Code execution reports: visually augmented summaries of executed source code fragments

Abstract

Understanding a fragment of code is important for developers as it enables them to optimize, debug and extend it. Developers adopt different procedures for understanding a piece of code, which involves going through the source code, documentation, and profilers results. Various code comprehension techniques have suggested code summarization approaches, which generates the intended behavior of code in natural language text. In this thesis, we present an approach to summarize the actual behavior of a method during its execution. For this purpose, we create a framework that facilitates the generation of interactive and web-based natural language reports with small embedded word-size visualizations. Then, we develop a tool that profiles a method for runtime behavior, and then it processes the information. The tool uses our framework to generate a visually augmented natural language summary report that explains the behavior of the code. In the end, we conduct a small user study to evaluate the quality of our code execution reports.