| For many years, programmers have faced the problem of reading and trying to understand other programmers' code, either to maintain it or to learn from it. Analysis of dynamic data structure usage is useful for both program understanding and for improving the accuracy of other program analyses.;We have designed and implemented a dynamic heap analysis system that allows one to examine and analyze how Java programs build and modify data structures. Using a complete execution trace from a profiled run of the program, we build an internal representation that mirrors the evolving runtime data structures. The resulting series of representations can then be analyzed and visualized. This gives us an accurate representation of the data structures created and an insight into the program's behaviour. Furthermore we show how to use our approach to help understand how programs use data structures, the precise effect of garbage collection, and to establish limits on static data structure analysis.;A deep understanding of dynamic data structures is particularly important for modern, object-oriented languages that make extensive use of heap-based data structures. These analysis results can be useful for an important group of applications such as parallelization, garbage collection optimization, program understanding or improvements to other optimization.;Data structure usage has been the target of various static techniques. Static approaches, however, may suffer from reduced accuracy in complex situations and have the potential to be overly-conservative in their approximation. An accurate, clean picture of runtime heap activity is difficult to achieve. |
