Managing the development of large software systems: concepts and techniques
ICSE '87 Proceedings of the 9th international conference on Software Engineering
Software systems engineering
IEEE Transactions on Software Engineering
Tutorial, Human Factors in Software Development
Tutorial, Human Factors in Software Development
Operational Profiles in Software-Reliability Engineering
IEEE Software
Software Reliability Models: Assumptions, Limitations, and Applicability
IEEE Transactions on Software Engineering
An Architectural Model For Software Reliability Quantification
ISSRE '97 Proceedings of the Eighth International Symposium on Software Reliability Engineering
A Practical Method For The Estimation Of Software Reliability Growth In The Early Stage Of Testing
ISSRE '97 Proceedings of the Eighth International Symposium on Software Reliability Engineering
A New Challenge for Applying Time Series Metrics Data to Software Quality Estimation
Software Quality Control
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Software reliability prediction models are of paramount importance since they provide early identification of cost overruns, software development process issues, optimal development strategies, etc. Existing prediction models were developed mostly during the past 5 to 10 years and, hence, have become obsolete. Furthermore, they are not based on a deep knowledge and understanding of the software development process. This limits their predictive power. This paper presents an approach to the prediction of software reliability based on a systematic identification of software process failure modes and their likelihoods. A direct consequence of the approach and its supporting data collection efforts is the identification of weak areas in the software development process. A Bayesian framework for the quantification of software process failure mode probabilities is recommended since it allows usage of historical data that are only partially relevant to the software at hand. The approach is applied to the requirements analysis phase.