Mining Change Histories for Unknown Systematic Edits

Software developers often need to repeat similar modifications in multiple different locations of a system's source code. These repeated similar modifications, or systematic edits, can be both tedious and error-prone to perform manually. While there are tools that can be used to assist in automating systematic edits, it is not straightforward to find out where the occurrences of a systematic edit are located in an existing system. This knowledge is valuable to help decide whether refactoring is needed, or whether future occurrences of an existing systematic edit should be automated. In this paper, we tackle the problem of finding unknown systematic edits using a closed frequent itemset mining algorithm, operating on sets of distilled source code changes. This approach has been implemented for Java programs in a tool called SysEdMiner. To evaluate the tool's precision and scalability, we have applied it to an industrial use case.