Software reliability analysis models
IBM Journal of Research and Development
Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
Software risk management
The Detection of Fault-Prone Programs
IEEE Transactions on Software Engineering
Modeling and managing risk early in software development
ICSE '93 Proceedings of the 15th international conference on Software Engineering
New Ways to Get Accurate Reliability Measures
IEEE Software
Operational Profiles in Software-Reliability Engineering
IEEE Software
Determining the Cost of a Stop-Test Decision
IEEE Software
Capability Maturity Model, Version 1.1
IEEE Software
Testing Process Guidance for Resource Constrained Software Testing
ISSRE '99 Proceedings of the 10th International Symposium on Software Reliability Engineering
"Good enough" software reliability estimation plug-in for Eclipse
eclipse '03 Proceedings of the 2003 OOPSLA workshop on eclipse technology eXchange
Toward a Software Testing and Reliability Early Warning Metric Suite
Proceedings of the 26th International Conference on Software Engineering
Early estimation of defect density using an in-process Haskell metrics model
A-MOST '05 Proceedings of the 1st international workshop on Advances in model-based testing
Early estimation of software quality using in-process testing metrics: a controlled case study
3-WoSQ Proceedings of the third workshop on Software quality
Iterative identification of fault-prone binaries using in-process metrics
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
Enabling the adoption of aspects - testing aspects: a risk model, fault model and patterns
Proceedings of the 8th ACM international conference on Aspect-oriented software development
Toward Non-security Failures as a Predictor of Security Faults and Failures
ESSoS '09 Proceedings of the 1st International Symposium on Engineering Secure Software and Systems
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During early software testing phases, testing profiles are often very different from operational profiles. Consequently, assessment of operational software quality during these non-operational testing stages is difficult, and is open to interpretation. The paper discusses some issues related to this. Software is assumed to be a large system composed of components that evolve in parallel. The focus is on early identification of software components that in operation may be excessively error-prone. The approach involves definition of states based on static and dynamic propositions about the verification and testing history of the software, and the use of that information in models that span multiple testing phases. An example based on a risk model is presented.