Estimating the total number of software failures using an exponential model
ACM SIGSOFT Software Engineering Notes
Software Risk Management: Principles and Practices
IEEE Software
Software Reliability Modelling and Identification
A model for software rework reduction through a combination of anomaly metrics
Journal of Systems and Software
Electronic Commerce Research and Applications
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The current research attempts to update our knowledge of the way in which defects and the expense of correcting them (or alternatively, leaving them uncorrected) influences the final cost of software. Current industry models are based on data gathered decades ago, which has raised the question of their applicability in a world of modular, graphically intensive, object-oriented software development. The results of the research show that the evolutionary growth model of software errors appears to be valid for contemporary software development programs, and is not just an artefact of the particular techniques used several decades ago. In addition, it concludes that serious defects have less influence on cost than other defects (assuming they are resolved); that defects only generate significant costs if their resolution requires system redesign; that uncorrected defects become exponentially more costly with each phase in which they are unresolved; that the number of days that a project is open is a log-linear predictor of the number of software defects that will be discovered; and that testing must occur over a substantial portion of the useful life of the system in order to detect a substantial portion of the total defects in the software. As the software industry becomes more complex, this research will help us manage defect costs as they contribute to the overall programming costs of the software.