{"id":569919,"date":"2019-02-26T11:55:13","date_gmt":"2019-02-26T19:55:13","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=569919"},"modified":"2019-02-26T11:55:13","modified_gmt":"2019-02-26T19:55:13","slug":"symbolic-regex-matcher","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/symbolic-regex-matcher\/","title":{"rendered":"Symbolic Regex Matcher"},"content":{"rendered":"<p>Symbolic regex matcher is a new open source .NET <em>regular expression matching tool and match generator<\/em> in the <em>Microsoft Automata<\/em> framework. It is based on the .NET regex parser in combination with a set based representation of character classes. The main feature of the tool is that the core matching algorithms are based on <em>symbolic derivatives<\/em> that support extended regular expression operations such as intersection and complement and also support a large set of commonly used features such as bounded loop quantifiers. The particularly useful features of the tool are that it supports full UTF16 encoded strings, the match generation is backtracking free, thread safe, and parallelizes with low overhead in multithreaded applications. We discuss the main design decisions behind the tool, explain the core algorithmic ideas and how the tool works, discuss some practical usage scenarios, and compare it to existing state of the art.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Symbolic regex matcher is a new open source .NET regular expression matching tool and match generator in the Microsoft Automata framework. It is based on the .NET regex parser in combination with a set based representation of character classes. The main feature of the tool is that the core matching algorithms are based on symbolic [&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-569919","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":"","msr_affiliation":"","msr_published_date":"2019-4-1","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":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2019\/02\/SRM_tacas19.pdf","id":"569934","title":"srm_tacas19","label_id":"243103","label":0}],"msr_related_uploader":"","msr_attachments":[{"id":569934,"url":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2019\/02\/SRM_tacas19.pdf"}],"msr-author-ordering":[{"type":"edited_text","value":"Margus Veanes (margus)","user_id":32806,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Margus Veanes (margus)"},{"type":"edited_text","value":"Olli Saarikivi (olsaarik)","user_id":37700,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Olli Saarikivi (olsaarik)"},{"type":"text","value":"Tiki Wan","user_id":0,"rest_url":false},{"type":"text","value":"Eric Xu","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[199565],"msr_event":[],"msr_group":[144812],"msr_project":[259698],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":259698,"post_title":"Automata","post_name":"automata","post_type":"msr-project","post_date":"2016-07-20 18:35:07","post_modified":"2018-12-04 17:02:22","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/automata\/","post_excerpt":"Automata is a .NET library that provides algorithms for composing and analyzing regular expressions, automata, and transducers. In addition to classical word automata, it also includes algorithms for analysis of tree automata and tree transducers. The library covers algorithms over finite alphabets as well as their symbolic counterparts. In symbolic automata concrete characters have been replaced by character predicates. Such predicates can range over very large or even infinite alphabets, like integers. 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