Technical debt management in release planning : a decision support framework

Abstract

Technical debt is a financial metaphor used to describe the tradeoff between the short term benefit of taking a shortcut during the design or implementation phase of a software product (e.g., in order to meet a deadline) and the long term consequences of taking said shortcut, which may affect the quality of the software product. Recently, academics and industry practitioners have offered several models and methods which purport to explain or manage this phenomenon. Unfortunately, to date, there has yet to be a framework which supports managers in making decisions regarding technical debt. Although similar solutions exist to support the release planning phase of software development, they focus on the management of new features and do not take into account issues relating to technical debt and its effects on the development process. This thesis describes a software engineering decision support system focusing on three key components: analysis and decision, intelligence, and simulation. Supporting each of these components is a meta-model which bridges the gap between technical debt management and software release planning. To investigate the development of the analysis and decision and intelligence components we used a reduced form of this meta-model in conjunction with a coalition formation games approach. This approach served to evaluate the technical debt management and release planning issues, and was found superior, using simulation, in comparison to a first-come, first-served method (representative of typical agile planning processes). To investigate the development of the simulation component we conducted a simulation study to evaluate different strategies for technical debt management as proposed in the literature. The results of this study provide compelling evidence for current technical debt management strategies proposed in the literature that can be immediately applied by practitioners. Finally, we describe the initial work on an extended simulation framework which will form the basis of a complete simulation component for a technical debt management and release planning decision support framework.