Test cases use assertions to check program behaviour. While these assertions may not be complex, they are themselves code that must be written correctly in order to determine whether a test case should pass or fail. We claim that most test assertions are relatively repetitive and straight-forward, making their construction well suited to automation and that this automation can reduce developer effort while improving assertion quality. Examining 33,873 assertions from 105 projects revealed that developer-written assertions fall into twelve high-level categories, confirming that the vast majority ($>$90%) of test assertions are fairly simple in practice. We created AutoAssert, a human-in-the-loop tool to fit naturally into a developer's test-writing workflow by automatically generating assertions for JavaScript and TypeScript test cases. A developer invokes AutoAssert by identifying the variable they want validated; AutoAssert uses dynamic analysis to generate assertions relevant for this variable and its runtime values, injecting the assertions into the test case for the developer to accept, modify, delete. Comparing AutoAssert's assertions to those written by developers, we found that the assertions generated by AutoAssert are the same kind of assertion as was written by developers 84% of the time in a sample of over 1,000 assertions. Additionally we validated the utility of AutoAssert-generated assertions with 17 developers who found the majority of generated assertions to be useful and expressed considerable interest in using such a tool for their own projects.

Source code histories are commonly used by developers and researchers to reason about how software evolves. Through a survey with 42 professional software developers, we learned that developers face significant mismatches between the output provided by developers' existing tools for examining source code histories and what they need to successfully complete their historical analysis tasks. To address these shortcomings, we propose CodeShovel, a tool for uncovering method histories that quickly produces complete and accurate change histories for 90% methods (including 97% of all method changes) outperforming leading tools from both research (e.g, FinerGit) and practice (e.g., IntelliJ / git log). CodeShovel helps developers to navigate the entire history of source code methods so they can better understand how the method evolved. A field study on industrial code bases with 16 industrial developers confirmed our empirical findings of CodeShovel's correctness, low runtime overheads, and additionally showed that the approach can be useful for a wide range of industrial development tasks.

Autograders are an invaluable tool for deploying assessments in large classes. However students sometimes rely on the autograder in place of careful thought for ways to improve to their solution. We sought to naturally encourage students to check their own solutions more, and hammer the grader less. To do this, we imposed a penalty each time a student's grade went down: we called these regression penalties. We assessed whether the introduction of these penalties resulted in less reliance on the autograder without hurting student performance.