[{"_id":"4458","title":"Abstractions from proofs","date_created":"2018-12-11T12:08:57Z","conference":{"name":"POPL: Principles of Programming Languages"},"page":"232 - 244","publisher":"ACM","extern":1,"day":"01","date_updated":"2019-08-02T12:38:30Z","publist_id":"270","citation":{"mla":"Henzinger, Thomas A., et al. *Abstractions from Proofs*. ACM, 2004, pp. 232–44, doi:10.1145/964001.964021.","ama":"Henzinger TA, Jhala R, Majumdar R, Mcmillan K. Abstractions from proofs. In: ACM; 2004:232-244. doi:10.1145/964001.964021","short":"T.A. Henzinger, R. Jhala, R. Majumdar, K. Mcmillan, in:, ACM, 2004, pp. 232–244.","apa":"Henzinger, T. A., Jhala, R., Majumdar, R., & Mcmillan, K. (2004). Abstractions from proofs (pp. 232–244). Presented at the POPL: Principles of Programming Languages, ACM. https://doi.org/10.1145/964001.964021","chicago":"Henzinger, Thomas A, Ranjit Jhala, Ritankar Majumdar, and Kenneth Mcmillan. “Abstractions from Proofs,” 232–44. ACM, 2004. https://doi.org/10.1145/964001.964021.","ista":"Henzinger TA, Jhala R, Majumdar R, Mcmillan K. 2004. Abstractions from proofs. POPL: Principles of Programming Languages 232–244.","ieee":"T. A. Henzinger, R. Jhala, R. Majumdar, and K. Mcmillan, “Abstractions from proofs,” presented at the POPL: Principles of Programming Languages, 2004, pp. 232–244."},"publication_status":"published","type":"conference","abstract":[{"text":"The success of model checking for large programs depends crucially on the ability to efficiently construct parsimonious abstractions. A predicate abstraction is parsimonious if at each control location, it specifies only relationships between current values of variables, and only those which are required for proving correctness. Previous methods for automatically refining predicate abstractions until sufficient precision is obtained do not systematically construct parsimonious abstractions: predicates usually contain symbolic variables, and are added heuristically and often uniformly to many or all control locations at once. We use Craig interpolation to efficiently construct, from a given abstract error trace which cannot be concretized, a parsominous abstraction that removes the trace. At each location of the trace, we infer the relevant predicates as an interpolant between the two formulas that define the past and the future segment of the trace. Each interpolant is a relationship between current values of program variables, and is relevant only at that particular program location. It can be found by a linear scan of the proof of infeasibility of the trace.We develop our method for programs with arithmetic and pointer expressions, and call-by-value function calls. For function calls, Craig interpolation offers a systematic way of generating relevant predicates that contain only the local variables of the function and the values of the formal parameters when the function was called. We have extended our model checker Blast with predicate discovery by Craig interpolation, and applied it successfully to C programs with more than 130,000 lines of code, which was not possible with approaches that build less parsimonious abstractions.","lang":"eng"}],"doi":"10.1145/964001.964021","month":"04","quality_controlled":0,"status":"public","author":[{"orcid":"0000−0002−2985−7724","full_name":"Thomas Henzinger","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","first_name":"Thomas A","last_name":"Henzinger"},{"last_name":"Jhala","first_name":"Ranjit","full_name":"Jhala, Ranjit"},{"full_name":"Majumdar, Ritankar S","first_name":"Ritankar","last_name":"Majumdar"},{"full_name":"McMillan, Kenneth L","last_name":"Mcmillan","first_name":"Kenneth"}],"year":"2004","date_published":"2004-04-01T00:00:00Z"}]