{"id":"https://openalex.org/W7125972305","doi":"https://doi.org/10.1109/ase63991.2025.00132","title":"Belief Propagation with Local Structure and Its Applications in Program Analysis","display_name":"Belief Propagation with Local Structure and Its Applications in Program Analysis","publication_year":2025,"publication_date":"2025-11-16","ids":{"openalex":"https://openalex.org/W7125972305","doi":"https://doi.org/10.1109/ase63991.2025.00132"},"language":null,"primary_location":{"id":"doi:10.1109/ase63991.2025.00132","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ase63991.2025.00132","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124142066","display_name":"Yiqian Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqian Wu","raw_affiliation_strings":["Peking University,Key Laboratory of High Confidence Software Technologies,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Key Laboratory of High Confidence Software Technologies,Beijing,China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032709994","display_name":"Yijia Chen","orcid":"https://orcid.org/0000-0002-9295-5028"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Chen","raw_affiliation_strings":["Peking University,Key Laboratory of High Confidence Software Technologies,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Key Laboratory of High Confidence Software Technologies,Beijing,China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5147928501","display_name":"Yingfei Xiong","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingfei Xiong","raw_affiliation_strings":["Peking University,Key Laboratory of High Confidence Software Technologies,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Key Laboratory of High Confidence Software Technologies,Beijing,China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124078582","display_name":"Xin Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Zhang","raw_affiliation_strings":["Peking University,Key Laboratory of High Confidence Software Technologies,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Key Laboratory of High Confidence Software Technologies,Beijing,China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":1.4143,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.87263327,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1566","last_page":"1577"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.7139999866485596,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.7139999866485596,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10142","display_name":"Formal Methods in Verification","score":0.10719999670982361,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.028699999675154686,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/belief-propagation","display_name":"Belief propagation","score":0.8931000232696533},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.8094000220298767},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.7738000154495239},{"id":"https://openalex.org/keywords/approximate-inference","display_name":"Approximate inference","score":0.5705000162124634},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5410000085830688},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5356000065803528},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5192000269889832},{"id":"https://openalex.org/keywords/probabilistic-relevance-model","display_name":"Probabilistic relevance model","score":0.4352000057697296},{"id":"https://openalex.org/keywords/divergence-from-randomness-model","display_name":"Divergence-from-randomness model","score":0.41290000081062317}],"concepts":[{"id":"https://openalex.org/C152948882","wikidata":"https://www.wikidata.org/wiki/Q4060686","display_name":"Belief propagation","level":3,"score":0.8931000232696533},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.8094000220298767},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.7738000154495239},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.5705000162124634},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5475999712944031},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5410000085830688},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5356000065803528},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5192000269889832},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45980000495910645},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4560000002384186},{"id":"https://openalex.org/C143017306","wikidata":"https://www.wikidata.org/wiki/Q3318133","display_name":"Probabilistic relevance model","level":4,"score":0.4352000057697296},{"id":"https://openalex.org/C149189445","wikidata":"https://www.wikidata.org/wiki/Q5283894","display_name":"Divergence-from-randomness model","level":3,"score":0.41290000081062317},{"id":"https://openalex.org/C24404364","wikidata":"https://www.wikidata.org/wiki/Q7246846","display_name":"Probabilistic analysis of algorithms","level":3,"score":0.4034000039100647},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3702000081539154},{"id":"https://openalex.org/C123614077","wikidata":"https://www.wikidata.org/wiki/Q1364905","display_name":"Propagation of uncertainty","level":2,"score":0.3628000020980835},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.33739998936653137},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3336000144481659},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32839998602867126},{"id":"https://openalex.org/C159246509","wikidata":"https://www.wikidata.org/wiki/Q5428725","display_name":"Factor graph","level":3,"score":0.3262999951839447},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C137002209","wikidata":"https://www.wikidata.org/wiki/Q898521","display_name":"Hidden variable theory","level":3,"score":0.31139999628067017},{"id":"https://openalex.org/C137105694","wikidata":"https://www.wikidata.org/wiki/Q3407510","display_name":"Local consistency","level":4,"score":0.3057999908924103},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2962000072002411},{"id":"https://openalex.org/C2779363554","wikidata":"https://www.wikidata.org/wiki/Q5420835","display_name":"Expectation propagation","level":4,"score":0.2802000045776367},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2770000100135803},{"id":"https://openalex.org/C162500139","wikidata":"https://www.wikidata.org/wiki/Q2835887","display_name":"Estimation of distribution algorithm","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C165216359","wikidata":"https://www.wikidata.org/wiki/Q670653","display_name":"Marginal distribution","level":3,"score":0.26919999718666077},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2612000107765198},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.2547000050544739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ase63991.2025.00132","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ase63991.2025.00132","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W163786857","https://openalex.org/W1516111018","https://openalex.org/W1535430927","https://openalex.org/W2047650874","https://openalex.org/W2062818807","https://openalex.org/W2089417393","https://openalex.org/W2102506621","https://openalex.org/W2137813581","https://openalex.org/W2141955346","https://openalex.org/W2156723666","https://openalex.org/W2166091242","https://openalex.org/W2395654200","https://openalex.org/W2481629607","https://openalex.org/W2485330962","https://openalex.org/W2494200839","https://openalex.org/W2499134782","https://openalex.org/W2577537660","https://openalex.org/W2593267253","https://openalex.org/W2762682773","https://openalex.org/W2798352717","https://openalex.org/W2808311877","https://openalex.org/W2926374695","https://openalex.org/W2954738632","https://openalex.org/W3084921114","https://openalex.org/W3194969426","https://openalex.org/W4284692434","https://openalex.org/W4284702776","https://openalex.org/W4313729819"],"related_works":[],"abstract_inverted_index":{"In":[0,12],"program":[1,40,142],"analysis,":[2],"there":[3],"is":[4,37,66,78,137],"an":[5,111],"emerging":[6],"trend":[7],"to":[8,51,89,102],"apply":[9],"probabilistic":[10,21,87,147],"reasoning.":[11],"general,":[13],"these":[14],"approaches":[15],"build":[16],"their":[17],"models":[18,23,43],"based":[19,117,145],"on":[20,118,139,146,170],"graphical":[22,148],"because":[24],"they":[25],"can":[26,81,156],"express":[27],"local":[28,84,107],"correlations":[29],"through":[30],"factors":[31,105],"in":[32],"a":[33],"compositional":[34],"manner,":[35],"which":[36],"suitable":[38],"for":[39,57],"analysis.":[41],"These":[42],"commonly":[44],"use":[45,99],"the":[46,53,60,83,92,104,123,164],"loopy":[47,63,113,166],"belief":[48,64,114,167],"propagation":[49,65,115,168],"algorithm":[50,116,125,169],"infer":[52],"marginal":[54],"probability":[55],"distribution":[56],"efficiency.":[58],"However,":[59],"efficiency":[61],"of":[62,86,132],"still":[67],"affected":[68],"by":[69],"large":[70],"factors.":[71],"To":[72,94],"address":[73],"this":[74,96],"challenge,":[75],"our":[76,133,154],"insight":[77],"that":[79,153],"we":[80,98],"exploit":[82],"structure":[85],"constraints":[88],"speed":[90],"up":[91],"inference.":[93],"realize":[95],"idea,":[97],"if-then":[100],"rules":[101],"encode":[103],"with":[106],"structures":[108],"and":[109,127,159],"propose":[110],"efficient":[112],"it.":[119],"We":[120],"also":[121],"discuss":[122],"inference":[124],"complexity":[126],"prove":[128],"some":[129],"applicable":[130],"conditions":[131],"approach.":[134],"Our":[135],"approach":[136,155],"evaluated":[138],"two":[140],"existing":[141],"analysis":[143],"works":[144],"models.":[149],"The":[150],"results":[151],"show":[152],"be":[157],"5.11":[158],"2.31":[160],"times":[161],"faster":[162],"than":[163],"original":[165],"average,":[171],"respectively.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-25T07:29:55.448023","created_date":"2026-01-29T00:00:00"}