Semantic integrity assertions are predicates that define consistent database states. To enforce such assertions, a database system must prevent any update from mapping a consistent state to an inconsistent one. In this paper, we describe an enforcement method that is efficient for a large class of
\nrelational calculus assertions. The method automatically selects minima and maxima of certain sets to maintain as redundant data in the database. This redundant data is sufficient for enforcing all of the assertions in the class, yet it can be easily maintained. Correctness proofs are expressed in Hoare’s program logic.<\/p>\n","protected":false},"excerpt":{"rendered":"
Semantic integrity assertions are predicates that define consistent database states. To enforce such assertions, a database system must prevent any update from mapping a consistent state to an inconsistent one. In this paper, we describe an enforcement method that is efficient for a large class of relational calculus assertions. The method automatically selects minima and […]<\/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":[13563],"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-712234","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-data-platform-analytics","msr-locale-en_us"],"msr_publishername":"IEEE","msr_edition":"","msr_affiliation":"","msr_published_date":"1980-9-1","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\/2020\/12\/BernsteinBlausteinClarke-VLDB1980.pdf","id":"712243","title":"bernsteinblausteinclarke-vldb1980","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[{"id":712243,"url":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2020\/12\/BernsteinBlausteinClarke-VLDB1980.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"Phil Bernstein","user_id":33253,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Phil Bernstein"},{"type":"text","value":"Barbara T. 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