2011
DOI: 10.1007/978-3-642-22110-1_23
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A Specialization Calculus for Pruning Disjunctive Predicates to Support Verification

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Cited by 10 publications
(5 citation statements)
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“…HIP verification times are decent, but barrier calls are fairly computationally expensive to verify due to the need to check multiple entailments. We believe that performance can be further improved by adding optimizations to SLEEK in the style of [13]. Since barrier calls are fairly rare in actual code, we believe that the performance of HIP/SLEEK on larger examples will be acceptable.…”
Section: Figure 8: Separation Constraint Entailmentmentioning
confidence: 99%
See 1 more Smart Citation
“…HIP verification times are decent, but barrier calls are fairly computationally expensive to verify due to the need to check multiple entailments. We believe that performance can be further improved by adding optimizations to SLEEK in the style of [13]. Since barrier calls are fairly rare in actual code, we believe that the performance of HIP/SLEEK on larger examples will be acceptable.…”
Section: Figure 8: Separation Constraint Entailmentmentioning
confidence: 99%
“…Sleek One of the barrier definitions in barrier.slk is the example barrier given in Figure 1. It took 2,700 (highly tedious) lines of code and 48 seconds of verification time ( Figure 5) to convince Coq that the example barrier definition met the soundness requirements 13 . 13 Techniques such as those developed by Braibant et al [7], Nanevski et al [26], and Gonthier et al [18] can probably eliminate some (but not all) of the tedium of reasoning about the associativity and commutativity of * .…”
Section: Figure 8: Separation Constraint Entailmentmentioning
confidence: 99%
“…The formalism underlying the pruning process is as follows: given a context ∆ c with its overapproximation π c and a branch ∆ i with its over-approximation π b i , if π c ∧π b i is unsatisfiable, so is ∆ c * ∆ i . Similar to the specialization calculus [15], our unfolding mechanism also prunes infeasible disjuncts while unfolding user-defined predicates. However, the specialization calculus performs exhaustive pruning with multiple unfolding that may be highly costly and redundant compared with our one-step unfolding.…”
Section: Implementation Of Separation Logic Instantiationmentioning
confidence: 99%
“…These results suggest that for large code bases, where disjunctive specifications are likely to be used, the verification times can easily become less than satisfactory. Techniques like the one described in [9], where disjunctive formulae are pruned when unfolding shape predicates, can be used to achieve better results. Another approach that can achieve better verification times is to divide the search space in disjoint parts and run the verification in parallel for each of them.…”
Section: Verification Statisticsmentioning
confidence: 99%