Customized Regression Testing Using Telemetry Usage Patterns

Pervasive telemetry in modern applications is providing new possibilities in the application of regression testing techniques. Similar to how research in bioinformatics is leading to personalized medicine, tailored to individuals, usage telemetry in modern software allows for custom regression testing, tailored to the usage patterns of an installation. By customizing regression testing based on software usage, the effectiveness of regression testing techniques can be greatly improved, leading to reduced testing costs and enhanced detection of defects that are most important to that customer. In this research, we introduce the concept of fingerprinting software usage patterns through telemetry. We provide various algorithms tocompute fingerprints and conduct an empirical study that shows that fingerprints are effective in identifying distinct usage patterns. Further, we discuss how usage fingerprints can be used to improve regression test prioritization run time by over 30 percent compared to traditional prioritization techniques.