Leveraging Field Data for Impact Analysis and Regression Testing


Software products are often released with missing functionality, errors, or incompatibilities that may result in failures, inferior performances, or, more generally, user dissatisfaction. In previous work, we presented the Gamma approach, which facilitates remote analysis and measurement of deployed software and allows for gathering program-execution data from the field. In this paper, we investigate the use of the Gamma approach to support and improve two fundamental tasks performed by software engineers during maintenance: impact analysis and regression testing. We present a new approach that leverages field data to perform these two tasks. We also present a set of empirical studies that we performed to assess the usefulness of the approach. The studies were performed on a real subject and on a real user population. The results of the studies show that the use of field data is effective and, for the cases considered, can considerably affect the results of dynamic analyses. Moreover, the empirical studies show that the approach is also efficient: the kind of field data that we consider requires very limited space and little instrumentation to be collected.

Related research categories:
(1) Program Analysis
(2) Empirical Studies
(3) Testing
(4) Regression Testing
(5) Monitoring
(6) Deployed Software

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