Effects of pointers on data dependences
Alessandro Orso, Saurabh Kumar Sinha, Mary Jean Harrold · 2002
This paper presents a technique for computing and classifying data dependences that takes into account the complexities introduced by specific language constructs, such as pointers, arrays and structures. The classification is finer-grained than previously proposed classifications. Moreover unlike previous work, the paper presents empirical results that illustrate the distribution of data dependences for a set of C subjects. The paper also presents a potential application for the proposed classification, program slicing, and a technique that completes slices based on data-dependence types. This technique facilitates the use of slicing for program understanding because a user can either augment a slice incrementally, by incorporating data dependences based on their relevance, or focus on specific kinds of dependences. Finally, the paper presents a case study that shows how the incremental addition of data dependences allows for growing the size of the slices in steps.