{"id":168338,"date":"2015-07-01T00:00:00","date_gmt":"2015-07-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/symbolic-polytopes-for-quantitative-interpolation-and-verification\/"},"modified":"2018-10-16T20:15:46","modified_gmt":"2018-10-17T03:15:46","slug":"symbolic-polytopes-for-quantitative-interpolation-and-verification","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/symbolic-polytopes-for-quantitative-interpolation-and-verification\/","title":{"rendered":"Symbolic Polytopes for Quantitative Interpolation and Verification"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Proving quantitative properties of programs, such as bounds on resource usage or information leakage, often leads to verification conditions that involve cardinalities of sets. Existing approaches for dealing with such verification conditions operate by checking cardinality bounds for given formulas. However, they cannot synthesize formulas that satisfy given cardinality constraints, which limits their applicability for inferring cardinality-based inductive arguments. In this paper we present an algorithm for synthesizing formulas for given cardinality constraints, which relies on the theory of counting integral points in symbolic polytopes. We cast our algorithm in terms of a cardinality-constrained interpolation procedure, which we put to work in a solver for recursive Horn clauses with cardinality constraints based on abstraction refinement. We implement our technique and describe its evaluation on a number of representative examples.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Proving quantitative properties of programs, such as bounds on resource usage or information leakage, often leads to verification conditions that involve cardinalities of sets. Existing approaches for dealing with such verification conditions operate by checking cardinality bounds for given formulas. However, they cannot synthesize formulas that satisfy given cardinality constraints, which limits their applicability 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-168338","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":"Computer Aided Verification (CAV)","msr_affiliation":"","msr_published_date":"2015-07-01","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"204267","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"main.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/main-2.pdf","id":204267,"label_id":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"text","value":"Klaus v. 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