{"id":{"repo_id":"uoit","oai_identifier":"oai:ontariotechu.scholaris.ca:10155/1282"},"canonical_url":"https://search.dev.ndltd.org/etd/uoit/oai:ontariotechu.scholaris.ca:10155/1282","repository":{"repo_id":"uoit","name":"Ontario Institute of Technology","base_url":"https://ontariotechu.scholaris.ca/server/oai/request"},"display":{"title":"Extending the relational model with constraint satisfaction","abstract":"We propose a new approach to data driven constraint programming. By extending the relational model to handle constraints and variables as first class citizens, we are able to express first order logic SAT problems using an extended SQL which we refer to as SAT/SQL. With SAT/SQL, one can efficiently solve a wide range of practical constraint and optimization problems. SAT/SQL integrates both SAT solver and relational data processing to enable efficient and large scale data driven constraint programming. Furthermore, our research presents two novel meta-programming operators: MINREPAIR and MIN-CONFLICT which are iterative debugging facilities for constraint programming with SAT/SQL.","abstract_html":"We propose a new approach to data driven constraint programming. By extending the relational model to handle constraints and variables as first class citizens, we are able to express first order logic SAT problems using an extended SQL which we refer to as SAT/SQL. With SAT/SQL, one can efficiently solve a wide range of practical constraint and optimization problems. SAT/SQL integrates both SAT solver and relational data processing to enable efficient and large scale data driven constraint programming. Furthermore, our research presents two novel meta-programming operators: MINREPAIR and MIN-CONFLICT which are iterative debugging facilities for constraint programming with SAT/SQL.","abstract_has_math":false,"creators":["Valdron, Michael J."],"institution":"University of Ontario Institute of Technology","degree_name":"Master of Science (MSc)","degree_level":null,"degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":[],"advisors":["Pu, Ken"],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-01-01","date_published":"2021-01-01","updated_at":"2026-07-24T05:35:36Z","subjects":["Constraints","Databases","Algebra","Optimization","Satisfiability"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10155/1282","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Pu, Ken"]},{"key":"dc:creator","label":"Author","values":["Valdron, Michael J."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2021-04-19T20:18:26Z","2022-03-29T17:27:01Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2021-04-19T20:18:26Z","2022-03-29T17:27:01Z"]},{"key":"dc:date.issued","label":"Date","values":["2021-01-01"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MSc)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Ontario Institute of Technology"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Constraints","Databases","Algebra","Optimization","Satisfiability"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10155/1282"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["We propose a new approach to data driven constraint programming. By extending the relational model to handle constraints and variables as first class citizens, we are able to express first order logic SAT problems using an extended SQL which we refer to as SAT/SQL. With SAT/SQL, one can efficiently solve a wide range of practical constraint and optimization problems. SAT/SQL integrates both SAT solver and relational data processing to enable efficient and large scale data driven constraint programming. Furthermore, our research presents two novel meta-programming operators: MINREPAIR and MIN-CONFLICT which are iterative debugging facilities for constraint programming with SAT/SQL."]},{"key":"dc:title","label":"Title","values":["Extending the relational model with constraint satisfaction"]}]}],"canonical_facts":{"dc:contributor.advisor":["Pu, Ken"],"dc:creator":["Valdron, Michael J."],"dc:date.accessioned":["2021-04-19T20:18:26Z","2022-03-29T17:27:01Z"],"dc:date.available":["2021-04-19T20:18:26Z","2022-03-29T17:27:01Z"],"dc:date.issued":["2021-01-01"],"dc:description.abstract":["We propose a new approach to data driven constraint programming. By extending the relational model to handle constraints and variables as first class citizens, we are able to express first order logic SAT problems using an extended SQL which we refer to as SAT/SQL. With SAT/SQL, one can efficiently solve a wide range of practical constraint and optimization problems. SAT/SQL integrates both SAT solver and relational data processing to enable efficient and large scale data driven constraint programming. Furthermore, our research presents two novel meta-programming operators: MINREPAIR and MIN-CONFLICT which are iterative debugging facilities for constraint programming with SAT/SQL."],"dc:identifier.uri":["https://hdl.handle.net/10155/1282"],"dc:language.iso":["en"],"dc:subject":["Constraints","Databases","Algebra","Optimization","Satisfiability"],"dc:title":["Extending the relational model with constraint satisfaction"],"dc:type":["Thesis"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_name":["Master of Science (MSc)"],"thesis:institution_name":["University of Ontario Institute of Technology"]},"updated_at":"2026-07-24T05:35:36Z"}