{"id":165492,"date":"2013-06-20T00:00:00","date_gmt":"2013-06-20T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/on-solving-universally-quantified-horn-clauses\/"},"modified":"2018-10-16T22:07:11","modified_gmt":"2018-10-17T05:07:11","slug":"on-solving-universally-quantified-horn-clauses","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/on-solving-universally-quantified-horn-clauses\/","title":{"rendered":"On Solving Universally Quantified Horn Clauses"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Program proving can be viewed as solving for unknown relations (such as loop invariants, procedure summaries and so on) that occur in the logical verification conditions of a program, such that the verification conditions are valid. Generic logical tools exist that can solve such problems modulo certain background theories, and therefore can be used for program analysis. Here, we extend these techniques to solve for quantified relations. This makes it possible to guide the solver by constraining the form of the proof, allowing it to converge when it otherwise would not. We show how to simulate existing abstract domains in this way, without having to directly implement program analyses or make certain heuristic choices, such as the terms and predicates that form the parameters of the abstract domain. Moreover, the approach gives the flexibility to go beyond these domains and experiment quickly with various invariant forms.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Program proving can be viewed as solving for unknown relations (such as loop invariants, procedure summaries and so on) that occur in the logical verification conditions of a program, such that the verification conditions are valid. Generic logical tools exist that can solve such problems modulo certain background theories, and therefore can be used for [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13560],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-165492","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-programming-languages-software-engineering","msr-locale-en_us"],"msr_publishername":"Springer","msr_edition":"Static Analysis Symposium 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