AT&T Technical Journal
The effect of system workload on error latency: an experimental study
SIGMETRICS '85 Proceedings of the 1985 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Quantifying Software Validation: When to Stop Testing?
IEEE Software
An analysis of software project failure
ICSE '79 Proceedings of the 4th international conference on Software engineering
Estimating the Probability of Failure When Testing Reveals No Failures
IEEE Transactions on Software Engineering
Improving Quality With a Manufacturing Process
IEEE Software
Qualitative and Quantitative Reliability Assessment
IEEE Software
Quantitative Analysis of Faults and Failures in a Complex Software System
IEEE Transactions on Software Engineering
Reliability of a commercial telecommunications system
ISSRE '96 Proceedings of the The Seventh International Symposium on Software Reliability Engineering
Evaluation of Software Dependability Based on Stability Test Data
FTCS '95 Proceedings of the Twenty-Fifth International Symposium on Fault-Tolerant Computing
Analysis of Software Fault Removal Policies Using a Non-Homogeneous Continuous Time Markov Chain
Software Quality Control
Software defect repair times: a multiplicative model
Proceedings of the 4th international workshop on Predictor models in software engineering
A multiplicative model of software defect repair times
Empirical Software Engineering
Approximating deployment metrics to predict field defects and plan corrective maintenance activities
ISSRE'09 Proceedings of the 20th IEEE international conference on software reliability engineering
A quantitative analysis into the economics of correcting software bugs
CISIS'11 Proceedings of the 4th international conference on Computational intelligence in security for information systems
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The author analyzes and models the software development process, and presents field experience for large distributed systems. Defect removal is shown to be the bottleneck in achieving the appropriate quality level before system deployment in the field. The time to defect detection, the defect repair time and a factor reflecting the introduction of new defects due to imperfect defect repair are some of the constants in the laws governing defect removal. Test coverage is a measure of defect removal effectiveness. A birth-death mathematical model based on these constants is developed and used to model field failure report data. The birth-death model is contrasted with a more classical decreasing exponential model. Both models indicate that defect removal is not a cost-effective way to achieve quality. As a result of the long latency of software defects in a system, defect prevention is suggested to be a far more practical solution to quality than defect removal.