R. (2014). A cost--benefit framework for assessing advanced manufacturing technology development: A case study. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 0954405414539932.
• Lane, J. A., Galorath, D. D., & Valerdi, R. (2014). On the Shoulders of Giants: A Tribute to Prof. Barry W. Boehm. Journal of Cost Analysis and Parametrics, 7(3), 149--159.
• Monreal Jr., J., Valerdi, R., & Latt, L. D. (2014). A systems approach to healthcare efficiency improvement. Procedia Computer Science, 28, 610-618.
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  Abstract: Healthcare patient outcomes and healthcare costs, in the context of the healthcare delivery system, is a prominent societal issue for the U.S. Although improvements have been achieved, they are silo-centric, specific to a single area or discipline. It is clear that improvements need to be transferred across the healthcare delivery system in a broader sense. To that end, the ability to measure a change in the system is paramount in determining progress and in what parts of the system are impacted. The research work presented describes a case of how an Electronic Medical Record (EMR) system implementation can be measured within a systems or systems engineering context. In the first phase, time motion study has been employed to assess physician workflow. In this manner, data collection, analysis, and inferences elicited can be quickly assessed by subject matter experts for effectiveness. The objective of this collaborative work is that it demonstrates a systems engineering driven application of the improvement of an orthopaedic office that may then be generalized to a broader context. This works employs a phased approach which allows for synchronization between one set of tools or methodologies from one phase that inform and provide insight for the next. Additionally it facilitates an iterative effort as each phase will assess and reassess the key stakeholders and take into account the process/product life cycle thus allowing refinement of the previous phase and its results. The progression from one phase to another provides the means of measuring the progress and impact. The partnership between the Department of Orthopaedics and the Department of Systems and Industrial Engineering at the University of Arizona, provides a real-life setting for testing our hypotheses. All of the features described in this implementation make up a methodological framework that will render implications for engineers, physicians, patients, and policy makers. © 2014 The Authors. Published by Elsevier B.V.
• Valerdi, R. (2014). Farewell and Acknowledgement to Nicolene Hengen--JET's Inaugural Managing Editor. Journal of Enterprise Transformation, 4(1), 1--2.
• Basole, R. C., Bellamy, M., Clear, T., Dabkowski, M., Monreal, J., Park, H., Valerdi, R., & Van Aken, E. (2013). Challenges and opportunities for enterprise transformation research. Journal of Enterprise Transformation, 3(4), 330--352.
• Dabkowski, M., Estrada, J., Reidy, B., & Valerdi, R. (2013). Network science enabled cost estimation in support of MBSE. Procedia Computer Science, 16, 89--97.
• Fortune, J., & Valerdi, R. (2013). A framework for reusing systems engineering products. Systems Engineering, 16(3), 304-312.
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  Abstract: As budgetary pressure on large complex systems continues to increase, the interest in reusing systems engineering products is emerging. Reuse is the idea of leveraging previously developed products (i.e., hardware, software, designs, outcomes of a process) into a new application for purposes of improving project attributes such as quality, cost, schedule, or risk. While reuse is well documented and commonly practiced in the domains of software and product-line development, limited research has been performed on the (deliberate or accidental) reuse of systems engineering products. This paper classifies such products as those generated as outputs of both the systems engineering process, including architecture elements, requirements, test plans, and interface specifications, as well as the overall system design process. Through reuse, systems engineers may not need to repeat certain development activities associated with these products, potentially reducing effort, or obtaining schedule/risk benefits through the utilization of heritage products. To begin addressing the topic of reuse from a systems engineering perspective, this paper presents a generalized framework for the reuse of systems engineering products; documenting the key considerations, activities, and resources necessary for effective reuse. Building on insight from systems engineering practitioners and previous work by the authors on systems engineering cost estimation, the framework is intended to serve as a tool for planning, executing, and managing reuse activities, as well as identifying reuse opportunities. © 2012 Wiley Periodicals. Inc. Syst Eng 16: Copyright © 2012 Wiley Periodicals, Inc.
• Pan, X., Valerdi, R., & Kang, R. (2013). Systems thinking: A comparison between Chinese and Western approaches. Procedia Computer Science, 16, 1027--1035.
• R., J., & Valerdi, R. (2013). Successful adoption of software process improvement models: A cultural-methodological proposal. Journal of Software, 8(9), 2367-2378.
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  Abstract: Adoption of a Software Process Improvement Model (SPIM) is a problematic activity that occurs in almost all software development companies. This problem has different causes. One of these causes has relation with cultural aspects that are present in: a) The Company's organizational culture, b) The SPIM's documents embedded culture. Whether these cultural aspects are not treated properly there will be a problem that generates millions in economic losses to companies around the world. To reduce these economic losses and increase successful rates of SPIM adoptions, we developed a culturalmethodological proposal. This has four steps: a) Identify the Company's organizational culture, b) identify the SPIM's documents embedded culture and, c) Identify and quantify cultural aspects of organizational culture and embedded culture and, d) explain differences between them. The purpose is to generate information that can be used to develop plans and strategies for adoption and institutionalization of SPIM. Our proposal is illustrated using the Mexican Norm: NMXI-059/NYCE-2005 as an example of a SPIM and 8 Mexican Software development companies as an example of organizational culture. © 2013 ACADEMY PUBLISHER.
• Valerdi, R., & Christopherson, T. L. (2013). COSYSMO calibration steps and results. 23rd Annual International Symposium of the International Council on Systems Engineering, INCOSE 2013, 1, 725-733.
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  Abstract: This paper provides insight into calibrating a systems engineering cost model (COSYSMO) by providing a process that organizations can follow to improve their estimation accuracy. A specific example is provided from Raytheon Missile Systems to illustrate how data are collected and how they influence the cost estimating relationship. The results from this specific case are generalized to other organizations who wish to improve their cost estimation capabilities in systems engineering. © 2013 by Ricardo Valerdi and Tim Christopherson. Published and used by INCOSE with permission.
• Valerdi, R., Monreal, J., Valenzuela, D., & Hernandez, K. (2013). Measures of Effectiveness for STEM Program: The Arizona Science of Baseball. Procedia Computer Science, 16, 1053--1061.
• Valerdi, R., Rhodes, D. H., & Haskins, C. (2013). Report on the 2013 Workshop of INCOSE's Systems Engineering and Architecting Doctoral Student Network. INSIGHT, 16(2), 60--63.
• Wang, G., Valerdi, R., Roedler, G. J., & Pena, M. (2013). Quantifying systems engineering reuse - A generalized reuse framework in COSYSMO. 23rd Annual International Symposium of the International Council on Systems Engineering, INCOSE 2013, 2, 1285-1303.
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  Abstract: This paper further elaborates a generalized reuse framework for systems engineering reuse previously published and defines two interrelated reuse processes - development for reuse (DFR) and development with reuse (DWR). It proposes a quantitative approach for assessing such a reuse effort by defining a set of reuse categories for both the DFR and the DWR processes and by extending the model definition and cost estimating relationship of COSYSMO, a systems engineering cost model. © 2013 by Gan Wang, Ricardo Valerdi, Garry Roedler, and Mauricio Pena.
• Yang, Y., Zhimin, H. e., Mao, K., Qi, L. i., Nguyen, V., Boehm, B., & Valerdi, R. (2013). Analyzing and handling local bias for calibrating parametric cost estimation models. Information and Software Technology, 55(8), 1496-1511.
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  Abstract: Context Parametric cost estimation models need to be continuously calibrated and improved to assure more accurate software estimates and reflect changing software development contexts. Local calibration by tuning a subset of model parameters is a frequent practice when software organizations adopt parametric estimation models to increase model usability and accuracy. However, there is a lack of understanding about the cumulative effects of such local calibration practices on the evolution of general parametric models over time. Objective This study aims at quantitatively analyzing and effectively handling local bias associated with historical cross-company data, thus improves the usability of cross-company datasets for calibrating and maintaining parametric estimation models. Method We design and conduct three empirical studies to measure, analyze and address local bias in cross-company dataset, including: (1) defining a method for measuring the local bias associated with individual organization data subset in the overall dataset; (2) analyzing the impacts of local bias on the performance of an estimation model; (3) proposing a weighted sampling approach to handle local bias. The studies are conducted on the latest COCOMO II calibration dataset. Results Our results show that the local bias largely exists in cross company dataset, and the local bias negatively impacts the performance of parametric model. The local bias based weighted sampling technique helps reduce negative impacts of local bias on model performance. Conclusion Local bias in cross-company data does harm model calibration and adds noisy factors to model maintenance. The proposed local bias measure offers a means to quantify degree of local bias associated with a cross-company dataset, and assess its influence on parametric model performance. The local bias based weighted sampling technique can be applied to trade-off and mitigate potential risk of significant local bias, which limits the usability of cross-company data for general parametric model calibration and maintenance. © 2013 Elsevier B.V. All rights reserved.
• De Zhou, Z., Valerdi, R., & Zhou, S. (2012). Guest editorial special section on enterprise systems. IEEE Transactions on Industrial Informatics, 3(8), 630.
• Ferguson, B., McCurley, J., Stoddard, B., Cohen, J., & Morrow, T. (2012). Quantifying Uncertainty in Early f C f Lifecycle Cost Estimation for DOD MDAPs.
• Ling, L. i., Ge, R., Zhou, S., & Valerdi, R. (2012). Guest editorial integrated healthcare information systems. IEEE Transactions on Information Technology in Biomedicine, 16(4), 515-517.
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  PMID: 22760931;Abstract: The use of integrated information systems for healthcare has been started more than a decade ago. In recent years, rapid advances in information integration methods have spurred tremendous growth in the use of integrated information systems in healthcare delivery. Various techniques have been used for probing such integrated systems. These techniques include service-oriented architecture (SOA), EAI, workflow management, grid computing, and others. Many applications require a combination of these techniques, which gives rise to the emergence of enterprise systems in healthcare. Development of the techniques originated from different disciplines has the potential to significantly improve the performance of enterprise systems in healthcare. This editorial paper briefly introduces the enterprise systems in the perspective of healthcare informatics. © 2012 IEEE.
• Newnes, L., & Valerdi, R. (2012). Special issue on through life cost estimating. International Journal of Computer Integrated Manufacturing, 25(4-5), 297-299.
• Valerdi, R. (2012). The Top 12 Signs You Are a Systems Engineer. INSIGHT, 15(2), 46--47.
• Valerdi, R. (2012). optimism in Cost estimation. The IFPUG Guide to IT and Software Measurement, 177.
• Valerdi, R., & Zonnenshain, A. (2012). Teaching them how to fish: Industry-focused student projects in systems engineering. 22nd Annual International Symposium of the International Council on Systems Engineering, INCOSE 2012 and the 8th Biennial European Systems Engineering Conference 2012, EuSEC 2012, 4, 2868-2875.
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  Abstract: This paper provides an overview of industry-focused systems engineering team projects for university students. The projects described are from two universities: the University of Arizona (U.S.A.) and Technion (Israel). The role of such projects in teaching and learning of systems engineering is explored, specifically in the context of constructivist learning theory. Characteristics of successful student projects are discussed together with examples of such projects and their resulting artifacts. We conclude by proposing measures of success of such projects. © 2012 by Ricardo Valerdi & Avigdor Zonnenshain.
• Valerdi, R., Rhodes, D. H., & Dagli, C. (2012). Seven Years and Counting: The 2012 Workshop of INCOSE's Systems Engineering and Architecting Doctoral Student Network. INSIGHT, 15(2), 53--54.
• Wang, G., Valerdi, R., Roedler, G. J., Ankrum, A., & Gaffney Jr., J. E. (2012). Harmonising software engineering and systems engineering cost estimation. International Journal of Computer Integrated Manufacturing, 25(4-5), 432-443.
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  Abstract: Complex systems are developed with the help of numerous engineering disciplines. In software-intensive systems, software and systems engineers play a major role in design, development, test and deployment. Since these roles are often very tightly coupled, it is difficult to determine which life cycle functions can be performed jointly versus separately. This makes it particularly difficult for resource estimation and project planning. To resolve this issue, we examine the gaps and overlaps between software engineering and systems engineering cost models with intent to harmonise the estimates for project estimation. In particular, we evaluate the central assumptions of the constructive cost model II and constructive systems engineering cost model and propose an approach to identify gaps and overlaps between them. Furthermore, we provide guidelines on how to reconcile and resolve the identified gaps and overlaps. The ultimate purpose of this work is to develop effective techniques for accurately estimating the combined software and systems engineering effort for software-intensive systems. © 2012 Taylor & Francis.
• Zhou, Z. D., Valerdi, R., & Zhou, S. (2012). Guest editorial special section on enterprise systems. IEEE Transactions on Industrial Informatics, 8(3), 630-.
• Boehm, B., & Valerdi, R. (2011). Impact of software resource estimation research on practice: A preliminary report on achievements, synergies, and challenges. Proceedings - International Conference on Software Engineering, 1057-1065.
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  Abstract: This paper is a contribution to the Impact Project in the area of software resource estimation. The objective of the Impact Project has been to analyze the impact of software engineering research investments on software engineering practice. The paper begins by summarizing the motivation and context for analyzing software resource estimation; and by summarizing the study's purpose, scope, and approach. The approach includes analyses of the literature; interviews of leading software resource estimation researchers, practitioners, and users; and value/impact surveys of estimators and users. The study concludes that research in software resource estimation has had a significant impact on the practice of software engineering, but also faces significant challenges in addressing likely future software trends. © 2011 ACM.
• Hihn, J., Chattopadhyay, D., & Valerdi, R. (2011). How Engineers Really Think About Risk: A Study of JPL Engineers.
• Latner, A., & Valerdi, R. (2011). Feature performance metrics for software as a service offering. Advanced Concurrent Engineering, 151-158.
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  Abstract: This paper provides a framework to measure the performance of software as a service (SaaS) product features to prioritize development efforts. Firstly, relative value is measured by the impact of each feature on customer acquisition and retention. Secondly, feature value is compared to feature cost and specifically development investment to determine feature profitability. Thirdly, feature sensitivity is measured. Feature sensitivity is defined as the effect a fixed amount of development investment has on value in a given time. Fourthly, features are segmented according to their location relative to the value to cost trend line into most valuable features, outperforming, underperforming and fledglings. Finally, results are analyzed to determine future action. Maintenance and bug fixes are prioritized according to feature value. Product enhancements are prioritized according to sensitivity with special attention to fledglings. Underperforming features are either put on "life-support," terminated or overhauled. This framework is applicable to SaaS companies for the purpose of prioritizing features, an important consideration for concurrent engineering of software systems. © 2011 Springer-Verlag London Limited.
• Province, S., Wang, F., Wang, J., Yang, G., Valerdi, R., Cochairs, G., Farrell, J. A., Wang, Y., Duarte-Mermoud, M., Lin, H., & others, . (2011). 6TH INTERNATIONAL CONFERENCE ON SYSTEM OF SYSTEMS ENGINEERING. IEEE CONTROL SYSTEMS MAGAZINE.
• Purchase, V., Parry, G., Valerdi, R., Nightingale, D., & Mills, J. (2011). Enterprise Transformation: Why are we interested, What is it, and What are the challenges?. Journal of Enterprise Transformation, 1(1), 14--33.
• Valerdi, R. (2011). Convergence of expert opinion via the wideband delphi method: An application in cost estimation models. 21st Annual International Symposium of the International Council on Systems Engineering, INCOSE 2011, 2, 1238-1251.
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  Abstract: This paper discusses the notion of collective intelligence through the application of the Wideband Delphi method as a way to obtain convergence among a group of experts. The specific application is the definition and calibration of cost estimation models that use data collected from experts as part of their calibration. Convergence is important in this case because companies need to commit to cost estimates early in the planning cycle since so many other decisions are dependent on it. Our results demonstrate that, in most cases, convergence among experts can be achieved after three roundsof the Wideband Delphi. © 2011 by Ricardo Valerdi.
• Valerdi, R. (2011). Heuristics for systems engineering cost estimation. IEEE Systems Journal, 5(1), 91--98.
• Valerdi, R., & Fernandes, B. (2011). Underestimation in the "when it gets worse before it gets better" phenomenon in process improvement. Advanced Concurrent Engineering, 3-10.
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  Abstract: When people make interventions to a system they expect the effects to be nearly instantaneous. Unfortunately, in most of the cases the intervention intended to improve the process actually causes outcomes to get worse before they get better, if they get better at all. The challenge in these types of situations is being able to readjust expectations that there is a delay in the improvement. This is not simply a case of learning curve where people get better by performing repetitive tasks over time. What we are describing is a delay in the improvement and, in some cases, a degradation of performance. In this paper we discuss why humans tend to underestimate such delays in process improvement across a variety of circumstances. To illustrate this, we compare data collected from a survey with three well-documented scenarios of process improvement: the implementation of a preventative maintenance program at DuPont, the modification of Tiger Woods' golf swing, and the implementation of a platform engineering initiative for the embedded software product line at Rolls-Royce. We discuss potential reasons for the chronic underestimation of these types of improvements and recommend mechanisms for making these estimates more realistic. © 2011 Springer-Verlag London Limited.
• Valerdi, R., & Nightingale, D. (2011). An Introduction to the Journal of Enterprise Transformation. Journal of Enterprise Transformation, 1(1), 1--6.
• Valerdi, R., & Potoski, M. (2011). How Weapon Systems are Like Jelly Beans: Prediction Markets as an Information Aggregation Tool for Effective Project Management in Defense Acquisition Projects.
• Valerdi, R., & Shing, M. (2011). Message from the program chairs. Proceedings of 2011 6th International Conference on System of Systems Engineering: SoSE in Cloud Computing, Smart Grid, and Cyber Security, SoSE 2011.
• Yang, Y., Xie, L., Zhimin, H. e., Qi, L. i., Nguyen, V., Boehm, B., & Valerdi, R. (2011). Local bias and its impacts on the performance of parametric estimation models. ACM International Conference Proceeding Series.
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  Abstract: Background: Continuously calibrated and validated parametric models are necessary for realistic software estimates. However, in practice, variations in model adoption and usage patterns introduce a great deal of local bias in the resultant historical data. Such local bias should be carefully examined and addressed before the historical data can be used for calibrating new versions of parametric models. Aims: In this study, we aim at investigating the degree of such local bias in a cross-company historical dataset, and assessing its impacts on parametric estimation model's performance. Method: Our study consists of three parts: 1) defining a method for measuring and analyzing the local bias associated with individual organization data subset in the overall dataset; 2) assessing the impacts of local bias on the estimation performance of COCOMO II 2000 model; 3) performing a correlation analysis to verify that local bias can be harmful to the performance of a parametric estimation model. Results: Our results show that the local bias negatively impacts the performance of parametric model. Our measure of local bias has a positive correlation with the performance by statistical importance. Conclusion: Local calibration by using the whole multi-company data would get worse performance. The influence of multi-company data could be defined by local bias and be measured by our method.Copyright © 2011 ACM.
• Abdimomunova, L., & Valerdi, R. (2010). An organizational assessment process in support of enterprise transformation. Information Knowledge Systems Management, 9(3-4), 175--195.
• Aggarwal, T. (2010). Application of Prediction Markets for Cost and Risk Assessment in Defense Acquisition Programs.
• Brown, S., Valerdi, R., & Muller, G. (2010). Towards a framework of research methodology choices in Systems Engineering.
• Bukhari, H. (2010). Portfolio Risk Index: Characterizing Risk at the Portfolio Level.
• Cowart, K., Valerdi, R., & Kenley, C. R. (2010). Development, Validation and Implementation Considerations of a Decision Support System for Unmanned & Autonomous System of Systems Test & Evaluation.
• Da Xu, L., De Zhou, Z., Lee, J., Valerdi, R., Wang, P., & Zhang, C. (2010). Wuhan, China 19-20 December 2010.
• Deonandan, I., Valerdi, R., Lane, J. A., & Macias, F. (2010). Cost and risk considerations for Test and Evaluation of Unmanned and Autonomous systems of systems. 2010 5th International Conference on System of Systems Engineering, SoSE 2010.
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  Abstract: The evolutionary nature of Unmanned and Autonomous systems of systems (UASoS) acquisition needs to be matched by evolutionary test capabilities yet to be developed. As part of this effort we attempt to understand the cost and risk considerations for UASoS Test and Evaluation (T&E) and propose the development of a parametric cost model to conduct trade-off analyses. This paper focuses on understanding the need for effort estimation for UASoS, the limitations of existing cost estimation models, and how our effort can be merged with the cost estimation processes. We present the prioritization of both technical and organizational cost drivers. We note that all drivers associated with time constraints, integration, complexity, understanding of architecture and requirements are rated highly, while those regarding stakeholders and team cohesion are rated as medium. We intend for our cost model approach to provide management guidance to the T&E community in estimating the effort required for UASoS T&E. © 2010 IEEE.
• Dickerson, C., & Valerdi, R. (2010). Using relational model transformations to reduce complexity in SoS requirements traceability: Preliminary investigation. 2010 5th International Conference on System of Systems Engineering, SoSE 2010.
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  Abstract: The principles and methods of Model Driven Architecture are applied to the problem of requirements traceability for a System of Systems (SoS). Model transformations of operational threads are used to reduce the complexity of modeling mission requirements and their flow into the architecture of the SoS. The allocation of requirements to operational mission threads (OMTs) rather than to individual systems reduces the complexity of the requirements tracing. Relational transformations provide a mathematically based formalism for model transformations that permit precise computation of the transformation of operational threads into threads of systems allocated from the SoS. Connectivity requirements for the SoS are also exposed in this way and the number of permissible system threads are seen to correspond directly to the number of permissible transformations. The principles and methods are illustrated by an elementary case study for sensor fusion. © 2010 IEEE.
• Ferreira, S., Medvidovi{'c}, N., Deonandan, I., Valerdi, R., Hess, J., Mikaelian, T., & Shull, G. (2010). Unmanned and Autonomous Systems of Systems Test and Evaluation: Challenges and Opportunities.
• Hess, J. T. (2010). Adaptive Test Strategies Using PATFrame.
• Hess, J. T., & Valerdi, R. (2010). Test and evaluation of a SoS using a prescriptive and adaptive testing framework. 2010 5th International Conference on System of Systems Engineering, SoSE 2010.
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  Abstract: Testers need the ability to adapt test planning on the order of days and weeks. PATFrame will use its reasoning engine to prescribe the most effective strategies for the situation at hand. Strategies in this context include methods of experimental designs, test schedules and resource allocation. By facilitating rapid planning and re-planning, the PATFrame reasoning engine will enable users to use information learned during the test process to improve the effectiveness of their own testing rather than simply follow a preset schedule. This capability is particularly attractive in the domain of Systems of Systems testing because the complexity of test planning and scheduling make frequent re-planning by hand infeasible. © 2010 IEEE.
• Hess, J., Agarwal, G., Cowart, K. K., Deonandan, I., Kenley, C. R., Mikaelian, T., & Valerdi, R. (2010). Normative and descriptive models for test & evaluation of unmanned and autonomous systems of systems. 20th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2010, 1, 644-654.
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  Abstract: The United States Department of Defense (DoD) has purchased and deployed many unmanned autonomous systems and is expected to do so at an ever-increasing rate in the years to come. These autonomous systems are often expected to operate in system of systems environments. Our research aims to address a number of questions posed by members of DoD's acquisition workforce regarding test and evaluation of these systems. In this paper we present a small set of normative (ideal) and descriptive (actual) models for test and evaluation. We describe test strategies used in the DARPA Grand Challenge competition and the SPHERES test bed, and extract lessons learned from each case study. We will use these models as a step toward identifying prescriptive models for testing unmanned and autonomous systems of systems. The prescriptive models will be implemented within PATFrame (Prescriptive and Adaptive Testing Framework), the decision support system that we are developing. © 2010 by John Hess, Gaurav Agarwal, Kris Cowart, Indira Deonandan, C. Robert Kenley, Tsoline Mikaelian, and Ricardo Valerdi.
• Initiative, L. A., Initiative, S. E., & others, . (2010). Systems Engineering Leading Indicators Guide, Version 2.0.
• Kalawsky, R., & Valerdi, R. (2010). Highlights from the 2009 Conference on Systems Engineering Research and Systems Engineering and Architecting Doctoral Network. INSIGHT, 13(2), 7--9.
• Lane, J. A., & Valerdi, R. (2010). Accelerating system of systems engineering understanding and optimization through lean enterprise principles. 2010 IEEE International Systems Conference Proceedings, SysCon 2010, 196-201.
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  Abstract: By applying a lean enterprise lens to studies of the evolving field of system of systems engineering (SoSE), it has been observed that many SoSE teams are developing processes that are consistent with many lean enterprise principles. These SoSE processes are designed to efficiently evolve the group of systems to meet new needs using limited resources. This paper provides further insights and recommendations for the evolution of system of systems processes using lean concepts. We conclude with a discussion of the potential conflicts between SoSE and lean paradigms and provide thirteen SoS case studies to illustrate the emphasis on lean thinking. ©2010 IEEE.
• Liu, K., Simpkiss, B., Valerdi, R., & Greene, F. (2010). Use of the Air Force HSI Requirements Pocket Guide to Improve Writing and Interpretation of Human-Centered Requirements.
• Liu, K., Valerdi, R., & Laplante, P. A. (2010). Better requirements decomposition guidelines can improve cost estimation of systems engineering and human systems integration 8th Annual Conference on Systems Engineering Research. Hoboken, NJ.
• Madachy, R., & Valerdi, R. (2010). Automating Systems Engineering Risk Assessment.
• Perkins, L. N. (2010). Organizational Assessment: An Essential Tool for Enterprise Transformation.
• Perkins, L. N., Abdimomunova, L., Valerdi, R., Shields, T., & Nightingale, D. (2010). Insights from enterprise assessment: How to analyze LESAT results for enterprise transformation. Information Knowledge Systems Management, 9(3-4), 153--174.
• Perkins, L. N., Valerdi, R., Nightingale, D., & Rifkin, S. (2010). Organizational assessment models for enterprise transformation. 20th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2010, 1, 809-823.
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  Abstract: Organizational assessment is becoming increasingly important, both as a cross-time and cross-industry measurement and as a guiding force in enterprise transformation. Assessments provide crucial information about strengths, areas for improvement and potential investment strategies for achieving performance benefits. As performance is being recognized as a complex and multifaceted construct, assessment tools seek to incorporate and reflect a holistic measurement of performance across multiple dimensions such as stakeholder value, leadership, culture and quality. With a growing range of tools available, this paper examines four prevalent assessment strategies as examples of different approaches to organizational assessment. We compare these tools in terms of use cases, principles measured, outputs and contextual factors. Due to a lack of causal evidence between the principles assessed and objective evidence of improved organizational performance, organizations should utilize the assessment tool that best aligns with key transformation values or goals. By committing to a relevant and useful assessment tool and fully integrating it into strategic processes, organizations are able to achieve the internal knowledge and historical data necessary to improve performance and drive ongoing transformation efforts. © 2010 by L. Nathan Perkins, Ricardo Valerdi, Deborah Nightingale and Stan Rifkin.
• Rhodes, D. H., Ross, A. M., Gerst, K. J., & Valerdi, R. (2010). Extending systems engineering leading indicators for human systems integration effectiveness. INSIGHT, 13(2), 19--24.
• Smith, E. D., Pineda, R. L., Aldous, K., & Valerdi, R. (2010). COSYSMO & COSYSMO-R Parameter Estimation Biases.
• Valerdi, D., & others, . (2010). A Prescriptive and Adaptive Framework for UAS SoS Testing in LVC Environment.
• Valerdi, D., Fortune, D., & others, . (2010). Lessons learned about mixed methods research strategies in systems engineering: Evidence from PhD dissertations.
• Valerdi, D., Pe{~n}a, M., & others, . (2010). Practical Software and Systems Measurement: A Foundation for Objective Project Management.
• Valerdi, R. (2010). Heuristics for Systems Engineering Cost Estimation. IEEE Systems Journal.
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  Abstract: Engineering cannot wait until all phenomena are explained. Engineers may work effectively, often for centuries, with heuristics. This paper provides thirty one heuristics that have been inspired by the development and application of a systems engineering cost estimation model. The objective of this paper is to present such heuristics in a simple manner so that they can benefit systems engineering researchers and practitioners that develop, calibrate, and use cost models.
• Valerdi, R., & Blackburn, C. (2010). Leveraging measurement systems to drive enterprise transformation: Two case studies from the US aerospace industry. Information Knowledge Systems Management, 9(2), 77--97.
• Valerdi, R., & Boehm, B. W. (2010). COSYSMO: A systems engineering cost model.
• Valerdi, R., & Deonandan, I. (2010). A study of the effects of professional society development on the advancement of the profession: The systems engineering example. 20th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2010, 1, 542-556.
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  Abstract: The advancement of professions depends on global collaborations. Professional societies are enablers to this growth in a multitude of ways. Publication outlets to disseminate new ideas, collaboration mechanisms to form communities of interest and conferences to enable networking and recognition all play critical roles in defining and advancing disciplines. In response to this, INCOSE has made a conscious decision to hold its flagship event, the annual Symposium, at strategic locations around the world. At the moment, the majority of INCOSE members, approximately sixty percent, are based in the U.S. although the diversity of membership has increased over time. In this paper, we seek to analyze the impact of hosting a symposium in a particular location through the use of six retrospective case studies to determine how a professional society such as INCOSE can impact the systems engineering profession. We investigate the consequences of hosting a symposium in a specific region and analyze the impact of the symposium on the advancement of the profession of Systems Engineering. © 2010 by Ricardo Valerdi and Indira Deonandan.
• Valerdi, R., & Liu, K. (2010). Parametric Cost Estimation for Human Systems Integration. The Economics of Human Systems Integration: Valuation of Investments in People's Training and Education, Safety and Health, and Work Productivity, 123-161.
• Valerdi, R., & Liu, K. (2010). Parametric cost estimation for human systems integration. The Economics of Human Systems Integration: Valuation of Investments in Peoples Training and Education, Safety and Health, and Work Productivity, 72, 125.
• Valerdi, R., & Rhodes, D. H. (2010). Report from the 2010 Workshop of INCOSE's Systems Engineering and Architecting Doctoral Student Network (SEANET). INSIGHT, 13(2), 53--55.
• Valerdi, R., & Rouse, W. B. (2010). When systems thinking is not a natural act. 2010 IEEE International Systems Conference Proceedings, SysCon 2010, 184-189.
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  Abstract: Competence in systems thinking is implicitly assumed among the population of engineers and managers - in fact, most technical people will self-identify as systems thinkers. But systems thinking competencies are not as prevalent as these assertions might lead one to assume. Controlled experiments show that systems thinking performance, even among highly educated people, is poor. This paper provides a set of systems thinking competencies and demonstrates how these are not as common as advertised. We also discuss how these competencies can be measured. Our main thesis is that systems thinking is not a natural act because evolution has favored mechanisms tuned to dealing with immediate surface features of problems. We discuss the implications of this philosophy and provide recommendations for closing the gap between the demand and supply of systems thinking. ©2010 IEEE.
• Valerdi, R., Aggarwal, T., & Potoski, M. (2010). When More is Better: Design Principles for Prediction Markets in Defense Acquisition Cost Forecasting.
• Valerdi, R., Laplante, P., & others, . (2010). Better Requirements Decomposition Guidelines Can Improve Cost Estimation of Systems Engineering and Human Systems Integration.
• Valerdi, R., Medvidovic, N., Edwards, G., Kenley, C. R., & Macias, F. (2010). Identification and Prioritization of High-Value Test Scenarios for Autonomous Systems Via Architectural Analysis.
• Valerdi, R., Rhodes, D. H., Kimm, C. L., Headen, L. C., & others, . (2010). The F119 Engine: A Success Story of Human Systems Integration in Acquisition.
• Valerdi, R., Sousa, G., & Loureiro, G. (2010). Brazil: INCOSE's New Frontier. INSIGHT, 13(4), 50--50.
• Wang, G., Valerdi, R., & Fortune, J. (2010). Reuse in systems engineering. IEEE Systems Journal, 4(3), 376-384.
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  Abstract: Reuse in systems engineering is a frequent but poorly understood phenomenon. Nevertheless, it has a significant impact on system development and on estimating the appropriate amount of systems engineering effort with models like the Constructive Systems Engineering Cost Model (COSYSMO). Practical experience showed that the initial version of COSYSMO, based on a build from the scratch philosophy, needed to be refined in order to incorporate reuse considerations that fit today's industry environment. The notion of reuse recognizes the effect of legacy system definition in engineering a system and introduces multiple reuse categories for classifying the four COSYSMO size drivers-requirements, interfaces, algorithms, and operational scenarios. It fundamentally modifies the driver counting rules and updates its definition of system size. It provides an enabling framework for estimating a system under incremental and spiral development. In this paper, we present: 1) the definition of the COSYSMO reuse extension and the approach employed to define this extension; 2) the updated COSYSMO size driver definitions to be consistent with the reuse model; 3) the method applied to defining the reuse weights used in the modified parametric relationship; 4) a practical implementation example that instantiates the reuse model by an industry organization and the empirical data that provided practical validation of the extended COSYSMO model; and 5) recommendations for organizational implementation and deployment of this extension. © 2010 IEEE.
• Young, L. Z., Farr, D., John, V., Valerdi, D., & others, . (2010). The role of complexities in systems engineering cost estimating processes.
• Young, L., Valerdi, D., Wade, D., & others, . (2010). A Systematic Approach to Estimate the Life Cycle Cost and Effort of Project Management for Technology Centric Systems Development Projects.
• Adcock, R., Alef, E., Amato, B., Ardis, M., Bernstein, L., Boehm, B., Bourque, P., Brackett, J., Cantor, M., Cassel, L., & others, . (2009). Curriculum guidelines for graduate degree programs in software engineering.
• Adcock, R., Pyster, A., & Valerdi, R. (2009). A Draft Reference Curriculum for Software Engineering Master's Programs. INSIGHT, 12(1), 40--40.
• Blackburn, C., & Valerdi, R. (2009). Navigating the metrics landscape: an introductory literature guide to metric selection, implementation, & decision making.
• Czaika, E., & Valerdi, R. (2009). The culture of innovation styles: Are our corporate cultures tuned for innovation?. 19th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2009, 2, 788-800.
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  Abstract: Systems engineering work is requiring increasing collaboration among various enterperprises, nations, and individuals to innovate to meet the comlex needs of large numbers of stakeholders. This indicates a need to better understand the cultural differences in innovation styles that can enable or hinder collaboration. This paper argues that applying the Hofstede Cross-Cultural Dimensions to enterprises will provide useful insights for systems engineering enterprises in working with cross-cultural teams. Furthermore, this paper seeks to apply the Hofstede dimensions to identifying enterprise cultures conducive to innovation, radical and incremental. By exploring the relationship between the Hofstede Dimensions and Miller and Friesen's Conservative and Entreprenurial Innovation Models, and between the Hofstede Dimensions and Brown's System Model of Technological Innovation, this paper seeks to help enterprises match their culture to the type of innovation their enterprise culture supports. Furthermore, it suggests future research to investigate and compare the Hofstede dimensions of defense organizations and of the companies listed on the BusinessWeek Most Innovative Companies List. © 2009 by Ellen Czaika.
• Dixit, I., Valerdi, D., & others, . (2009). Re-conceptualizing the Work of Systems Engineers.
• Fortune, J., & Valerdi, R. (2009). Definition and initial validation of a systems engineering reuse model. AIAA Space 2009 Conference and Exposition.
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  Abstract: As system complexity increases or resource availability becomes constrained, a common occurrence with space systems, systems engineers are frequently asked to (or seek to) leverage previously developed systems engineering products to reduce cost, schedule, and risk. This research presents the definition and initial validation of a systems engineering cost model (COSYSMO 2.0) for estimating the effect of reuse on systems engineering effort and cost. Copyright © 2009 by The Aerospace Corporation.
• Fortune, J., Valerdi, R., Boehm, B. W., & Settles, F. S. (2009). Estimating systems engineering reuse.
• Gaffney, J. E., Valerdi, R., & Ross, M. A. (2009). Approaches to Calculating Systems Engineering Schedule in Parametric Cost Models.
• Rhodes, D. H., Valerdi, R., & Roedler, G. J. (2009). Systems engineering leading indicators for assessing program and technical effectiveness. Systems Engineering, 12(1), 21-35.
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  Abstract: This paper discusses a 3-year initiative to transform classical systems engineering (SE) measures into leading indicators, including the resulting guidance information that has been developed and future research directions. Systems engineering leading indicators are meas- ures for evaluating the effectiveness of the systems engineering activities on a program in a manner that provides information about impacts that are likely to affect the system or program performance objectives. A leading indicator may be an individual measure, or collection of measures, that is predictive of future system performance before the performance is realized. Contrary to simple status oriented measures typically used on most projects, leading indica- tors are intended to provide insight into the probable future state, allowing projects to improve the management and performance of complex programs before problems arise. This paper discusses the motivations and collaborative development of the SE leading indicators. It defines the leading indicator construct, introduces the initial set of 13 indicators, and provides guidance for implementation, analysis, and interpretation of these indicators. The initial set of indicators, developed through a collaboration of industry, government, and academia, has recently undergone validation through pilot studies and surveys. This work serves as a foundation for industry implementation and for further research to improve and expand the set of indicators, including development of a better understanding of how to best © 2008 Wiley Periodicals, Inc.
• Shields, T., & Valerdi, R. (2009). Enterprise Assessment Diagnostics: Lessons Learned from LAI Members.
• Valerdi, D., & others, . (2009). Navigating the Metrics Landscape: An Introductory Literature Guide to Metric Selection, Implementation, & Decision Making.
• Valerdi, D., & others, . (2009). Optimizing Optimism in Systems Engineers.
• Valerdi, D., & others, . (2009). Practical Implementation of an Enterprise Measurement System: From Inception to Transformation.
• Valerdi, D., & others, . (2009). Predictors of Adoption of Measurement Tools.
• Valerdi, D., & others, . (2009). Using Cost Models to Capture Project Risk: A Knowledge-Based Approach.
• Valerdi, R. (2009). INCOSE's Operations and Finances: Looking Back at 2008 and Forward to 2009. INSIGHT, 12(1), 45--46.
• Valerdi, R., & Blackburn, C. (2009). The human element of decision making in systems engineers: A focus on optimism. 19th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2009, 2, 986-1002.
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  Abstract: Biases continue to be an important aspect of human judgment and decision making because they can lead to unfavorable outcomes. Optimism bias is one type of bias that is often overlooked because of its association with good health and positive outcomes. However, the existence of optimism bias in human judgment can be very damaging especially when it distorts a person's view of future events. In order to better understand optimism bias we explore the benefits and downsides of optimism as well as some empirically-based origins of both optimism and pessimism. This provides a backdrop for a methodology for quantifying optimism and pessimism using the Brier score developed for calibrating weather reporters and a discussion about how sports bookies make well-calibrated decisions. Results are explored from an optimism survey given to a cohort of eighty systems engineers, which ultimately portray the degree to which optimism bias influences decision making in large projects. Further exploration of the key differences in optimism across professions helps distinguish motivational factors and characteristics of well-calibrated professions. We also present results from a calibration exercise, designed to infer if such activities can be adopted to assist systems engineering estimation. Finally, we provide prescriptive advice on how individual decision makers can better manage their optimism and become more realistic. 2009 by Ricardo Valerdi & Craig Blackburn.
• Valerdi, R., & Davidz, H. L. (2009). Empirical research in systems engineering: challenges and opportunities of a new frontier. Systems Engineering, 12(2), 169--181.
• Valerdi, R., Blackburn, C. D., & others, . (2009). Metrics for Enterprise Transformation.
• Valerdi, R., Jain, R., Ferris, T., & Kasser, J. (2009). An Exploration of matching teaching to the learning preferences of systems engineering graduate students. 19th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2009, 3, 1439-1456.
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  Abstract: This paper provides an exploratory study on the relationship between learning preferences of systems engineering graduate students and delivery methods of systems engineering coursework. We begin by providing an overview of learning in the systems engineering context, followed by two central research questions that guide the rest of the paper. Our study is focused on measuring learning preferences based on a previously developed survey instrument called VARK. We provide a detailed description of VARK and some insight into the existing database that sheds light on the typical distribution of learning preferences across disciplines. We provide some preliminary results and discuss their implications on systems engineering curriculum development and delivery. Finally, we discuss additional questions that remain to be explored as we strive to understand the learning preferences of systems engineering graduate students. © 2009 by Ricardo Valerdi, Rashmi Jain, Tim Ferris and Joseph Kasser.
• Wang, G., Shernoff, A., Turnidge, J., & Valerdi, R. (2009). Towards a holistic, total engineering cost model. 19th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2009, 1, 213-231.
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  Abstract: In this paper, we explore a new approach for a unified and interdisciplinary parametric model for estimating the total engineering effort in developing and delivering a software-intensive complex system. We begin by reviewing some of the limitations of using existing engineering discipline-focused tools for estimating total engineering cost and by articulating the benefits of such a holistic model. Applying a two step method combining heuristic analysis and data validation, we propose three hypotheses to expand the basic cost estimating relationship of COSYSMO, a systems engineering model, to the total engineering scope by including software size drivers. The implementation of the hypotheses and the validation approach are also discussed. We conclude the discussion by outlining the future work required to realize such a model and to apply it to supporting successful system development endeavours. © 2009 by Gan Wang, Alex Shernoff, Jon Turnidge, and Ricardo Valerdi.
• Wang, G., Valerdi, R., Roedler, G. J., Ankrum, A., & Gaffney Jr., J. E. (2009). Harmonizing systems and software cost estimation. 19th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2009, 1, 232-252.
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  Abstract: The objective of this paper is to examine the gaps and overlaps between software engineering and systems engineering cost models with intent to harmonize the estimates in engineering estimation. In particular, we evaluate the central assumptions of the COSYSMO and COCOMO II models and propose an approach to identify gaps and overlaps between them. We provide guidelines on how to reconcile and resolve the identified gaps and overlaps. The ultimate purpose of this work is to develop effective techniques for accurately estimating the combined systems and software engineering effort for software-intensive systems.
• Becerra-Fernández, I., Madey, G., Prietula, M., Rodríguez, D., Valerdi, R., & Wright, T. (2008). Design and development of a virtual Emergency Operations Center for disaster management research, training, and discovery. Proceedings of the Annual Hawaii International Conference on System Sciences.
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  Abstract: This paper describes the implementation plans and research activities of Project Ensayo, which is developing a virtual Emergency Operations Center (vEOC) based on one of the Nation's premier EOC's, that of Miami-Dade County. The goal of the EOC is to coordinate for 'community continuity', in other words help communities remain resilient in the face of disaster events. Organizations of this sort suffer from the lack of normal conditions that permit organizational learning in the traditional sense. The development of the Ensayo vEOC will support a portfolio of research projects including topics related to sensor data, knowledge and social networking modeling, decision-making, software approaches to commitment-based collaboration and coordination, time-critical negotiations under emergencies, and cyber-infrastructure resources. © 2008 IEEE.
• Blackburn, C., & Valerdi, R. (2008). Measuring systems engineering success: Insights from baseball. 18th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2008, 4, 2369-2385.
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  Abstract: Optimizing the efficiency of socio-technical systems and determining accurate measurements of performance is a critical issue in many systems engineering enterprises. In our analysis we explore some of the recurring themes of Michael Lewis's study of baseball, depicted in the best selling book Moneyball, and we make the connection to corresponding systems engineering principles of interest. The paper will focus on the systems engineering roadmap inspired by Lewis' study for developing and refining a meaningful set of metrics for organizational transformation. The following steps are highlighted to convey this transformation with the assistance of metrics: identify and understand value in the enterprise and your organization; consider an integrated system focus in your organization; use cost analysis methods to implement a strategy for executing the transformation; and manage risk throughout operations and improve the process continuously. © 2008 by Craig Blackburn & Ricardo Valerdi.
• Boehm, B. W., & Valerdi, R. (2008). Achievements and challenges in cocomo-based software resource estimation. IEEE Software, 25(5), 74-83.
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  Abstract: This article summarizes major achievements and challenges of software resource estimation over the last 40 years, emphasizing the Cocomo suite of models. Critical issues that have enabled major achievements include the development of good model forms, criteria for evaluating models, methods for integrating expert judgment and statistical data analysis, and processes for developing new models that cover new software development approaches. The article also projects future trends in software development and evolution processes, along with their implications and challenges for future software resource estimation capabilities. © 2008 IEEE.
• Boehm, B., Valerdi, R., & Honour, E. (2008). The ROI of systems engineering: Some quantitative results for software-intensive systems. Systems Engineering, 11(3), 221-234.
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  Abstract: This paper presents quantitative results on the return on investment of systems engineering (SE-ROI) from an analysis of the 161 software projects in the COCOMO II database. The analysis shows that, after normalizing for the effects of other cost drivers, the cost difference between projects doing a minimal job of software systems engineering-as measured by the thoroughness of its architecture definition and risk resolution-and projects doing a very thorough job was 18% for small projects and 92% for very large software projects as measured in lines of code. The paper also presents applications of these results to project experience in determining "how much up front systems engineering is enough" for baseline versions of smaller and larger software projects, for both ROI-driven internal projects and schedule-driven outsourced systems of systems projects. © 2008 Wiley Periodicals, Inc.
• Fortune, J., & Valerdi, R. (2008). Considerations for successful reuse in systems engineering. Space 2008 Conference.
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  Abstract: Reuse is the idea of leveraging previously developed capabilities into a new project for the purposes of improving project characteristics (i.e. cost, schedule, risk). While reuse is a fairly well-known concept in domains such as software and product development, almost no research has been conducted on reuse in the systems engineering domain. This paper provides six general principles of reuse, identifies success factors for reuse, and summarizes some key challenges and opportunities for future research in the area of reuse in systems engineering. Copyright © 2008 by the American Institute of Aeronautics and Astronautics, Inc.
• Ling, L. i., Valerdi, R., & Warfield, J. N. (2008). Advances in enterprise information systems. Information Systems Frontiers, 10(5), 499-501.
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  Abstract: Various recent research activities reported by Information Systems Frontiers, regarding the advancements of Enterprise Information Systems (EIS), which enables longterm strategic impact on global business and world economy, are presented. The study by Møller and others examines the development of a Virtual Enterprise Architecture for an automatic high-speed transport and sorting system applied to airports. The paper on role-oriented process-driven enterprise cooperative work using the combined rule scheduling strategies, proposes a dynamic Project Evaluation and Review Technique/Critical Path Method approach and discusses its applications in dynamic enterprise process scheduling. The paper by Li and others presents a newly-developed environmental health information system, a web-based platform that integrates databases, decision-making tools, and geographic information systems for supporting public health service and policy making.
• Valerdi, R. (2008). Cultural Barriers to the Adoption of Systems Engineering Research.
• Valerdi, R. (2008). Zen in the Art of Cost Estimation.
• Valerdi, R., & Rhodes, D. H. (2008). Report from the 2008 Workshop of INCOSE-s Systems Engineering & Architecting Doctoral Student Network (SEANET). INSIGHT, 11(3), 53--54.
• Valerdi, R., Axelband, E., Baehren, T., Boehm, B., Dorenbos, D., Jackson, S., Madni, A., Nadler, G., Robitaille, P., & Settles, S. (2008). A research agenda for systems of systems architecting. International Journal of System of Systems Engineering, 1(1-2), 171-188.
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  Abstract: This paper, documents the activity of a workshop on defining a research agenda for Systems of Systems SoS; Architecting, which was held at USC in October 2006. After two days of invited talks on critical success factors for SoS engineering, the authors of this paper convened for one day to brainstorm topics for the purpose of shaping the near-term research agenda of the newly convened USC Center for Systems and Software Engineering (CSSE). The output from the workshop is a list of ten high-impact items with corresponding research challenges in the context of SoS Architecting. Each item includes a description of the research challenges, its link to contemporary academic or industrial problems and reasons for advocacy of that area. The items were assessed in terms of value and difficulty to determine a prioritisation both for the CSSE's future research agenda and for others in the field. Copyright © 2008 Inderscience Enterprises Ltd.
• Valerdi, R., Fortune, J., & Wheaton, M. J. (2008). Estimating the Cost of Systems Engineering for Space Systems. INSIGHT, 11(5), 34--38.
• Valerdi, R., Haskins, C., Roussel, J., Kizilca, H., & Lisi, M. (2008). Could You Say That Again, Please?. INSIGHT, 11(3), 55--57.
• Valerdi, R., Nightingale, D., & Blackburn, C. (2008). Enterprises as systems: Context, boundaries, and practical implications. Information Knowledge Systems Management, 7(4), 377--399.
• Wang, G., Valerdi, R., Ankrum, A., Millar, C., & Roedler, G. J. (2008). COSYSMO reuse extension. 18th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2008, 4, 2456-2472.
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  Abstract: Reuse in systems engineering is a frequent, but poorly understood phenomenon. Nevertheless, it has a significant impact on estimating the appropriate amount of systems engineering effort with models like the Constructive Systems Engineering Cost Model. Practical experience showed that the initial version of COSYSMO, a model based on a "build from the scratch" philosophy, needed to be refined in order to incorporate reuse considerations that fit today's industry environment. The notion of reuse recognizes the effect of legacy system definition in engineering a system and introduces multiple reuse categories for classifying each of the four COSYSMO size drivers - requirements, interfaces, algorithms, and operational scenarios. It fundamentally modifies the counting rules for the COSYSMO size drivers and updates the definition of system size in COSYSMO. In this paper, we present (1) the definition of the COSYSMO reuse extension and the approach employed to define this extension; (2) the updated COSYSMO size driver definitions that are consistent with the reuse model; (3) the method applied to defining the reuse weights used in the modified parametric relationship; (4) a practical implementation example that instantiates the reuse model by an industry organization and the empirical data that provided practical validation of the extended COSYSMO model; and (5) recommendations for organizational implementation and deployment of this extension. © 2008 by Gan Wang, Ricardo Valerdi, Aaron Ankrum, Cort Millar, Garry Roedler.
• Wang, G., Valerdi, R., Boehm, B., & Shernoff, A. (2008). Proposed modification to COSYSMO estimating relationship. 18th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2008, 4, 2473-2485.
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  Abstract: This paper proposes a modification to the Academic COSYSMO estimating relationship to remedy a critical limitation in its current implementation of the cost drivers. The effort multipliers defined for these drivers have an overdramatic impact on the nominal effort, which unrealistically amplifies or compresses the effort estimate. This problem severely limits its practical applications. The newly proposed parametric relationship is inspired by the COCOMO II modeling approach and based on the considerations of the life cycle impact of the cost drivers. Two additional cost drivers are also introduced. The feasibility of the new model definition is examined with a boundary analysis and validated by the analysis of historical data. This work is based on the practical implementation of COSYSMO at BAE Systems. In this paper, we present (1) an analysis of the problem with the current COSYSMO model definition; (2) a proposal of two new cost drivers added to the current fourteen cost drivers; (3) an analysis of life cycle impact of the cost drivers and a division of the drivers based on the impact; (4) the modified COSYSMO parametric relationship; (5) validation of the modified COSYSMO relationship through an analysis of historical data; and (6) conclusion and suggestion of future work. © 2008 by Gan Wang, Ricardo Valerdi, Barry Boehm, Alex Shernoff.
• Axelband, E., Baehren, T., Dorenbos, D., Madni, A., Robitaille, P., Valerdi, R., Boehm, B., Jackson, S., Nadler, G., & Settles, S. (2007). A research agenda for systems of systems architecting. 17th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2007 - Systems Engineering: Key to Intelligent Enterprises, 3, 1987-2003.
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  Abstract: This paper documents the activity of a workshop on defining a research agenda for Systems of Systems (SoS) Architecting, which was held at USC in October 2006. After two days of invited talks on critical success factors for SoS engineering, the authors of this paper convened for one day to brainstorm topics for the purpose of shaping the near-term research agenda of the newly convened USC Center for Systems & Software Engineering. The output from the workshop is a list of ten high-impact items with corresponding research challenges in the context of SoS Architecting. Each item includes a description of the research challenges, its link to contemporary academic or industrial problems, and reasons for advocacy of that area. The items were assessed in terms of value and difficulty to determine a prioritization both for the CSSE's future research agenda and for others in the field. © 2007 by Axelband, Valerdi, Baehren, Boehm, Dorenbos, Jackson, Madni, Nadler, Robitaille, and Settles.
• Boehm, B., & Valerdi, R. (2007). The ROI of systems engineering: some quantitative results. Proceedings - 2007 IEEE Conference on Exploring Quantifiable IT Yields, EQUITY 2007, 79-86.
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  Abstract: This paper presents quantitative results on the return on investment of systems engineering (SE-ROI) from an analysis of the 161 software projects in the COCOMOII database. The analysis shows that, after normalizing for the effects of other cost drivers, the cost difference between projects doing a minimal job of software systems engineering - as measured by the thoroughness of its architecture definition and risk resolution - and projects doing a very thorough job was 18% for small projects and 92% for very large software projects as measured in lines of code. ©2008 IEEE.
• Boehm, B., Valerdi, R., & Honour, E. (2007). The ROI of systems engineering: Some quantitative results. 17th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2007 - Systems Engineering: Key to Intelligent Enterprises, 2, 851-865.
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  Abstract: This paper presents quantitative results on the return on investment of systems engineering (SE-ROI) from an analysis of the 161 software projects in the COCOMO II database. The analysis shows that, after normalizing for the effects of other cost drivers, the cost difference between projects doing a minimal job of software systems engineering - as measured by the thoroughness of its architecture definition and risk resolution - and projects doing a very thorough job was 18% for small projects and 92% for very large software projects as measured in lines of code. © 2007 by Barry Boehm, Ricardo Valerdi, and Eric Honour.
• Dixit, I., & Valerdi, R. (2007). Challenges in the development of systems engineering as a profession. 17th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2007 - Systems Engineering: Key to Intelligent Enterprises, 2, 866-881.
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  Abstract: This paper explores a fundamental and important question: is Systems Engineering a profession? It is fundamental because of the current existential crisis in the discipline and it is important because it helps in defining our role in the context of the greater technical community. By observing systems engineering through the theoretical lens of the professionalization literature rooted in sociology, we propose five key challenges to systems engineering as a profession. Firstly, defining the problem space, secondly, understanding the state of the body of knowledge, thirdly, the impact of lifecycle perspective, fourthly, the falsification of systems engineering theories and lastly, the question of standard of proof for systems engineering. The need for our thesis is motivated by understanding the current body of knowledge and proposing a direction that will enable the profession to overcome key challenges. © 2007 by Indrajeet Dixit and Ricardo Valerdi.
• Fong, A. (2007). Boundary Objects: Improving Inter-organizational Communication.
• Fong, A., Valerdi, R., & Srinivasan, J. (2007). Boundary objects as a framework to understand the role of systems integrators. Systems Research Forum, 2(1), 11-18.
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  Abstract: The US Department of Defense is facing challenges to develop the capabilities necessary to effectively operate in new operational environments. As a result, these services are seeking to partner with industry members and leverage both government and industry knowledge to develop System of Systems (SoS) that can provide the desired capabilities by integrating legacy systems with new technologies. These large-scale engineering projects require system integrators that can manage not only the technical interfaces but also the organizational ones. This paper proposes a boundary object framework that can assist in understanding the role of these systems integrators by observing changes in organizational interfaces. This framework does so by monitoring the objects and artifacts used at the interfaces. © 2007 World Scientific Publishing Company.
• Fong, A., Valerdi, R., & Srinivasan, J. (2007). Using a boundary object framework to analyze interorganizational collaboration. 17th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2007 - Systems Engineering: Key to Intelligent Enterprises, 3, 1938-1952.
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  Abstract: The U.S. military is facing a plethora of challenges as a result of tightening procurement budgets and the need to acquire new capabilities to operate in modern war environments. This requires integrating legacy systems with developing technologies in what is loosely defined to be a System of Systems. Most Systems of Systems require some integrator to manage and operate the system interfaces. In addition to technical integration challenges, these system integrators have the difficult undertaking of integrating various organizations. The boundary object framework proposed by this paper provides a tool for systems integrators working in System of Systems or any type of complex system to identify and categorize communication, coordination, and collaboration interfaces and address possible failures. © 2007 by Allan Fong, Ricardo Valerdi, Jayakanth Srinivasan.
• Initiative, L. A., & others, . (2007). Systems Engineering Leading Indicators Guide, Version 1.0.
• Kitterman, D., Griego, R. M., Valerdi, R., & Machado, M. (2007). First Latin America and Caribbean Initiative Dinner. INSIGHT, 10(2), 67--67.
• Lane, J. A., & Valerdi, R. (2007). Synthesizing SoS concepts for use in cost modeling. Systems Engineering, 10(4), 297-308.
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  Abstract: Today's need for more complex, capable systems in a short timeframe is leading many organizations towards the integration of existing systems into network-centric, knowledge-based system-of-systems (SoS). This presents new acquisition challenges in the area of cost estimation because of the lack of commonly accepted definitions and roles. Software and system cost models to date have focused on the software and system development activities of a single system. When viewing the new SoS architectures, one finds that the cost associated with the design and integration of these SoSs is not handled well, if at all, in current cost models. This paper looks at commonly cited definitions of SoS, then evaluates these definitions to determine if they adequately describe and converge on a set of SoS characteristics in the areas of product, development process, and development personnel that can be used to define boundaries and key parameters for an initial SoS cost model. Sixteen SoS definitions are synthesized to provide reasonable coverage for different properties of SoSs. Two examples are used to illustrate key characteristics relevant to cost modeling. © 2007 Wiley Periodicals, Inc.
• Normative, D. (2007). A Framework for Evolving System of Systems Engineering.
• Rhodes, D. H., & Valerdi, R. (2007). Enabling research synergies through a doctoral research network for systems engineering. Systems Engineering, 10(4), 348-360.
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  Abstract: As contrasted with traditional engineering and science fields, doctoral research in systems engineering is characterized by several unique factors. These include the relatively young tradition of systems engineering academic programs, the necessity for hybrid research methodologies, the existence of strong links with industry and government, and a nontraditional makeup of students in regard to their background, experience levels, and career goals. The International Council on Systems Engineering (INCOSE) has set strategic objectives and policies to encourage doctoral level research in systems engineering, and has recently undertaken an initiative to create a doctoral student research network. This paper describes the motivations for and formation of the Systems Engineering and Architecting Doctoral Student Network (SEANET), and presents findings from a survey conducted at the 2006 inaugural workshop event. While limited, this survey gives insight into the demographics of students and underscores the essential role of a network in motivating, encouraging, and shaping doctoral research in systems engineering. Implications are discussed based on three key findings from the survey. These include: (1) The pool of systems engineering doctoral students is largely nontraditional; (2) students identified attending workshops and access to data as the two most pressing issues that professional societies can help with; and (3) doctoral students in systems engineering have a high diversity of career interests. Professional societies play an important role in encouraging and enabling systems engineering research, and sponsorship of a research network is an effective mechanism for this goal given that such societies can provide a neutral venue for this interchange. ©2007 Wiley Periodicals, Inc.
• Rhodes, D., & Valerdi, R. (2007). Enabling Research Synergies through a Doctoral Research Network for System Engineering. INSIGHT, 10(3), 17--18.
• Valerdi, R. (2007). Cognitive limits of software cost estimation. Proceedings - 1st International Symposium on Empirical Software Engineering and Measurement, ESEM 2007, 117-125.
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  Abstract: This paper explores the cognitive limits of estimation in the context of software cost estimation. Two heuristics, representativeness and anchoring, motivate two experiments involving psychology students, engineering students, and engineering practitioners. The first experiment, designed to determine if there is a difference in estimating ability in everyday quantities, demonstrates that the three populations estimate with relatively equal accuracy. The results shed light on the distribution of estimates and the process of subjective judgment. The second experiment, designed to explore abilities for estimating the cost of software-intensive systems given incomplete information, shows that predictions by engineering students and practitioners are within 3-12% of each other. The value of this work is in helping better understand how software engineers make decisions based on limited information. The manifestation of the two heuristics is discussed together with the implications for the development of software cost estimation models in light of the findings from the two experiments.
• Valerdi, R. (2007). Myth Buster: Do Engineers Trust Parametric Models Over Their Own Intuition?.
• Valerdi, R. (2007). Pioneers of parametrics.
• Valerdi, R., & Madachy, R. (2007). Impact and contributions of MBASE on software engineering graduate courses. Journal of Systems and Software, 80(8), 1185-1190.
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  Abstract: As the founding Director of the Center for Software Engineering, Professor Barry Boehm developed courses that have greatly impacted the education of software engineering students. Through the use of the MBASE framework and complementary tools, students have been able to obtain real-life software development experience without leaving campus. Project team clients and the universities have also benefited. This paper provides evidence on the impact of Dr. Boehm's frameworks on courses at two universities, and identifies major contributions to software engineering education and practice. © 2006 Elsevier Inc. All rights reserved.
• Valerdi, R., & Miller, C. (2007). From research to reality: Making COSYSMO a trusted estimation tool in your organization. 17th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2007 - Systems Engineering: Key to Intelligent Enterprises, 3, 1980-1986.
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  Abstract: As the COSYSMO model transitions from the development phase into the adoption phase, industry stakeholders are beginning to embrace the model and integrate it into their existing measurement processes. To date, much of the guidance provided by the COSYSMO development team has been focused on the usage of the model. In the adoption phase, users need guidance on how to adopt the model as they work to convince management to invest resources in competition with other process improvement initiatives. This paper outlines a process which provides guidance on the piloting and institutionalization of COSYSMO designed to help scope the effort needed for successful adoption and implementation. The process has been developed as a result of interactions with over a dozen organizations that have participated in the industry calibration of the model and have begun to integrate the model into their internal processes. The knowledge obtained from working with these organizations is reflected in this process. © 2007 by Ricardo Valerdi and Chris Miller.
• Valerdi, R., E., J., Roedler, G. J., Wheaton, M. J., & Wang, G. (2007). Lessons learned from industrial validation of COSYSMO. 17th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2007 - Systems Engineering: Key to Intelligent Enterprises, 2, 839-850.
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  Abstract: The development of COSYSMO has been an ongoing collaboration between industry, government, and academia since 2001. INCOSE provided expertise as well as a forum for collaboration between stakeholders that led to the eventual development of the model. In 2004, we provided eleven lessons learned from experiences collecting systems engineering data from six companies in collaboration with the INCOSE Measurement Working Group and the Practical Software and Systems Measurement (PSM). These lessons were focused on the development of COSYSMO that was motivated by a similar model from the software domain, COCOMO II, but was a first of its kind for systems engineering. Now that the development phase of the model is completed we take a retrospective view of lessons learned during the ongoing validation phase of the model and present new lessons learned that should help cost model developers, academic researchers, and practitioners develop and validate similar approaches. These lessons include the need for more specific counting rules, an approach to account for reuse in systems engineering, and strategies for model adoption in organizations. © 2007 by Ricardo Valerdi, John Rieff, Garry Roedler, Marilee Wheaton, and Gan Wang.
• Valerdi, R., Ross, A. M., & Rhodes, D. H. (2007). A framework for evolving system of systems engineering. CrossTalk, 20(10), 28-30.
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  Abstract: We provide a framework for examining the differences between systems engineering and system of systems engineering (SoSE). By taking normative, descriptive, and prescriptive views of these constructs, similarities and differences can be better identified. Moreover, we note that additional work is needed in the development of normative and prescriptive models in order to advance our understanding of both systems engineering and SoSE.
• Valerdi, R., Srinivasan, J., Nightingale, N., & others, . (2007). From Good To Lean: The Bottom Line Impact of Enterprise Lean Transformation.
• Valerdi, R., Wheaton, M. J., & Fortune, J. (2007). Systems engineering cost estimation for space systems. A Collection of Technical Papers - AIAA Space 2007 Conference, 1, 8-17.
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  Abstract: The applicability of COSYSMO, a systems engineering cost model, is explored in the context of space systems through the analysis of two main assumptions. First, the WBS elements of the model are mapped to a prototypical WBS for space systems. Second, the life cycle phases assumed in the model are mapped to the phases outlined in the latest National Security Space acquisition policy. Through the analysis of these assumptions, the applicability of COSYSMO to space systems can be improved. Moreover, techniques for performing partial estimation of systems engineering by systems engineering activity and life cycle phase are provided to further the applicability of COSYSMO to space systems.
• Boehm, B. W., & Valerdi, R. (2006). Achievements and challenges in software resource estimation. development, 4, 30.
• Collar Jr, E., & Valerdi, R. (2006). Role of software readability on software development cost.
• Honour, E. C., & Valerdi, R. (2006). Advancing an ontology for systems engineering to allow consistent measurement.
• Nightingale, D., Valerdi, D., & others, . (2006). Coupling Lean Thinking and Systems Thinking at the Enterprise Level.
• Valerdi, R. (2006). A theory of objective sizing.
• Valerdi, R. (2006). Systems Engineering Cost Estimation Across BAE Systems: Trans-Atlantic Collaboration and Identification of Future Opportunities.
• Valerdi, R., & Dixit, I. (2006). On the use of architectural products for cost estimation.
• Valerdi, R., & Madachy, R. (2006). Impact & contributions of MBASE on software engineering graduate courses. Software Engineering Education Conference, Proceedings, 2006, 209-215.
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  Abstract: As the founding Director of the Center for Software Engineering, Professor Barry W. Boehm developed courses that have greatly impacted the education of software engineering students. Through the use of the MBASE framework and complementary tools, students have been able to obtain real-life software development experience without leaving campus. Project team clients and the universities have also benefited. This paper provides evidence on the impact of Dr. Boehm's frameworks on courses at two universities, and identifies major contributions to software engineering education and practice. © 2006 IEEE.
• Valerdi, R., Gaffney, J., Roedler, G., & Rieff, J. (2006). Extensions of COSYSMO to represent reuse.
• Wang, G., Lane, J. A., Valerdi, R., & Boehm, B. (2006). Towards a work breakdown structure for net centric system of systems engineering and management. 16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006, 1, 309-323.
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  Abstract: As the system engineering industry sees an increasing focus on the lifecycle development, acquisition, and sustainment of net-centric Systems of Systems (SoS) and Family of Systems (FoS), organizations find the need to evolve current processes and tools to better handle the increased scope, scale, and complexity of these efforts. One such tool, the Work Breakdown Structure (WBS) is important in planning and execution of program activities as requirements and goals of the program evolve. This paper provides an overview of the limitations of current WBSs with respect to SoS efforts and presents a proposed WBS structure that more adequately reflects the evolving processes and cross-organizational complexities. Copyright © 2006 by G. Wang, J. Lane, R. Valerdi and B. Boehm.
• Boehm, B., Valerdi, R., Lane, J. A., & Brown, A. W. (2005). COCOMO suite methodology and evolution. CrossTalk, 20-25.
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  Abstract: An overview of the models in the COCOMO suite that includes extensions and independent models, and describes the underlying methodologies and the logic behind the models and how they can be used together to support larger software system estimation needs, is presented. The models in this suite provide specialized set of estimates that address specific aspects of development effort for software-intensive systems. The models also provide a set of tools that enable more comprehensive cost estimates. The developments done on multiple COCOMO models in parallel for cost estimates that cover a broader scope that exceeds the boundaries of traditional software development are discussed.
• Boehm, B., Valerdi, R., Lane, J., & Brown, A. (2005). COCOMO suite methodology and evolution. CrossTalk, 18(4), 20--25.
• Lane, J. A., & Valerdi, R. (2005). Synthesizing SoS concepts for use in cost estimation. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 1, 993-998.
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  Abstract: Today's need for more complex, capable systems in a short timeframe is leading many organizations towards the integration of existing systems into network-centric, knowledge-based system-of-systems (SoS). Software and system cost model tools to date have focused on the software and system development activities of a single system. When viewing the new SoS architectures, one finds that the effort associated with the design and integration of these SoSs is not handled well, if at all, in current cost models. This paper includes (1) a comparison of various SoS definitions and concepts with respect to cost models, (2) a classification of these definitions in terms of product, process, and personnel focus, and (3) the definition of a set of discriminators for defining model boundaries and potential drivers for an SoS cost estimation model. Eleven SoS definitions are synthesized to provide reasonable coverage for different properties of SoS and illustrated in two examples. ©2005 IEEE.
• Lane, J., & Valerdi, R. (2005). Synthesizing systems-of-systems concepts for use in cost estimation. Proceedings, IEEE SMC.
• Roedler, G., & Rhodes, D. (2005). Systems Engineering Leading Indicators Guide-Beta Release.
• Roetzheim, W., Jones, C., Dekkers, C. A., Putnam, L. H., Putnam, D. T., Beckett, D. M., Boehm, B., Valerdi, R., Lane, J. A., Brown, A. W., & others, . (2005). Cost Estimation. crosstalk, 801, 775--5555.
• Valerdi, R. (2005). Cost metrics for unmanned aerial vehicles. Collection of Technical Papers - InfoTech at Aerospace: Advancing Contemporary Aerospace Technologies and Their Integration, 3, 1753-1758.
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  Abstract: This paper aims to enhance the understanding of UAV cost metrics and their uses. The paper is organized into three main areas: (1) overview of current approaches for aircraft, (2) life cycle issues with UAV cost estimation, and (3) cost metrics and model approach as applied to UAVs. As a result of this work we hope to provide a better understanding of the cost factors influencing the recently publicized scrutiny of UAV cost overruns. More importantly, we hope to begin the foundation for the development of Cost Estimating Relationships (CERs) that can potentially lead to the development of a parametric cost model for UAVs. Copyright © 2005 by MIT & The Aerospace Corporation.
• Valerdi, R. (2005). IIE Annual Conference, Atlanta, GA.
• Valerdi, R., & Eiche, B. (2005). On counting requirements. Proceedings CSER, 23--25.
• Valerdi, R., & Raj, J. (2005). Sea level requirements as systems engineering size metrics. 15th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2005, 2, 989-1002.
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  Abstract: The Constructive Systems Engineering Cost Model (COSYSMO) represents a collaborative effort between industry, government, and academia to develop a general model to estimate systems engineering effort. The model development process has benefited from a diverse group of stakeholders that have contributed their domain expertise and historical project data for the purpose of developing an industry calibration. But the use of multiple stakeholders having diverse perspectives has introduced challenges for the developers of COSYSMO. Among these challenges is ensuring that people have a consistent interpretation of the model's inputs. A consistent understanding of the inputs enables maximum benefits for its users and contributes to the model's predictive accuracy. The main premise of this paper is that the reliability of these inputs can be significantly improved with the aide of a sizing framework similar to one developed for writing software use cases. The focus of this paper is the first of four COSYSMO size drivers, # of Systems Requirements, for which counting rules are provided. In addition, two different experiments that used requirements as metrics are compared to illustrate the benefits introduced by counting rules.© 2005 by Ricardo Valerdi and Jatin Raj. Published and used by INCOSE with permission.
• Valerdi, R., & Wheaton, M. (2005). ANSI/EIA 632 as a standardized WBS for COSYSMO. Collection of Technical Papers - AIAA 5th ATIO and the AIAA 16th Lighter-than-Air Systems Technology Conference and Balloon Systems Conference, 2, 631-636.
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  Abstract: This paper provides an update on the systems engineering model (COSYSMO) being developed by the Center for Software Engineering at the University of Southern California in conjunction with its corporate affiliates and the International Council for Systems Engineering (INCOSE). The model will help organizations better estimate and plan their systems engineering activities that include development, integration, and test. In this light, the COSYSMO working group has focused on establishing the scope of the model through the ANSI/EIA 632 Systems Engineering standard. It was recognized early on that systems engineering activities varied extensively across organizations and projects. The key to collecting consistent data across disparate organizations was to clearly define the content in a WBS that was understandable by the systems engineering and cost estimation communities. Mappings have also established between each organization's or project's WBS elements and the COSYSMO standard WBS elements. The standardized WBS has become the framework for discussion of what systems engineering activities are included and excluded for a particular cost estimate. The paper will cover systems engineering and industry standards, the use of these standards in the COSYSMO model development process, and an analysis of the distribution of ANSI/EIA 632 activities covered in COSYSMO. Copyright © 2005 by University of Southern California & The Aerospace Corporation.
• Yang, Y., Chen, Z., Valerdi, R., & Boehm, B. (2005). Effect of Schedule Compression on Project Effort.
• Chen, Y., Boehm, B. W., Madachy, R., & Valerdi, R. (2004). An empirical study of eServices product UML sizing metrics. Proceedings - 2004 International Symposium on Empirical Software Engineering, ISESE 2004, 199-206.
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  Abstract: Size is one of the most fundamental measurements of software. For the past two decades, the source line of code (SLOC) and function point (FP) metrics have been dominating software sizing approaches. However both approaches have significant defects. For example, SLOC can only be counted when the software construction is complete, while the FP counting is time consuming, expensive, and subjective. In the late 1990s researchers have been exploring faster, cheaper, and more effective sizing methods, such as Unified Modeling Language (UML) based software sizing. In this paper we present an empirical 14-project-study of three different sizing metrics which cover different software life-cycle activities: requirement metrics (requirement), UML metrics (architecture), and SLOC metrics (implementation). Our results show that the software size in terms of SLOC was moderately well correlated with the number of external use cases and the number of classes. We also demonstrate that the number of sequence diagram steps per external use case is a possible complexity indicator of software size. However, we conclude that at least for this 14-project eServices applications sample, the UML-based metrics were insufficiently well-defined and codified to serve as precise sizing metrics.
• Valerdi, R. (2004). COSYSMO Working Group Report. INSIGHT, 7(3), 24--25.
• Wheaton, M. (2004). PSM.
• Valerdi, R., & Majchrzak, A. (2003). Individual players in a team sport: Stakeholder change in commitment in ISD projects. AMCIS 2003 Proceedings, 171.
• Valerdi, R. (2002). ISE590 Independent Research.

Proceedings Publications

• Wang, G., Roedler, G. J., Pena, M., & Valerdi, R. (2014). 3.3. 1 A Generalized Systems Engineering Reuse Framework and Its Cost Estimating Relationship. In INCOSE International Symposium, 24.
• Valerdi, R., & Christopherson, T. L. (2013). 6.3. 1 COSYSMO Calibration Steps and Results. In INCOSE International Symposium, 23.
• Wang, G., Roedler, G. J., Valerdi, R., & Pena, M. (2013). 9.2. 2 Quantifying Systems Engineering Reuse--a Generalized Reuse Framework in COSYSMO. In INCOSE International Symposium, 23.
• Valerdi, R., & Zonnenshain, A. (2012). Teaching Them How to Fish: Industry-Focused Student Projects in Systems Engineering. In INCOSE International Symposium, 22.
• Valerdi, R., & Zonnenshain, A. (2012). Teaching them how to fish. In 22nd Annual International Symposium of the International Council on Systems Engineering, INCOSE 2012 and the 8th Biennial European Systems Engineering Conference 2012, EuSEC 2012.
• Boehm, B., & Valerdi, R. (2011). Impact of software resource estimation research on practice: a preliminary report on achievements, synergies, and challenges. In 2011 33rd International Conference on Software Engineering (ICSE).
• Boghosian, M., & Valerdi, R. (2011). Cost Estimating Methodology for Very Small Satellites. In COCOMO Forum.
• Lane, J. A., & Valerdi, R. (2011). System Interoperability Influence on System of Systems Engineering Effort. In Proceedings of the Conference on Systems Engineering Research.
• Valerdi, R. (2011). 10.4. 2 Convergence of Expert Opinion via the Wideband Delphi Method: An Application in Cost Estimation Models. In INCOSE International Symposium, 21.
• Valerdi, R. (2011). Convergence of expert opinion via the wideband delphi method. In 21st Annual International Symposium of the International Council on Systems Engineering, INCOSE 2011.
• Yang, Y., Xie, L., He, Z., Li, Q., Nguyen, V., Boehm, B., & Valerdi, R. (2011). Local bias and its impacts on the performance of parametric estimation models. In Proceedings of the 7th International Conference on Predictive Models in Software Engineering.
• Deonandan, I., Valerdi, R., Lane, J. A., & Macias, F. (2010). Cost and risk considerations for test and evaluation of unmanned and autonomous systems of systems. In System of Systems Engineering (SoSE), 2010 5th International Conference on.
• Dickerson, C., & Valerdi, R. (2010). Using relational model transformations to reduce complexity in SoS requirements traceability: Preliminary investigation. In System of Systems Engineering (SoSE), 2010 5th International Conference on.
• Hess, J. T., & Valerdi, R. (2010). Test and evaluation of a SoS using a prescriptive and adaptive testing framework. In System of Systems Engineering (SoSE), 2010 5th International Conference on.
• Hess, J., Agarwal, G., Cowart, K. K., Deonandan, I., Kenley, C. R., Mikaelian, T., & Valerdi, R. (2010). 5.2. 2 Normative and Descriptive Models for Test & Evaluation of Unmanned and Autonomous Systems of Systems. In INCOSE International Symposium, 20.
• Lane, J. A., & Valerdi, R. (2010). Accelerating system of systems engineering understanding and optimization through lean enterprise principles. In Systems Conference, 2010 4th Annual IEEE.
• Perkins, L. N., Nightingale, D., Valerdi, R., & Rifkin, S. (2010). 6.3. 2 Organizational Assessment Models for Enterprise Transformation. In INCOSE International Symposium, 20.
• Valerdi, R., & Deonandan, I. (2010). 4.4. 3 A Study of the Effects of Professional Society Development on the Advancement of the Profession: The Systems Engineering Example. In INCOSE International Symposium, 20.
• Valerdi, R., & Rouse, W. B. (2010). When systems thinking is not a natural act. In Systems Conference, 2010 4th Annual IEEE.
• Valerdi, R., Brown, S., & Muller, G. (2010). Towards a framework of research methodology choices in Systems Engineering. In 8th Annual Conference on Systems Engineering Research (CSER 2010), Hoboken, NJ.
• Blackburn, C., & Valerdi, R. (2009). Practical implementation of an enterprise measurement system: from inception to transformation. In 7th Annual Conference on Systems Engineering Research.
• Czaika, E., & Valerdi, R. (2009). 5.2. 2 The Culture of Innovation Styles: Are our Corporate Cultures Tuned for Innovation?. In INCOSE International Symposium, 19.
• Czaika, E., & Valerdi, R. (2009). The culture of innovation styles. In 19th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2009.
• Lane, J. (2009). Cost model extensions to support systems engineering cost estimation for complex systems and systems of systems. In 7th Annual Conference on Systems Engineering Research.
• Liu, K., Valerdi, R., & Rhodes, D. H. (2009). Economics of human systems integration: The Pratt & Whitney F119 engine. In Conference on Systems Engineering Research.
• Valerdi, R., & Blackburn, C. (2009). 6.3. 1 The Human Element of Decision Making in Systems Engineers: A Focus on Optimism. In INCOSE International Symposium, 19.
• Valerdi, R., Ferris, T., Jain, R., & Kasser, J. (2009). 10.1. 1 An Exploration of Matching Teaching to the Learning Preferences of Systems Engineering Graduate Students. In INCOSE International Symposium, 19.
• Wang, G., Roedler, G. J., Valerdi, R., Ankrum, A., & Gaffney, J. E. (2009). 2.2. 2 Harmonizing Systems and Software Cost Estimation. In INCOSE International Symposium, 19.
• Wang, G., Turnidge, J., Shernoff, A., & Valerdi, R. (2009). 2.2. 1 Towards a Holistic, Total Engineering Cost Model. In INCOSE International Symposium, 19.
• Becerra-Fern{'a}ndez, I., Madey, G., Prietula, M., Rodr{'i}guez, D., Valerdi, R., & Wright, T. (2008). Design and development of a virtual emergency operations center for disaster management research, training, and discovery. In Hawaii International Conference on System Sciences, Proceedings of the 41st Annual.
• Blackburn, C., & Valerdi, R. (2008). 1.3. 1 Measuring Systems Engineering Success: Insights from Baseball. In INCOSE International Symposium, 18.
• Blackburn, C., & Valerdi, R. (2008). Measuring systems engineering success. In 18th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2008.
• Fortune, J., Valerdi, R., Wang, G., & others, . (2008). Systems Engineering Reuse: A Report on the State of the Practice. In 23rd International Forum on COCOMO and Systems/Software Cost Modeling.
• Valerdi, R., Boehm, B. W., & Reifer, D. J. (2008). The Constructive Systems Engineering Cost Model (COSYSMO): Quantifying the Costs of Systems Engineering Effort. In in Complex Systems, VDM Verlag.
• Valerdi, R., Yeo, T., Linden, H., Loureiro, G., & Fernandez, J. (2008). 7.5. 0 Global SE: The Reality and the Challenges. In INCOSE International Symposium, 18.
• Wang, G., Ankrum, A., Valerdi, R., Millar, C., & Roedler, G. J. (2008). 2.3. 2 COSYSMO Reuse Extension. In INCOSE International Symposium, 18.
• Wang, G., Boehm, B., Valerdi, R., & Shernoff, A. (2008). 2.3. 1 Proposed Modification to COSYSMO Estimating Relationship. In INCOSE International Symposium, 18.
• Axelband, E., Baehren, T., Dorenbos, D., Madni, A., Robitaille, P., Valerdi, R., Boehm, B., Jackson, S., Nadler, G., & Settles, S. (2007). A research agenda for systems of systems architecting. In INCOSE International Symposium, 17.
• Boehm, B., & Valerdi, R. (2007). The ROI of Systems Engineering: Some Quantitative Results. In Exploring Quantifiable IT Yields, 2007. EQUITY'07. IEEE International Conference on.
• Boehm, B., Valerdi, R., & Honour, E. (2007). 3.4. 2 The ROI of Systems Engineering: Some Quantitative Results. In INCOSE International Symposium, 17.
• Dixit, I., & Valerdi, R. (2007). 1.4. 3 Challenges in the Development of Systems Engineering as a Profession. In INCOSE International Symposium, 17.
• Fong, A., Valerdi, R., & Srinivasan, J. (2007). Boundary objects as a framework to understand the role of systems integrators. In Systems Research Forum, 2.
• Fong, A., Valerdi, R., & Srinivasan, J. (2007). Using a boundary object framework to analyze interorganizational collaboration. In INCOSE International Symposium, 17.
• Valerdi, R. (2007). Cognitive limits of software cost estimation. In First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007).
• Valerdi, R., & Gaffney, J. E. (2007). Reducing Risk and Uncertainty in COSYSMO Size and Cost Drivers: Some Techniques for Enhancing Accuracy. In 5th Conference on Systems Engineering Research, Hoboken, NJ.
• Valerdi, R., & Miller, C. (2007). From research to reality. In 17th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2007.
• Valerdi, R., & Miller, C. (2007). From research to reality: Making COSYSMO a trusted estimation tool in your organization. In INCOSE International Symposium, 17.
• Valerdi, R., Roedler, G. J., Rieff, J. E., Wheaton, M. J., & Wang, G. (2007). 9.4. 1 Lessons Learned From Industrial Validation of COSYSMO. In INCOSE International Symposium, 17.
• Valerdi, R., Wang, G., Roedler, G., Rieff, J., & Fortune, J. (2007). COSYSMO Reuse Extension. In 22nd International Forum on COCOMO and Systems/Software Cost Modeling.
• Valerdi, R., Wheaton, M. J., & Fortune, J. (2007). Systems engineering cost estimation for space systems. In AIAA SPACE 2007 Conference & Exposition.
• Srinivasan, J., Valerdi, R., & Lundqvist, K. (2006). Wanted: A Systems View on Certification. In National Workshop on Aviation Software System: Design for Certifiably Dependable Systems (NITRD HCSS-AS).
• Wang, G., Valerdi, R., Lane, J. A., & Boehm, B. (2006). 2.3. 2 Towards a Work Breakdown Structure for Net Centric System of Systems Engineering and Management. In INCOSE International Symposium, 16.
• Lane, J. A., & Valerdi, R. (2005). Synthesizing SoS concepts for use in cost estimation. In 2005 IEEE International Conference on Systems, Man and Cybernetics, 1.
• Valerdi, R., & Raj, J. (2005). 7.1. 2 Sea Level Requirements as Systems Engineering Size Metrics. In INCOSE International Symposium, 15.
• Valerdi, R., & Wheaton, M. (2005). ANSI/EIA 632 as a standardized WBS for COSYSMO. In AIAA 1st Infotech@ Aerospace Conference.
• Valerdi, R., Merrill, J., & Maloney, P. (2005). Cost metrics for unmanned aerial vehicles. In AIAA 16th Lighter-Than-Air Systems Technology Conference and Balloon Systems Conference.
• Wheaton, M., & Valerdi, R. (2005). EIA/ANSI 632 as a Standardized WBS for COSYSMO. In 2005 NASA Cost Analysis Symposium.
• Chen, Y., Boehm, B. W., Madachy, R., & Valerdi, R. (2004). An empirical study of eServices product UML sizing metrics. In Empirical Software Engineering, 2004. ISESE'04. Proceedings. 2004 International Symposium on.
• Valerdi, R., & Kohl, R. J. (2004). An approach to technology risk management. In Engineering Systems Division Symposium, 3.
• Valerdi, R., & Lane, J. A. (2004). STEPS TOWARD MODEL UNIFICATION FOR SOFTWARE, SYSTEMS ENGINEERING, AND SYSTEMS OF SYSTEMS. In 19th forum on COCOMO and software cost modeling. Los Angeles, CA.
• Valerdi, R., Chen, Y., & Yang, Y. (2004). System Level Metrics for Software Development Estimation. In International Symposium on Empirical Software Engineering, ISESE.
• Valerdi, R., Ernstoff, M., Mohlman, P. H., Reifer, D., & Stump, E. (2004). 2.6. 2 Systems Engineering Sizing in the Age of Acquisition Reform. In INCOSE International Symposium, 14.
• Valerdi, R., Miller, C., & Thomas, G. (2004). Systems engineering cost estimation by consensus. In 17th International Conference on Systems Engineering.
• Valerdi, R., Rieff, J., Roedler, G., & Wheaton, M. (2004). Lessons Learned From Collecting Systems Engineering Data. In 2nd Annual Conference on Systems Engineering Research, Los Angeles, CA.
• Boehm, B., Reifer, D. J., & Valerdi, R. (2003). COSYSMO: a systems engineering cost Model. In Proceedings of the 1st.
• Valerdi, R., Boehm, B. W., & Reifer, D. J. (2003). 3.1. 1 COSYSMO: A Constructive Systems Engineering Cost Model Coming of Age. In INCOSE International Symposium, 13.
• Valerdi, R., Ernstoff, M., Mohlman, P., Reifer, D., & Stump, E. (2003). Systems engineering sizing in the age of acquisition reform. In 18th Annual Forum on COCOMO and Software Cost Modeling, Los Angeles, CA.

Others

• Aggarwal, T., Valerdi, R., & Potoski, M. (2016). When More is Better: Design Principles for Prediction Markets in Defense Acquisition Cost Forecasting.
• Dabkowski, M., & Valerdi, R. (2016). The Budding SV3: Estimating the Cost of Architectural Growth Early in the Life Cycle.
• Deonandan, I. D. (2016). A Cost Model for Testing Unmanned and Autonomous Systems of Systems.
• Kotzian, M. J., Kobren, B., Wood, R. L., Fast, W. R., Tremaine, R. L., Seligman, D. J., Axiotis, G., Liu, K. K., Valerdi, R., Rhodes, D. H., & others, . (2016). Defense Acquisition Review Journal. Volume 17, Number 2, Issue 54. Achieving Excellence in a Changing Acquisition Environment.
• Liu, K. K., Valerdi, R., Rhodes, D. H., Kimm, L., & Headen, A. (2016). The F119 engine: A success story of human systems integration in acquisition.
• MARA{~n}{'O}N, R., GUALDA, E., & VALERDI, R. (2016). The Dynamics of Circular Migration in Southern Europe: An Example of Social Innovation.
• Madachy, R., & Valerdi, R. (2016). Knowledge-Based Systems Engineering Risk Assessment.
• Olwell, D., Roedler, G., Henshaw, M., & Valerdi, R. (2016). The Body of Knowledge and Curriculum to Advance Systems Engineering.
• Roetzheim, W., Jones, C., Dekkers, C. A., Putnam, L. H., Putnam, D. T., Beckett, D. M., Boehm, B., Valerdi, R., Lane, J. A., Brown, A., & others, . (2016). CrossTalk: The Journal of Defense Software Engineering. Volume 18, Number 4.
• Valerdi, R., & Potoski, M. (2016). Prediction Markets as an Information Aggregation Tool for Effective Project Management in Defense Acquisition Projects.
• Wang, P., Valerdi, R., Zhou, S., & Li, L. (2015). Introduction: Advances in IoT research and applications.
• Fitzgerald, B., Conboy, K., Power, K., Valerdi, R., Morgan, L., & Stol, K. (2013). Lean Enterprise Software and Systems: 4th International Conference, LESS 2013, Galway, Ireland, December 1-4, 2013, Proceedings.
• Muralidharan, S. (2012). Assessment of ocean thermal energy conversion.
• Zini, F. A. (2012). How do senior leaders conceive and re-architect their enterprises?.
• Aggarwal, T. (2011). Prediction markets for cost and risk assessment.
• Dorey, S. P. (2011). Enhancing cost realism through risk-driven contracting: Designing incentive fees based on probabilistic cost estimates.
• Evans, D. C. (2011). Predictors of successful outcomes of US Coast Guard construction contracts.
• Hwang, D. D. (2011). Performance measurement system design for supply chain organizations.
• Latner, A. (2011). Feature performance metrics in a service as a software offering.
• Mara{~n}{'o}n-Abreu, R. (2011). The dynamics of circular migration in Southern Europe.
• Morgan, D. B. (2011). Portfolio management in the Air Force: current status and opportunities.
• Rouse, W. B. (2011). The Economics of Human Systems Integration: Valuation of Investments in Peoples Training and Education, Safety and Health, and Work Productivity.
• Abdimomunova, L. (2010). Organizational assessment processes for enterprise transformation.
• Czaika, E. G. (2010). Starbucks cups: trash or treasure?: an example of facilitated systems thinking assisting stakeholders in designing their own system to recycle take-away cups.
• Liu, K. K. (2010). Cost Estimation of Human Systems Integration.
• Rizk, C. M. (2010). The economics of investing in green buildings.
• Blackburn, C. D., & others, . (2009). Metrics for enterprise transformation.
• Tibazarwa, A. (2009). Disciplined agility for process control & automation.
• Tiongson, A. J. (2009). Major system acquisition reform in the United States Coast Guard: a case for the application of Lean Enterprise principles.
• Aykroyd, T. N. (2008). Value assessment of new product innovations.
• Cascini, G. (2008). Computer-Aided Innovation (CAI): IFIP 20th World Computer Congress, Proceedings of the Second Topical Session on Computer-Aided Innovation, WG 5.4/TC 5 Computer-Aided Innovation, September 7-10, 2008, Milano, Italy.
• LaFon, C. C. (2008). Context characterization for synthesis of process architectures.
• Martinez, V. T. (2008). Global product development: a framework for organizational diagnosis.
• Casey, J. J. (2007). A lean enterprise approach to process improvement in a health care organization.
• Huang, K., & others, . (2007). Towards an information technology infrastructure cost model.
• Schiller, D. A. (2006). The Impact of the Geographic Distribution of Design Engineers on the Pace of Engineering Development.
• Valerdi, R. (2006). Academic COSYSMO User Manual-A Practical Guide for Industry and Government.
• Valerdi, R. (2006). academicCOSYSMO User Manual.
• Valerdi, R. (2005). The constructive systems engineering cost model (COSYSMO).