Software metrics (2nd ed.): a rigorous and practical approach
Software metrics (2nd ed.): a rigorous and practical approach
A Discipline for Software Engineering
A Discipline for Software Engineering
Art of Software Testing
Metrics and Models in Software Quality Engineering
Metrics and Models in Software Quality Engineering
Economics of software verification
PASTE '01 Proceedings of the 2001 ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering
Effective test metrics for test strategy evolution
CASCON '04 Proceedings of the 2004 conference of the Centre for Advanced Studies on Collaborative research
Software quality economics for defect-detection techniques using failure prediction
3-WoSQ Proceedings of the third workshop on Software quality
On the statistical properties of testing effectiveness measures
Journal of Systems and Software - Special issue: Quality software
Using portfolio theory for better and more consistent quality
Proceedings of the 2007 international symposium on Software testing and analysis
Software debugging, testing, and verification
IBM Systems Journal
Mining software defect data to support software testing management
Applied Intelligence
Insights into component testing process
Proceedings of the 2nd International Workshop on Emerging Trends in Software Metrics
Artificial neural networks application in software testing selection method
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I
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In-process tracking and measurements play a critical role in software development, particularly for software testing. Although there are many discussions and publications on this subject and numerous proposed metrics, few in-process metrics are presented with sufficient experiences of industry implementation to demonstrate their usefulness. This paper describes several in-process metrics whose usefulness has been proven with ample implementation experiences at the IBM Rochester AS/400® software development laboratory. For each metric, we discuss its purpose, data, interpretation, and use and present a graphic example with real-life data. We contend that most of these metrics, with appropriate tailoring as needed, are applicable to most software projects and should be an integral part of software testing.