Search-Based Prediction of Software Quality Evaluations and Comparisons

Abstract: Software verification and validation activities are essential for software quality but also constitute a large part of software development costs. Therefore efficient and cost-effective software verification and validation (V & V) activities are both a priority and a necessity considering the pressure to decrease time-to-market and intense competition faced by many, if not all, companies today. It is then perhaps not unexpected that decisions related to software quality, when to stop testing, testing schedule and testing resource allocation needs to be as accurate as possible. The objective of this thesis is to investigate research issues to help management decision-making process to control variation during software V & V activities, thereby supporting software quality. To achieve this, we investigate: the possibility of analyzing software fault history as a measurement technique to predict future software reliability, using measures to support test phase efficiency, assignment of resources to fix faults and classification of fault-prone modules of the software from non fault-prone ones. A common element in our investigations is the use of metaheuristic search-based techniques for supporting the decision-making process within software V&V activities. Apart from presenting the current state-of-the-art in the form a systematic literature review and doing comparative evaluations of a variety of techniques on large scale projects, the thesis also investigate more methodological investigations using search-based techniques that are relevant to the task of software quality measurement. Based on the research findings in this thesis, we conclude that search-based techniques (like genetic programming) are viable techniques for supporting the management decision-making process to control variation in software V & V activities. The accuracy of these techniques makes them an essential candidate for any future decision-support toolbox for effective software project management

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