{"id":"https://openalex.org/W7169169256","doi":"https://doi.org/10.48550/arxiv.2607.13439","title":"DREA: Decoupled Reasoning and Exploration Agents for Repository-Level Vulnerability Detection","display_name":"DREA: Decoupled Reasoning and Exploration Agents for Repository-Level Vulnerability Detection","publication_year":2026,"publication_date":"2026-07-15","ids":{"openalex":"https://openalex.org/W7169169256","doi":"https://doi.org/10.48550/arxiv.2607.13439"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.13439","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.13439","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.13439","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140974951","display_name":"Mingyang Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Mingyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5140988944","display_name":"Guozhu Meng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meng, Guozhu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.3059999942779541,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10260","display_name":"Software Engineering Research","score":0.3059999942779541,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12479","display_name":"Web Application Security Vulnerabilities","score":0.16850000619888306,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10734","display_name":"Information and Cyber Security","score":0.1145000010728836,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/correctness","display_name":"Correctness","score":0.8061000108718872},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6129000186920166},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5058000087738037},{"id":"https://openalex.org/keywords/vulnerability","display_name":"Vulnerability (computing)","score":0.47749999165534973},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.47099998593330383},{"id":"https://openalex.org/keywords/automated-reasoning","display_name":"Automated reasoning","score":0.374099999666214},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.36230000853538513},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.33079999685287476}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8133999705314636},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.8061000108718872},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6129000186920166},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5058000087738037},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49470001459121704},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.47749999165534973},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.47099998593330383},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4537999927997589},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.374099999666214},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.36230000853538513},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.31209999322891235},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C153180980","wikidata":"https://www.wikidata.org/wiki/Q19776675","display_name":"Commit","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28349998593330383},{"id":"https://openalex.org/C74072328","wikidata":"https://www.wikidata.org/wiki/Q1142726","display_name":"Intelligent agent","level":2,"score":0.2757999897003174},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C2777220311","wikidata":"https://www.wikidata.org/wiki/Q6423340","display_name":"Knowledge acquisition","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.13439","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.13439","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.13439","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.13439","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"are":[4,217],"increasingly":[5],"applied":[6],"to":[7,11,39,125,160,179,187],"vulnerability":[8,66,87,169],"detection":[9,51,116,152],"due":[10],"their":[12],"strong":[13],"code":[14],"comprehension":[15],"capabilities,":[16],"but":[17],"most":[18],"existing":[19],"approaches":[20],"rely":[21],"on":[22,106],"isolated":[23],"functions":[24,47],"or":[25,48],"context":[26,42,105,109],"extracted":[27],"by":[28,81,98,195,221],"fixed":[29],"program-analysis":[30],"rules.":[31],"These":[32],"methods":[33],"cannot":[34],"adaptively":[35],"explore":[36],"repository-level":[37,65,104],"dependencies":[38],"gather":[40],"sufficient":[41],"when":[43],"vulnerabilities":[44],"span":[45],"multiple":[46],"files,":[49],"compromising":[50],"reliability.":[52],"We":[53],"present":[54],"DREA":[55,68,174,212],"(Decoupled":[56],"Reasoning":[57,200],"and":[58,89,93,213],"Exploration":[59],"Agents),":[60],"a":[61,77,99,139,156,163,196,229],"hypothesis-driven":[62],"framework":[63],"for":[64,210,232],"detection.":[67],"decouples":[69],"reasoning":[70,157,226],"from":[71,147,177],"exploration":[72,124],"through":[73],"two":[74],"collaborating":[75],"agents:":[76],"planning":[78],"agent":[79,96],"backed":[80],"an":[82,94],"advanced":[83],"LLM":[84],"that":[85,102,205],"forms":[86],"hypotheses":[88],"directs":[90],"the":[91,112,126,167,188,214],"investigation,":[92],"explorer":[95],"powered":[97],"lightweight":[100],"model":[101,128],"retrieves":[103],"demand.":[107],"Goal-directed":[108],"acquisition":[110],"is":[111],"primary":[113],"source":[114],"of":[115,142,185,198,207],"improvement":[117],"in":[118],"this":[119],"design,":[120],"while":[121,181],"offloading":[122,182],"token-heavy":[123],"local":[127],"keeps":[129],"inference":[130],"economically":[131],"tractable.":[132],"To":[133],"support":[134],"evaluation,":[135],"we":[136,154],"construct":[137],"RepoPairBench,":[138],"repository-grounded":[140],"benchmark":[141],"validated":[143],"Python":[144],"vulnerability-fix":[145],"pairs":[146],"real-world":[148],"projects.":[149],"Beyond":[150],"binary":[151],"accuracy,":[153],"introduce":[155],"correctness":[158,201],"evaluation":[159],"assess":[161],"whether":[162],"model's":[164],"rationale":[165],"matches":[166],"documented":[168],"mechanism.":[170],"Across":[171],"three":[172],"LLMs,":[173],"improves":[175],"Pair-Correctness":[176],"19-26%":[178],"30-42%":[180],"over":[183],"93%":[184],"tokens":[186],"explorer,":[189],"reducing":[190],"estimated":[191],"billable":[192],"API":[193],"cost":[194],"factor":[197],"16-48.":[199],"analysis":[202],"further":[203],"reveals":[204],"26-55%":[206],"true":[208],"positives,":[209],"both":[211],"function-only":[215],"baseline,":[216],"correct":[218],"predictions":[219],"supported":[220],"flawed":[222],"rationales,":[223],"identifying":[224],"security":[225],"quality":[227],"as":[228],"shared":[230],"bottleneck":[231],"current":[233],"LLMs.":[234]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-17T00:00:00"}
