Understanding Software Changes: Extracting, Classifying, and Presenting Fine-Grained Source Code Changes

In modern software engineering, developers have to work with constantly evolving, interconnected software systems. Understanding how and why these systems and their dependencies between each other change is therefore an essential step in improving or maintaining them. For this, it is important to know what changed and how these changes influence the system. Most currently used tools that help developers to understand source code changes either use the textual representation of source code, allowing for a coarse-grained overview, or use the AST (abstract syntax tree) representation of source code to extract more fine-grained changes. We plan to improve the accuracy and classification of the extracted source code changes and to extend them by analysing the fine-grained changes of source code dependencies. We also propose a dynamical analysis of the impact of the previously extracted changes on performance metrics. This helps to understand what changes caused a certain change in program behaviour. We plan to use and combine this information to generate accurate and detailed change overviews that bridge the gap between existing coarse-grained solutions and the raw changes contained in the code, aiming to reduce the developers' time spent reading changed code and help them to quickly understand the changes between two versions of source code.