{"id":"https://openalex.org/W7162439883","doi":"https://doi.org/10.48550/arxiv.2605.25356","title":"Names Are All You Need: Effective and Safe Regression Test Selection for Python","display_name":"Names Are All You Need: Effective and Safe Regression Test Selection for Python","publication_year":2026,"publication_date":"2026-05-25","ids":{"openalex":"https://openalex.org/W7162439883","doi":"https://doi.org/10.48550/arxiv.2605.25356"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.25356","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25356","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":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.2605.25356","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137010812","display_name":"You Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, You","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013438083","display_name":"Michael Pradel","orcid":"https://orcid.org/0000-0003-1623-498X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pradel, Michael","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137042250","display_name":"Zhongxin Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zhongxin","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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9035000205039978,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9035000205039978,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T10260","display_name":"Software Engineering Research","score":0.022600000724196434,"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/T12127","display_name":"Software System Performance and Reliability","score":0.007400000002235174,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/python","display_name":"Python (programming language)","score":0.7369999885559082},{"id":"https://openalex.org/keywords/regression-testing","display_name":"Regression testing","score":0.6798999905586243},{"id":"https://openalex.org/keywords/dependency-graph","display_name":"Dependency graph","score":0.4490000009536743},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4196000099182129},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.4189000129699707},{"id":"https://openalex.org/keywords/code-coverage","display_name":"Code coverage","score":0.41100001335144043},{"id":"https://openalex.org/keywords/test-case","display_name":"Test case","score":0.3889000117778778},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.3625999987125397}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7815999984741211},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.7369999885559082},{"id":"https://openalex.org/C161821725","wikidata":"https://www.wikidata.org/wiki/Q917415","display_name":"Regression testing","level":5,"score":0.6798999905586243},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.512499988079071},{"id":"https://openalex.org/C16311509","wikidata":"https://www.wikidata.org/wiki/Q4148050","display_name":"Dependency graph","level":3,"score":0.4490000009536743},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4196000099182129},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.4189000129699707},{"id":"https://openalex.org/C53942775","wikidata":"https://www.wikidata.org/wiki/Q1211721","display_name":"Code coverage","level":3,"score":0.41100001335144043},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40549999475479126},{"id":"https://openalex.org/C128942645","wikidata":"https://www.wikidata.org/wiki/Q1568346","display_name":"Test case","level":3,"score":0.3889000117778778},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3650999963283539},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.3625999987125397},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.35929998755455017},{"id":"https://openalex.org/C136643341","wikidata":"https://www.wikidata.org/wiki/Q1361526","display_name":"Reachability","level":2,"score":0.35260000824928284},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.32440000772476196},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3215999901294708},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3183000087738037},{"id":"https://openalex.org/C102379954","wikidata":"https://www.wikidata.org/wiki/Q2589940","display_name":"Call graph","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C97686452","wikidata":"https://www.wikidata.org/wiki/Q7604153","display_name":"Static analysis","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28780001401901245},{"id":"https://openalex.org/C27458966","wikidata":"https://www.wikidata.org/wiki/Q1187693","display_name":"Control flow graph","level":2,"score":0.2849999964237213},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C1009929","wikidata":"https://www.wikidata.org/wiki/Q179550","display_name":"Software bug","level":3,"score":0.2551000118255615},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.25356","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25356","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":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.2605.25356","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25356","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.5088324546813965,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Regression":[0],"test":[1,113,159,184,214],"selection":[2],"reduces":[3,224],"the":[4,70,124,173,195,268,273],"cost":[5],"of":[6,22,89,213,238,247,263,270],"regression":[7,278],"testing":[8,226,279],"by":[9,15,147,188,220,228],"executing":[10],"only":[11,250],"those":[12],"tests":[13,244],"affected":[14,52,187,243],"a":[16,82,86,106,112,136,179,231],"code":[17,90,119],"change.":[18],"Despite":[19],"extensive":[20],"study":[21],"RTS":[23,32,49,73,102,176,200],"in":[24,33,58,127,253,280],"statically":[25],"typed":[26],"languages,":[27],"achieving":[28],"effective":[29],"and":[30,93,100,161],"safe":[31,260],"Python":[34,72,83,175],"is":[35,103,114,121,259],"challenging.":[36],"Python's":[37,54],"dynamic":[38],"typing":[39],"makes":[40],"precise":[41],"call-graph":[42,133],"construction":[43],"difficult,":[44],"which":[45,183],"can":[46],"cause":[47],"call-graph-based":[48],"to":[50,140,164],"miss":[51],"tests.":[53],"eager":[55],"importing":[56],"mechanism,":[57],"contrast,":[59,257],"renders":[60],"file-level":[61,205],"dependency":[62,78,144],"analysis":[63,138],"overly":[64],"conservative.":[65],"This":[66,130],"paper":[67],"presents":[68],"NameRTS,":[69,170,271],"first":[71,174],"approach":[74],"based":[75,202],"on":[76,109,203,216],"fine-grained":[77],"analysis.":[79],"NameRTS":[80,151,193,210,240],"models":[81],"program":[84],"as":[85,105],"bipartite":[87],"graph":[88],"element":[91,120],"nodes":[92],"name":[94,149,166],"nodes,":[95],"with":[96,178,194,249],"edges":[97],"capturing":[98],"definitions":[99],"references.":[101],"formulated":[104],"reachability":[107],"problem":[108],"this":[110,208],"graph:":[111],"selected":[115],"if":[116],"any":[117],"modified":[118],"reachable":[122],"from":[123],"names":[125],"used":[126],"that":[128,156],"test.":[129],"design":[131],"avoids":[132],"construction,":[134],"enabling":[135],"conservative":[137],"amenable":[139],"safety.":[141],"To":[142,168],"control":[143],"cascades":[145],"introduced":[146],"coarse":[148,204],"matching,":[150],"applies":[152],"two":[153],"pruning":[154],"strategies":[155],"leverage":[157],"prior":[158],"executions":[160],"context":[162],"information":[163],"refine":[165],"matching.":[167],"evaluate":[169],"we":[171],"construct":[172],"dataset":[177],"ground":[180],"truth":[181],"indicating":[182],"files":[185,215],"are":[186],"each":[189],"commit.":[190],"We":[191],"compare":[192],"best-performing":[196],"baseline,":[197],"BabelRTS,":[198],"an":[199],"technique":[201],"dependencies.":[206],"On":[207],"benchmark,":[209],"skips":[211],"69.90%":[212],"average,":[217],"outperforming":[218],"BabelRTS":[219,258],"146.5%.":[221],"It":[222],"also":[223],"end-to-end":[225],"time":[227],"45.59%,":[229],"yielding":[230],"107.7%":[232],"improvement":[233],"over":[234],"BabelRTS.":[235],"In":[236,256],"terms":[237],"safety,":[239],"selects":[241],"all":[242],"for":[245,261,275],"99.6%":[246],"commits,":[248],"rare":[251],"misses":[252],"exceptional":[254],"cases.":[255],"76.6%":[262],"commits.":[264],"These":[265],"results":[266],"demonstrate":[267],"effectiveness":[269],"paving":[272],"way":[274],"more":[276],"efficient":[277],"Python.":[281]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-27T00:00:00"}