{"id":"https://openalex.org/W7138883975","doi":"https://doi.org/10.48550/arxiv.2603.17893","title":"scicode-lint: Detecting Methodology Bugs in Scientific Python Code with LLM-Generated Patterns","display_name":"scicode-lint: Detecting Methodology Bugs in Scientific Python Code with LLM-Generated Patterns","publication_year":2026,"publication_date":"2026-03-18","ids":{"openalex":"https://openalex.org/W7138883975","doi":"https://doi.org/10.48550/arxiv.2603.17893"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.17893","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17893","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":"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.2603.17893","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041278425","display_name":"Sergey Samsonau","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Samsonau, Sergey V.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5041278425"],"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/T13650","display_name":"Computational Physics and Python Applications","score":0.26249998807907104,"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/T13650","display_name":"Computational Physics and Python Applications","score":0.26249998807907104,"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/T11986","display_name":"Scientific Computing and Data Management","score":0.0934000015258789,"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":0.09120000153779984,"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/python","display_name":"Python (programming language)","score":0.8715000152587891},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6316999793052673},{"id":"https://openalex.org/keywords/dependency-graph","display_name":"Dependency graph","score":0.49140000343322754},{"id":"https://openalex.org/keywords/random-testing","display_name":"Random testing","score":0.4325999915599823},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.3961000144481659},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.36809998750686646},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.364300012588501}],"concepts":[{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.8715000152587891},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.791100025177002},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6316999793052673},{"id":"https://openalex.org/C16311509","wikidata":"https://www.wikidata.org/wiki/Q4148050","display_name":"Dependency graph","level":3,"score":0.49140000343322754},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.45019999146461487},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4438000023365021},{"id":"https://openalex.org/C106159264","wikidata":"https://www.wikidata.org/wiki/Q17146789","display_name":"Random testing","level":4,"score":0.4325999915599823},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.3961000144481659},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.36809998750686646},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.364300012588501},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3560999929904938},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.3499999940395355},{"id":"https://openalex.org/C1009929","wikidata":"https://www.wikidata.org/wiki/Q179550","display_name":"Software bug","level":3,"score":0.31439998745918274},{"id":"https://openalex.org/C207850805","wikidata":"https://www.wikidata.org/wiki/Q269608","display_name":"Reverse engineering","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C97686452","wikidata":"https://www.wikidata.org/wiki/Q7604153","display_name":"Static analysis","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C137287247","wikidata":"https://www.wikidata.org/wiki/Q1329550","display_name":"Static program analysis","level":4,"score":0.263700008392334},{"id":"https://openalex.org/C92966194","wikidata":"https://www.wikidata.org/wiki/Q651794","display_name":"Compiled language","level":4,"score":0.2624000012874603},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.17893","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17893","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":"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.2603.17893","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17893","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":"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":"Responsible consumption and production","id":"https://metadata.un.org/sdg/12","score":0.47081050276756287}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Methodology":[0],"bugs":[1],"in":[2],"scientific":[3,64,139],"Python":[4,44],"code":[5,59],"produce":[6],"plausible":[7],"but":[8],"incorrect":[9,77],"results":[10],"that":[11,28],"traditional":[12],"linters":[13],"and":[14,48,79],"static":[15],"analysis":[16],"tools":[17,34],"cannot":[18],"detect.":[19],"Several":[20],"research":[21],"groups":[22],"have":[23],"built":[24],"ML-specific":[25],"linters,":[26],"demonstrating":[27],"detection":[29,129],"is":[30,144,159],"feasible.":[31],"Yet":[32],"these":[33],"share":[35],"a":[36,154],"sustainability":[37],"problem:":[38],"dependency":[39],"on":[40,50,136,153],"specific":[41],"pylint":[42],"or":[43],"versions,":[45],"limited":[46],"packaging,":[47],"reliance":[49],"manual":[51],"engineering":[52,118],"for":[53,68],"every":[54],"new":[55,112],"pattern.":[56],"As":[57],"AI-generated":[58],"increases":[60],"the":[61,66],"volume":[62],"of":[63],"software,":[65],"need":[67],"automated":[69],"methodology":[70],"checking":[71],"(such":[72],"as":[73],"detecting":[74],"data":[75],"leakage,":[76],"cross-validation,":[78],"missing":[80],"random":[81],"seeds)":[82],"grows.":[83],"We":[84],"present":[85],"scicode-lint,":[86],"whose":[87],"two-tier":[88],"architecture":[89],"separates":[90],"pattern":[91,151],"design":[92],"(frontier":[93],"models":[94],"at":[95,103,133],"build":[96],"time)":[97],"from":[98],"execution":[99],"(small":[100],"local":[101],"model":[102],"runtime).":[104],"Patterns":[105],"are":[106],"generated,":[107],"not":[108,117],"hand-coded;":[109],"adapting":[110],"to":[111],"library":[113],"versions":[114],"costs":[115],"tokens,":[116],"hours.":[119],"On":[120,161],"Kaggle":[121],"notebooks":[122],"with":[123,147],"human-labeled":[124],"ground":[125],"truth,":[126],"preprocessing":[127],"leakage":[128],"reaches":[130],"65%":[131],"precision":[132,143,158],"100%":[134],"recall;":[135],"38":[137],"published":[138],"papers":[140],"applying":[141],"AI/ML,":[142],"62%":[145],"(LLM-judged)":[146],"substantial":[148],"variation":[149],"across":[150,168],"categories;":[152],"held-out":[155],"paper":[156],"set,":[157],"54%.":[160],"controlled":[162],"tests,":[163],"scicode-lint":[164],"achieves":[165],"97.7%":[166],"accuracy":[167],"66":[169],"patterns.":[170]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-20T00:00:00"}