Symbolic heap abstraction with demand-driven axiomatization of memory invariants

  • Authors:

  • Isil Dillig;Thomas Dillig;Alex Aiken

  • Affiliations:

  • Stanford University, Stanford, CA, USA;Stanford University, Stanford, CA, USA;Stanford University, Stanford, CA, USA

  • Venue:
  • Proceedings of the ACM international conference on Object oriented programming systems languages and applications
  • Year:
  • 2010

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Abstract

Many relational static analysis techniques for precise reasoning about heap contents perform an explicit case analysis of all possible heaps that can arise. We argue that such precise relational reasoning can be obtained in a more scalable and economical way by enforcing the memory invariant that every concrete memory location stores one unique value directly on the heap abstraction. Our technique combines the strengths of analyses for precise reasoning about heap contents with approaches that prioritize axiomatization of memory invariants, such as the theory of arrays. Furthermore, by avoiding an explicit case analysis, our technique is scalable and powerful enough to analyze real-world programs with intricate use of arrays and pointers; in particular, we verify the absence of buffer overruns, incorrect casts, and null pointer dereferences in OpenSSH (over 26,000 lines of code) after fixing 4 previously undiscovered bugs found by our system. Our experiments also show that the combination of reasoning about heap contents and enforcing existence and uniqueness invariants is crucial for this level of precision.