Incremental Slicing Based on Data-Dependences Types

  • Authors:

  • Alessandro Orso;Saurabh Sinha;Mary Jean Harrold

  • Affiliations:

  • Georgia Institute of Technology;Georgia Institute of Technology;Georgia Institute of Technology

  • Venue:
  • ICSM '01 Proceedings of the IEEE International Conference on Software Maintenance (ICSM'01)
  • Year:
  • 2001

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Abstract

Program slicing is useful for assisting with many software-maintenance tasks. The presence and frequent usage of pointers in languages such as C causes complex data dependences. To function effectively on such programs, slicing techniques must account for pointer-induced data dependences. Existing slicing techniques do not distinguish data dependences based on their types. This paper presents a new slicing technique, in which slices are computed based on types of data dependences. This new slicing technique offers several benefits and can be exploited in different ways, such as identifying subtle data dependences for debugging, computing reduced-size slices quickly for complex programs, and performing incremental slicing. This paper describes an algorithm for incremental slicing that increases the scope of a slice in steps, by incorporating different types of data dependences at each step. The paper also presents empirical results to illustrate the performance of the technique in practice. The results illustrate that incremental slices can be significantly smaller than complete slices. Finally, the paper presents a case study that explores the usefulness of incremental slicing for debugging.