Source code modifications are often documented with log messages. Such messages are a key component of software maintenance: they can help developers validate changes, locate and triage defects, and understand modifications. However, this documentation can be burdensome to create and can be incomplete or inaccurate. We present an automatic technique for synthesizing succinct human-readable documentation for arbitrary program differences. Our algorithm is based on a combination of symbolic execution and a novel approach to code summarization. The documentation it produces describes the effect of a change on the runtime behavior of a program, including the conditions under which program behavior changes and what the new behavior is. We compare our documentation to 250 human-written log messages from 5 popular open source projects. Employing a human study, we find that our generated documentation is suitable for supplementing or replacing 89 % of existing log messages that directly describe a code change.

Web-based applications are growing in complexity and criticality, increasing the need for their precise validation. Regression testing is an established approach for providing information about the quality of an application in the face of recurring updates that dominate the web. We present techniques to address a key challenge of the automated regression testing of web-based applications. Innocuous program evolutions often appear to fail tests and must be manually inspected. We rely on inherent similarities between independent web-based applications to provide fully automated solutions for reducing the number of false positives associated with regression testing such applications, simultaneously focusing on returning all true positives. Our approach predicts which test cases merit human inspection by applying a model derived from regression testing other programs. We are 2.5 to 50 times as accurate as current industrial practice, but require no user annotations. I.