TY - GEN
T1 - Linear absolute value relation analysis
AU - Chen, Liqian
AU - Miné, Antoine
AU - Wang, Ji
AU - Cousot, Patrick
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2011
Y1 - 2011
N2 - Linear relation analysis (polyhedral analysis), devoted to discovering linear invariant relations among variables of a program, remains one of the most powerful abstract interpretations but is subject to convexity limitations. Absolute value enjoys piecewise linear expressiveness and thus natively fits to encode certain non-convex properties. Based on this insight, we propose to use linear absolute value relation analysis to discover linear relations among values and absolute values of program variables. Under the framework of abstract interpretation, the analysis yields a new numerical abstract domain, namely the abstract domain of linear absolute value inequalities (∑ k a k x k + ∑ k b k |x k | ≤ c), which can be used to analyze programs involving piecewise linear behaviors (e.g., due to conditional branches or absolute value function calls). Experimental results of our prototype are encouraging; The new abstract domain can find non-convex invariants of interest in practice.
AB - Linear relation analysis (polyhedral analysis), devoted to discovering linear invariant relations among variables of a program, remains one of the most powerful abstract interpretations but is subject to convexity limitations. Absolute value enjoys piecewise linear expressiveness and thus natively fits to encode certain non-convex properties. Based on this insight, we propose to use linear absolute value relation analysis to discover linear relations among values and absolute values of program variables. Under the framework of abstract interpretation, the analysis yields a new numerical abstract domain, namely the abstract domain of linear absolute value inequalities (∑ k a k x k + ∑ k b k |x k | ≤ c), which can be used to analyze programs involving piecewise linear behaviors (e.g., due to conditional branches or absolute value function calls). Experimental results of our prototype are encouraging; The new abstract domain can find non-convex invariants of interest in practice.
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U2 - 10.1007/978-3-642-19718-5_9
DO - 10.1007/978-3-642-19718-5_9
M3 - Conference contribution
AN - SCOPUS:79953232742
SN - 9783642197178
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 156
EP - 175
BT - Programming Languages and Systems - 20th European Symposium on Programming, ESOP 2011, Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS 2011, Proceedings
T2 - 20th European Symposium on Programming, ESOP 2011, Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS 2011
Y2 - 26 March 2011 through 3 April 2011
ER -