Dynamic Analysis of Software Systems using Execution Pattern Mining

Abstract

Software system analysis for extracting system functionality remains as a major problem in the reverse engineering literature and the early approaches mainly rely on static properties of software. In this paper, we propose a novel technique for dynamic analysis of software systems to identify the implementation of the software features that are specified through a number of feature-specific task scenarios. The execution of task scenarios and application of data mining algorithm sequential pattern discovery on the generated traces allow us to extract common functionality associated with the corresponding feature-specific task scenarios. The extracted patterns are used to identify the groups of core functions that implement software features. The proposed approach can be used for program comprehension and feature to source code assignment. A case study on the Unix Xfig drawing tool has been provided