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Software Reliability Engineering: More Reliable Software Faster and CheaperSeptember 2004
Publisher:
  • Authorhouse
ISBN:978-1-4184-9388-2
Published:01 September 2004
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Bibliometrics
Abstract

No abstract available.

Cited By

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    Vescan A, Camelia S and Budur A Towards a Reliability Prediction Model based on Internal Structure and Post-Release Defects Using Neural Networks Proceedings of the 25th International Conference on Evaluation and Assessment in Software Engineering, (379-386)
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    Duncan R Designing Packetc Programming Language for Reliable Network Apps Proceedings of the 2018 VII International Conference on Network, Communication and Computing, (107-114)
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    Pita Costa J and Galinac Grbac T The Topological Data Analysis of Time Series Failure Data in Software Evolution Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion, (25-30)
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    Grbac T and Mauša G On the distribution of software faults in evolution of complex systems Proceedings of the International Colloquium on Software-intensive Systems-of-Systems at 10th European Conference on Software Architecture, (1-7)
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    Kumar P and Singh Y (2012). Assessment of software testing time using soft computing techniques, ACM SIGSOFT Software Engineering Notes, 37:1, (1-6), Online publication date: 27-Jan-2012.
  6. Radliński Ł Empirical analysis of the impact of requirements engineering on software quality Proceedings of the 18th international conference on Requirements Engineering: foundation for software quality, (232-238)
  7. Ray M, Kumawat K and Mohapatra D (2018). Source code prioritization using forward slicing for exposing critical elements in a program, Journal of Computer Science and Technology, 26:2, (314-327), Online publication date: 1-Mar-2011.
  8. Radliński Ł A framework for integrated software quality prediction using Bayesian nets Proceedings of the 2011 international conference on Computational science and Its applications - Volume Part V, (310-325)
  9. ACM
    Singh Y and Kumar P (2010). Application of feed-forward neural networks for software reliability prediction, ACM SIGSOFT Software Engineering Notes, 35:5, (1-6), Online publication date: 22-Oct-2010.
  10. ACM
    Mohanta S, Vinod G, Ghosh A and Mall R (2010). An approach for early prediction of software reliability, ACM SIGSOFT Software Engineering Notes, 35:6, (1-9), Online publication date: 27-Nov-2010.
  11. ACM
    Northrop L, Klein M, Goodenough J and Smith D Needed foundations for assuring the desirable behavior of software-reliant systems Proceedings of the FSE/SDP workshop on Future of software engineering research, (259-262)
  12. Lo J The implementation of artificial neural networks applying to software reliability modeling Proceedings of the 21st annual international conference on Chinese control and decision conference, (4385-4390)
  13. ACM
    Petersen K, Rönkkö K and Wohlin C The impact of time controlled reading on software inspection effectiveness and efficiency Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement, (139-148)
  14. Eusgeld I References Dependability metrics, (267-300)
  15. Wagner S Global Sensitivity Analysis of Predictor Models in Software Engineering Proceedings of the Third International Workshop on Predictor Models in Software Engineering
  16. Wagner S and Deissenboeck F An Integrated Approach to Quality Modelling Proceedings of the 5th International Workshop on Software Quality
  17. Lyu M Software Reliability Engineering 2007 Future of Software Engineering, (153-170)
  18. Pretschner A Model-based testing in practice Proceedings of the 2005 international conference on Formal Methods, (537-541)
  19. Huang C (2005). Cost-reliability-optimal release policy for software reliability models incorporating improvements in testing efficiency, Journal of Systems and Software, 77:2, (139-155), Online publication date: 1-Aug-2005.
  20. ACM
    Pretschner A Model-based testing Proceedings of the 27th international conference on Software engineering, (722-723)
  21. ACM
    Pretschner A, Prenninger W, Wagner S, Kühnel C, Baumgartner M, Sostawa B, Zölch R and Stauner T One evaluation of model-based testing and its automation Proceedings of the 27th international conference on Software engineering, (392-401)
  22. Thelin T, Runeson P, Wohlin C, Olsson T and Andersson C (2019). Evaluation of Usage-Based Reading—Conclusions after Three Experiments, Empirical Software Engineering, 9:1-2, (77-110), Online publication date: 1-Mar-2004.
  23. ACM
    Bowring J, Rehg J and Harrold M Active learning for automatic classification of software behavior Proceedings of the 2004 ACM SIGSOFT international symposium on Software testing and analysis, (195-205)
  24. ACM
    Bowring J, Rehg J and Harrold M (2004). Active learning for automatic classification of software behavior, ACM SIGSOFT Software Engineering Notes, 29:4, (195-205), Online publication date: 1-Jul-2004.
  25. Huang C, Lyu M and Kuo S (2003). A Unified Scheme of Some Nonhomogenous Poisson Process Models for Software Reliability Estimation, IEEE Transactions on Software Engineering, 29:3, (261-269), Online publication date: 1-Mar-2003.
  26. Thelin T, Runeson P and Wohlin C (2003). An Experimental Comparison of Usage-Based and Checklist-Based Reading, IEEE Transactions on Software Engineering, 29:8, (687-704), Online publication date: 1-Aug-2003.
Contributors
  • Nokia Bell Labs

Recommendations

Reviews

Robert L. Glass

I have heard about Musa's work on software reliability engineering for most of my professional career. To be honest, I have been a bit turned off by it, because, first, it seemed somehow unrealistic in a software world where quantitative approaches feel more unrealistic than qualitative ones, and, second, the math involved in most initial presentations of the material seemed daunting, even to this once-upon-a-time math major. So, I leapt at the chance to review this second edition of Musa's book (first published in 1999 [1]), albeit with considerable misgivings. The arrival of the book did little to diminish those misgivings. But, upon cracking open the book's cover, I found myself pleasantly surprised. The book is eminently readable. It minimizes its math content. It is chock full of exercises, workshops, "special situation" discussions, background supplements, and many frequently asked questions and their articulate responses. What is software reliability engineering (SRE), and what is it good for__?__ The author opens the book by saying (as his subtitle says) that the approach is about a "better way to develop software," a way that is "quantitatively based." The essence of SRE is its focus on "operational profiles, random process, software reliability models, statistical estimation, and sequential sampling theory." Its usage involves six primary activities: defining the project, implementing operational profiles, engineering the "just right" reliability, preparing for test, executing test, and guiding test (there is a major chapter devoted to each of those activities). The audience for the book is "software testers, systems engineers, system architects, acquirers of software, quality assurance engineers, reliability engineers, development managers, and students." That brings us to the subject of what SRE is good for. Quite a bit of the book is devoted to that topic (the book is part user manual, part sales brochure, and part tutorial, but those three parts are integrated in such a way that you hardly notice them). Musa provides lots of cheerleading data: he notes that "SRE is low in cost, and its implementation has virtually no schedule impact," and he cites benefits at AT&T, where it has been a "Best Current Practice" since 1991. The author names 24 leading companies that have used SRE, including Microsoft and IBM, and notes that it is a standard at both the Institute of Electrical and Electronics Engineers (IEEE) and the American Institute of Aeronautics and Astronautics (AIAA). SRE has been around, the author says, since its early beginning in 1973. It is intended to focus on user-oriented, rather than developer-oriented, notions of reliability (the author says it is more about operation than about software design). The book has its quirks. It includes "rapid delivery" and "low cost" as quality attributes. It says that the method is appropriate for maintenance, but its heart seems to be largely in development. It spends little time on ways to choose test cases, in spite of the fact that its "preparing for test" chapter is quite long (there is much more on choosing an appropriate number of test cases, reinforcing my early feeling that the book was quantitative when qualitative might be more appropriate). In spite of its heavy use of the term "just right" with respect to reliability, a definition or explanation of that term was not apparent in the chapter with that term in the title, and the term was present in neither the glossary nor the index. Given the claims for the approach, and its apparent broad standardization and usage, getting to know this book could be quite important to software project people. I recommend it, as both an exposure to the notions of SRE, for the purpose of making a decision about its use, and as a user manual and tutorial if you decide to proceed with its implementation. Online Computing Reviews Service

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