Unification-based pointer analysis with directional assignments
PLDI '00 Proceedings of the ACM SIGPLAN 2000 conference on Programming language design and implementation
POPL '77 Proceedings of the 4th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
A New Numerical Abstract Domain Based on Difference-Bound Matrices
PADO '01 Proceedings of the Second Symposium on Programs as Data Objects
Varieties of Static Analyzers: A Comparison with ASTREE
TASE '07 Proceedings of the First Joint IEEE/IFIP Symposium on Theoretical Aspects of Software Engineering
A Comparative Study of Industrial Static Analysis Tools
Electronic Notes in Theoretical Computer Science (ENTCS)
Formal Methods in System Design
Static program analysis of large embedded code base: an experience
Proceedings of the 4th India Software Engineering Conference
Survey of array out of bound access checkers for C code
Proceedings of the 5th India Software Engineering Conference
Trace partitioning in abstract interpretation based static analyzers
ESOP'05 Proceedings of the 14th European conference on Programming Languages and Systems
ESOP'05 Proceedings of the 14th European conference on Programming Languages and Systems
Counterexample driven refinement for abstract interpretation
TACAS'06 Proceedings of the 12th international conference on Tools and Algorithms for the Construction and Analysis of Systems
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Abstract interpretation is widely used to perform static code analysis with non-relational (interval) as well as relational (difference-bound matrices, polyhedral) domains. Analysis using non-relational domains is highly scalable but delivers imprecise results, whereas, use of relational domains produces precise results but does not scale up. We have developed a tool that implements K-limited path sensitive interval domain analysis to get precise results without losing on scalability. The tool was able to successfully analyse 10 million lines of embedded code for different properties such as division by zero, array index out of bound (AIOB), overflow-underflow and so on. This paper presents details of the tool and results of our experiments for detecting AIOB property. A comparison with the existing tools in the market demonstrates that our tool is more precise and scales better.