|Authors||B. Cornelissen, L. Moonen and A. Zaidman|
|Editors||H. Mei and K. Wong|
|Title||An Assessment Methodology for Trace Reduction Techniques|
|Afilliation||Software Engineering, Software Engineering|
|Publication Type||Proceedings, refereed|
|Year of Publication||2008|
|Conference Name||Proceedings of the 24th IEEE International Conference on Software Maintenance (ICSM 2008)|
Program comprehension is an important concern in software maintenance because these tasks generally require a degree of knowledge of the system at hand. While the use of dynamic analysis in this process has become increasingly popular, the literature indicates that dealing with the huge amounts of dynamic information remains a formidable challenge. Although various trace reduction techniques have been proposed to address these scalability concerns, their applicability in different contexts often remains unclear because extensive comparisons are lacking. This makes it difficult for end-users to determine which reduction types are best suited for a certain analysis task. In this paper, we propose an assessment methodology for the evaluation and comparison of trace reduction techniques. We illustrate the methodology using a selection of four types of reduction methods found in literature, which we evaluate and compare using a test set of seven large execution traces. Our approach enables a systematic assessment of trace reduction techniques, which eases the selection of suitable reductions in different settings, and allows for a more effective use of dynamic analysis tools in software maintenance.