{"id":"https://openalex.org/W7165635032","doi":"https://doi.org/10.48550/arxiv.2606.22906","title":"From Fragments to Paths: Task-Level Context Recovery for Large Industrial Codebases","display_name":"From Fragments to Paths: Task-Level Context Recovery for Large Industrial Codebases","publication_year":2026,"publication_date":"2026-06-22","ids":{"openalex":"https://openalex.org/W7165635032","doi":"https://doi.org/10.48550/arxiv.2606.22906"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.22906","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22906","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2606.22906","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139214912","display_name":"Jiawei He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Jiawei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139141315","display_name":"Weisong Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Weisong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071295669","display_name":"Mengyu Shi","orcid":"https://orcid.org/0000-0002-3720-6075"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Mengyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139180250","display_name":"Jie Jia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia, Jie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139195648","display_name":"Tong Bian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bian, Tong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030018760","display_name":"Xiaomin Yang","orcid":"https://orcid.org/0000-0002-5593-5108"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Xikai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136693321","display_name":"Dong Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Dong","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":0.8604999780654907,"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":0.8604999780654907,"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/T11986","display_name":"Scientific Computing and Data Management","score":0.018300000578165054,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.011599999852478504,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/codebase","display_name":"Codebase","score":0.7307999730110168},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5733000040054321},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5619999766349792},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5432000160217285},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.4740999937057495},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.46320000290870667},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.4325000047683716},{"id":"https://openalex.org/keywords/context-switch","display_name":"Context switch","score":0.4237000048160553}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7563999891281128},{"id":"https://openalex.org/C51929080","wikidata":"https://www.wikidata.org/wiki/Q2425187","display_name":"Codebase","level":3,"score":0.7307999730110168},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5733000040054321},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5619999766349792},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5432000160217285},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.4740999937057495},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.46320000290870667},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.4325000047683716},{"id":"https://openalex.org/C53833338","wikidata":"https://www.wikidata.org/wiki/Q1061424","display_name":"Context switch","level":2,"score":0.4237000048160553},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.42289999127388},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4097999930381775},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3675000071525574},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.35899999737739563},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3537999987602234},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3474999964237213},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30720001459121704},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.29649999737739563},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C8505890","wikidata":"https://www.wikidata.org/wiki/Q605095","display_name":"Budget constraint","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.29100000858306885},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27379998564720154},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26589998602867126},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2619999945163727}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.22906","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22906","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.22906","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22906","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4786371886730194,"id":"https://metadata.un.org/sdg/9"}],"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],"have":[3],"shown":[4],"strong":[5],"performance":[6,203],"on":[7,84,153,163,171,204],"software":[8],"engineering":[9],"(SE)":[10],"tasks,":[11,100,132],"yet":[12],"understanding":[13,199],"large":[14,47,154],"industrial":[15,48,78,117],"repositories":[16],"remains":[17],"challenging.":[18],"Existing":[19],"methods":[20],"often":[21],"retrieve":[22],"only":[23],"local":[24],"fragments":[25],"and":[26,61,81,93,129,156],"fail":[27],"to":[28,56,149,159],"recover":[29,62],"the":[30,103,185],"broader":[31,63],"task-relevant":[32,64,90],"context":[33,65],"needed":[34],"for":[35,46],"complex":[36,205],"repository-level":[37],"tasks.":[38,207],"We":[39],"present":[40],"DeepDiscovery,":[41],"a":[42,52,120,167,174,180],"task-level":[43,197],"repository-understanding":[44,79],"method":[45],"codebases.":[49],"DeepDiscovery":[50,87,101,133,178],"uses":[51],"two-stage":[53],"\\textit{Location--Inference}":[54],"framework":[55],"localize":[57],"high-confidence":[58],"task":[59],"anchors":[60],"over":[66],"multi-relational":[67],"repository":[68,198],"structure":[69],"under":[70],"budget":[71],"constraints.":[72],"Across":[73],"controlled":[74,168],"method-level":[75],"evaluation,":[76],"organization-internal":[77,116],"scenarios,":[80],"end-to-end":[82,169],"evaluation":[83,170],"SWE-bench":[85,172],"Verified,":[86,173],"consistently":[88],"improves":[89,134],"file":[91,105],"recovery":[92,106],"downstream":[94],"SE":[95,206],"performance.":[96],"On":[97,115],"27":[98,126],"medium-scale":[99,127,164],"achieves":[102,179],"best":[104],"quality":[107],"among":[108],"five":[109],"representative":[110],"baselines":[111],"without":[112],"offline":[113],"preprocessing.":[114],"tasks":[118,128],"from":[119,147,157],"production-scale":[121],"integrated":[122],"codebase":[123],"ecosystem,":[124],"including":[125],"40":[130],"large-scale":[131],"Full":[135],"Recall":[136],"Rate":[137],"across":[138],"multiple":[139],"AI":[140],"coding":[141],"systems,":[142],"with":[143,177],"absolute":[144],"gains":[145],"ranging":[146],"1.6":[148],"9.2":[150],"percentage":[151,161,190],"points":[152,162],"subprojects":[155],"2.5":[158],"7.4":[160],"subprojects.":[165],"In":[166],"system":[175],"equipped":[176],"78.6\\%":[181],"Solve":[182],"Rate,":[183],"outperforming":[184],"corresponding":[186],"baseline":[187],"by":[188],"8.2":[189],"points.":[191],"These":[192],"results":[193],"suggest":[194],"that":[195],"stronger":[196],"can":[200],"improve":[201],"coding-agent":[202]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}