Abstracting Runtime Heaps for Program Understanding

  • Authors:
  • Mark Marron;Cesar Sanchez;Zhendong Su;Manuel Fahndrich

  • Affiliations:
  • Imdea Software Institute, Boadilla del Monte;Imdea Software Institute, Boadilla del Monte;University of California, Davis, Davis;Microsoft Research

  • Venue:
  • IEEE Transactions on Software Engineering
  • Year:
  • 2013

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Abstract

Modern programming environments provide extensive support for inspecting, analyzing, and testing programs based on the algorithmic structure of a program. Unfortunately, support for inspecting and understanding runtime data structures during execution is typically much more limited. This paper provides a general purpose technique for abstracting and summarizing entire runtime heaps. We describe the abstract heap model and the associated algorithms for transforming a concrete heap dump into the corresponding abstract model as well as algorithms for merging, comparing, and computing changes between abstract models. The abstract model is designed to emphasize high-level concepts about heap-based data structures, such as shape and size, as well as relationships between heap structures, such as sharing and connectivity. We demonstrate the utility and computational tractability of the abstract heap model by building a memory profiler. We use this tool to identify, pinpoint, and correct sources of memory bloat for programs from DaCapo.