Improving software development process and project management with software project telemetry
Philip M. Johnson, Qin Zhang · 2006
Software development is slow, expensive and error prone, often resulting in products with a large number of defects which cause serious problems in usability, reliability, and performance. To combat this problem, measurement provides a systematic and empirically-guided approach to control and improve development processes and final products. However, due to the high cost associated with and difficulties in decision-making, measurement is not widely adopted by organizations. This dissertation proposes a novel metrics-based program called software project to address the problems. It uses sensors to collect metrics automatically and unobtrusively. It employs a domain-specific language to represent telemetry trends in product and process metrics. Project management and process improvement decisions are made by detecting changes in telemetry trends and comparing trends between different periods of the same project. Software project telemetry avoids many problems inherent in traditional metrics models, such as the need to accumulate a historical project database and ensure that the historical data remain comparable to current and future projects. The claim of this dissertation is that project telemetry provides an effective approach to (1) automated metrics collection and analysis, and (2) in-process, empirically-guided development process problem detection and diagnosis. Two empirical studies were carried out to evaluate the claim: one in engineering classes, and the other in the Collaborative Software Development Lab. The results suggested that project telemetry had acceptably-low metrics collection and analysis overhead, and that it provided decision-making value at least in the exploratory context of the two studies.