2010 | OriginalPaper | Buchkapitel
A Method to Measure Productivity Trends during Software Evolution
verfasst von : Hans Christian Benestad, Bente Anda, Erik Arisholm
Erschienen in: Evaluation of Novel Approaches to Software Engineering
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Better measures of productivity are needed to support software process improvements. We propose and evaluate indicators of productivity trends that are based on the premise that productivity is closely related to the effort required to complete change tasks. Three indicators use change management data, while a fourth compares effort estimates of benchmarking tasks. We evaluated the indicators using data from 18 months of evolution in two commercial software projects. The productivity trend in the two projects had opposite directions according to the indicators. The evaluation showed that productivity trends can be quantified with little measurement overhead. We expect the methodology to be a step towards making quantitative self-assessment practices feasible even in low ceremony projects.