Identifying Dynamic Data Structures by Learning Evolving Patterns in Memory.

We investigate whether dynamic data structures in pointer programs can be identified by analysing program executions only. This paper describes a first step towards solving this problem by applying machine learning and pattern recognition techniques to analyse executions of C programs. By searching for repeating temporal patterns in memory caused by multiple invocations of data-structure operations, we are able to first locate and then identify these operations. Applying a prototypic tool implementing our approach to pointer programs that employ, e.g., lists, queues and stacks, we show that the identified operations can accurately determine the data structures used.