{"id":"https://openalex.org/W4391009381","doi":"https://doi.org/10.48550/arxiv.2401.07576","title":"PyTester: Deep Reinforcement Learning for Text-to-Testcase Generation","display_name":"PyTester: Deep Reinforcement Learning for Text-to-Testcase Generation","publication_year":2024,"publication_date":"2024-01-15","ids":{"openalex":"https://openalex.org/W4391009381","doi":"https://doi.org/10.48550/arxiv.2401.07576"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2401.07576","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2401.07576","pdf_url":"https://arxiv.org/pdf/2401.07576","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2401.07576","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072159853","display_name":"Wannita Takerngsaksiri","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Takerngsaksiri, Wannita","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062616009","display_name":"Rujikorn Charakorn","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Charakorn, Rujikorn","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081449581","display_name":"Chakkrit Tantithamthavorn","orcid":"https://orcid.org/0000-0002-5516-9984"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tantithamthavorn, Chakkrit","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5017943466","display_name":"Yuan-Fang Li","orcid":"https://orcid.org/0000-0003-4651-2821"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yuan-Fang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5072159853"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"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":0.9997000098228455,"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":0.9997000098228455,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9994000196456909,"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/T10430","display_name":"Software Engineering Techniques and Practices","score":0.9987000226974487,"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/computer-science","display_name":"Computer science","score":0.8260458707809448},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.7570198774337769},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7414647340774536},{"id":"https://openalex.org/keywords/test-driven-development","display_name":"Test-driven development","score":0.6172159314155579},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.5353671908378601},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.524169921875},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5106146931648254},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.5004148483276367},{"id":"https://openalex.org/keywords/test-case","display_name":"Test case","score":0.48447370529174805},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4471222162246704},{"id":"https://openalex.org/keywords/code-coverage","display_name":"Code coverage","score":0.4400831460952759},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.424208402633667},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.33939129114151},{"id":"https://openalex.org/keywords/software-development","display_name":"Software development","score":0.2794959545135498},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.24991264939308167}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8260458707809448},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.7570198774337769},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7414647340774536},{"id":"https://openalex.org/C4478048","wikidata":"https://www.wikidata.org/wiki/Q950250","display_name":"Test-driven development","level":4,"score":0.6172159314155579},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.5353671908378601},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.524169921875},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5106146931648254},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.5004148483276367},{"id":"https://openalex.org/C128942645","wikidata":"https://www.wikidata.org/wiki/Q1568346","display_name":"Test case","level":3,"score":0.48447370529174805},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4471222162246704},{"id":"https://openalex.org/C53942775","wikidata":"https://www.wikidata.org/wiki/Q1211721","display_name":"Code coverage","level":3,"score":0.4400831460952759},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.424208402633667},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.33939129114151},{"id":"https://openalex.org/C529173508","wikidata":"https://www.wikidata.org/wiki/Q638608","display_name":"Software development","level":3,"score":0.2794959545135498},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.24991264939308167},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2401.07576","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2401.07576","pdf_url":"https://arxiv.org/pdf/2401.07576","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2401.07576","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2401.07576","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":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2401.07576","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2401.07576","pdf_url":"https://arxiv.org/pdf/2401.07576","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.550000011920929,"id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391009381.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2598672065","https://openalex.org/W1993817217","https://openalex.org/W3120610872","https://openalex.org/W1638297612","https://openalex.org/W2523911541","https://openalex.org/W87461448","https://openalex.org/W1494584744","https://openalex.org/W2131157060","https://openalex.org/W3188635326","https://openalex.org/W4313447549"],"abstract_inverted_index":{"Test-driven":[0],"development":[1,7],"(TDD)":[2],"is":[3,26,32,79],"a":[4,135,155,180],"widely-employed":[5],"software":[6],"practice":[8],"that":[9,105,139,173,198],"mandates":[10],"writing":[11,18,23],"test":[12,24,48,83,90,103,112,127,149],"cases":[13,25,104,150],"based":[14],"on":[15,163],"requirements":[16],"before":[17],"the":[19,27,65,110,119,164,170,214,219],"actual":[20,77],"code.":[21],"While":[22],"centerpiece":[28],"of":[29,221],"TDD,":[30,46,75],"it":[31],"time-consuming,":[33],"expensive,":[34],"and":[35,147,169,193],"often":[36],"shunned":[37],"by":[38,212],"developers.":[39],"To":[40],"address":[41],"these":[42],"issues":[43],"associated":[44],"with":[45,96,109,154],"automated":[47],"case":[49,91],"generation":[50,92,137],"approaches":[51,57,93,116],"have":[52],"recently":[53],"been":[54],"investigated.":[55],"Such":[56],"take":[58],"source":[59],"code":[60,78],"as":[61,76],"input,":[62],"but":[63],"not":[64,71],"requirements.":[66],"Therefore,":[67],"existing":[68],"work":[69],"does":[70],"fully":[72],"support":[73],"true":[74],"required":[80],"to":[81,101,122,184],"generate":[82,102,123,142],"cases.":[84,113,128],"In":[85,129],"addition,":[86],"current":[87],"deep":[88],"learning-based":[89],"are":[94,106],"trained":[95],"one":[97],"learning":[98,223],"objective,":[99],"i.e.,":[100],"exactly":[107],"matched":[108],"ground-truth":[111],"However,":[114],"such":[115],"may":[117],"limit":[118],"model's":[120],"ability":[121],"different":[124],"yet":[125],"correct":[126],"this":[130],"paper,":[131],"we":[132],"introduce":[133],"PyTester,":[134,179],"Text-to-Testcase":[136],"approach":[138,177],"can":[140],"automatically":[141],"syntactically":[143],"correct,":[144],"executable,":[145],"complete,":[146],"effective":[148],"while":[151],"being":[152],"aligned":[153],"given":[156],"natural":[157],"language":[158,182,188],"requirement.":[159],"We":[160],"evaluate":[161],"PyTester":[162],"public":[165],"APPS":[166],"benchmark":[167],"dataset,":[168],"results":[171],"show":[172],"our":[174],"Deep":[175],"RL":[176],"enables":[178],"small":[181,204],"model,":[183],"outperform":[185],"much":[186],"larger":[187],"models":[189],"like":[190],"GPT3.5,":[191],"StarCoder,":[192],"InCoder.":[194],"Our":[195],"findings":[196],"suggest":[197],"future":[199],"research":[200],"could":[201],"consider":[202],"improving":[203],"over":[205],"large":[206],"LMs":[207],"for":[208],"better":[209],"resource":[210],"efficiency":[211],"integrating":[213],"SE":[215],"domain":[216],"knowledge":[217],"into":[218],"design":[220],"reinforcement":[222],"architecture.":[224]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2024-01-19T00:00:00"}
