In a software development cycle, programs go through many iterations. Identifying and understanding program changes is a tedious but necessary task for programmers, especially when software is developed in a collaborative environment. Existing tools used by the programmers either lack in finding the structural differences, or report the differences as atomic changes, such as updates of individual syntax tree nodes. Programmers frequently use program restructuring techniques, such as refactorings that are composed of several individual atomic changes. Current version differencing tools omit these high-level changes, reporting just the set of individual atomic changes. When a large number of refactorings are performed, the number of reported atomic changes is very large. As a result, it will be very difficult to understand the program differences. This problem can be addressed by reporting the program differences as composite changes, thereby saving programmers the effort of navigating through the individual atomic changes. This thesis proposes a methodology to explore the atomic changes reported by existing version differencing tools to infer composite changes. First, we will illustrate the different approaches that can be used for representing object language program differences using a variation representation. Next we will present the process of composite change inference from the structured representation of atomic changes. This process describes patterns that specify the expected structure of an expression corresponding to each composite change that has to be inferred. The information in patterns is then used to design the change inference algorithm. The composite changes inferred from a given expression are annotated in the expression, allowing the changes to be reported as desired. / Graduation date: 2012