Virtual Software Engineering Laboratories in Support of Trade-off Analyses
Software Quality Control
A framework for the simulation of structural software evolution
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Measuring and predicting software productivity: A systematic map and review
Information and Software Technology
Simulation of experiments for data collection: a replicated study
EASE'06 Proceedings of the 10th international conference on Evaluation and Assessment in Software Engineering
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Empirical knowledge from software engineering studiesis an important source for the creation of accurate simulationmodels. This article describes the development of asimulation model using empirical knowledge gained froman experiment at the NASA/GSFC Software EngineeringLaboratory and from two replications at the University ofKaiserslautern. Data and analysis results are used to identifyinfluence dependencies between parameters, and to calibratemodels. The goal of the model is the determinationof the effects (i. e., defect detection efficiency) of a requirementsinspection process under varying contexts. Thepurpose is to provide decision support for project managersand process engineers when planning or changinga development process. This article describes the systematicmodel development with a focus on the use of empiricalknowledge. Additionally, limitations of the model,lessons learned, and research questions for future work aresketched. The model performed well in an initial validationrun, with only little deviation from experimental values.