Applied software measurement: assuring productivity and quality
Applied software measurement: assuring productivity and quality
Why triangular membership functions?
Fuzzy Sets and Systems
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Optimizing the selection of VV&A activities: a risk/benefit approach
Proceedings of the 29th conference on Winter simulation
An empirical study of regression test application frequency
Proceedings of the 22nd international conference on Software engineering
Software Cost Estimation with Cocomo II with Cdrom
Software Cost Estimation with Cocomo II with Cdrom
Measures for Excellence: Reliable Software on Time, within Budget
Measures for Excellence: Reliable Software on Time, within Budget
Software development cost estimation approaches – A survey
Annals of Software Engineering
Quantitative Analysis of Faults and Failures in a Complex Software System
IEEE Transactions on Software Engineering
Estimating the Number of Residual Defects
HASE '98 The 3rd IEEE International Symposium on High-Assurance Systems Engineering
The Importance of Life Cycle Modeling to Defect Detection and Prevention
STEP '02 Proceedings of the 10th International Workshop on Software Technology and Engineering Practice
Sequential Testing in Product Development
Management Science
Measuring and optimizing systems' quality costs and project duration
Systems Engineering
A Comparison of Metric-Based and Empirical Approaches for Cognitive Analysis of Modeling Languages
Fundamenta Informaticae - Cognitive Informatics, Cognitive Computing, and Their Denotational Mathematical Foundations (I)
Analysing telecom companies using the Toyota NPD model
International Journal of Mobile Communications
Choquet integral based aggregation approach to software development risk assessment
Information Sciences: an International Journal
A systematic literature review of software quality cost research
Journal of Systems and Software
A Comparison of Metric-Based and Empirical Approaches for Cognitive Analysis of Modeling Languages
Fundamenta Informaticae - Cognitive Informatics, Cognitive Computing, and Their Denotational Mathematical Foundations (I)
A model to detect problems on scrum-based software development projects
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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The overall lifecycle cost associated with product failures exceeds 10% of yearly corporations' turnover. A major factor contributing to this loss is ineffective performance of software and systems Verification, Validation and Testing (VVT). Given these realities, we proposed a set of quantitative probabilistic models for estimating costs and risks stemming from carrying out any given VVT strategy [Engel, A., Barad, M., 2003. A methodology for modeling VVT risks and costs. Systems Engineering Journal 6 (3), 135-151, Wiley InterScience, Online ISSN: 1520-6858, Print ISSN: 1098-1241]. We also demonstrated that quality costs in software-intensive projects are likely to consume as much as 60% of the development budget. Finally, we showed that project cost and duration could be reduced by optimizing the VVT strategy, yielding about 10-15% reduction in development costs and project schedule [Engel, A., Shachar, S., 2006. Measuring and optimizing systems' quality costs and project duration. Systems Engineering Journal 9 (3), 259-280]. A key problem associated with such cost and time estimates is that input data are imprecise by nature. Certain parameters are better captured using tuple structures (e.g. Minimum, Most-likely and Maximum values). Other parameters can be better encapsulated using linguistic terms such as ''High'' or ''Low''. This paper extends the above research by modeling the problem using the fuzzy logic paradigm. We estimate the quality cost occurring during the development of software for an avionic suite in a fighter aircraft and demonstrate that applying fuzzy logic methodology yields results comparable to estimations based on models using the probabilistic paradigm (less than 4% differences in each of the five VVT cost categories).