Decision Making under Uncertainty in Software Engineering: Release Readiness

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This research investigates the detection of software defects. The aim of the research is to address the question of "when to stop testing the software and release it?'. Under the constant pressure of "Deliver Now!' due time and budget constraints, software managers in real life do not observe only one factor, such as defect rates. Managers combine their prior knowledge with historical data about factors representing different lifecycle processes and their effects on the final reliability of software product. Furthermore, product reliability is strongly connected with software development life cycle (SDLC) activities. Each phase in the SDLC has to be modeled by considering the relations of product, process, and people related factors, as well as the relationships between these phases and their impacts on the final software product reliability. Previous studies in release planning well addressed how SDLC processes can be prioritized based on stakeholder preferences. However, there is also a need to model casual relations between SDLC processes to decide if the release is ready in terms of its reliability. This research aims to understand cause - effect relationships of SDLC activities leading decisions to stop testing activity. This research program is based on empirical analyses and aims to develop a model to quantify release readiness of software product. Other researchers in the software engineering domain can also use this model. My objective is to develop a Bayesian model that uses both quantitative and qualitative data based on data availability and quality. Such a hybrid model would give flexibility by combining local data extracted from organizational systems with expert judgments collected through questionnaires. I also plan to extend my existing software metrics collection tool, Prest, to include more metrics, and capabilities for analysis, defect and reliability prediction. The proposed research program is highly relevant to the Canadian software development industry. Software development companies in Canada to assist their managers to make decisions under uncertainty can use the tool.