{"id":"https://openalex.org/W7127103383","doi":"https://doi.org/10.1145/3787256.3787263","title":"Improving Training Data Quality for Automated Test Case Generation Using Machine Learning and Its Evaluation","display_name":"Improving Training Data Quality for Automated Test Case Generation Using Machine Learning and Its Evaluation","publication_year":2025,"publication_date":"2025-11-21","ids":{"openalex":"https://openalex.org/W7127103383","doi":"https://doi.org/10.1145/3787256.3787263"},"language":null,"primary_location":{"id":"doi:10.1145/3787256.3787263","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3787256.3787263","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 8th International Conference on Computational Intelligence and Intelligent Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3787256.3787263","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124796693","display_name":"Taiga Ishinari","orcid":null},"institutions":[{"id":"https://openalex.org/I30181195","display_name":"Ohu University","ror":"https://ror.org/01fe6f215","country_code":"JP","type":"education","lineage":["https://openalex.org/I30181195"]},{"id":"https://openalex.org/I4210098241","display_name":"Fukushima Prefectural Asaka High School","ror":"https://ror.org/013ch2r08","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210098241"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Taiga Ishinari","raw_affiliation_strings":["Graduate Schools of Engineering, Nihon University, Koriyama, Fukushima, Japan"],"raw_orcid":"https://orcid.org/0009-0008-2442-6678","affiliations":[{"raw_affiliation_string":"Graduate Schools of Engineering, Nihon University, Koriyama, Fukushima, Japan","institution_ids":["https://openalex.org/I4210098241","https://openalex.org/I30181195"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kiyoshi Ueda","orcid":"https://orcid.org/0009-0000-6505-3400"},"institutions":[{"id":"https://openalex.org/I104946051","display_name":"Nihon University","ror":"https://ror.org/05jk51a88","country_code":"JP","type":"education","lineage":["https://openalex.org/I104946051"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kiyoshi Ueda","raw_affiliation_strings":["College of Engineering, Nihon University, Koriyama, Fukushima, Japan"],"raw_orcid":"https://orcid.org/0009-0000-6505-3400","affiliations":[{"raw_affiliation_string":"College of Engineering, Nihon University, Koriyama, Fukushima, Japan","institution_ids":["https://openalex.org/I104946051"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124846967","display_name":"Yuki Shimizu","orcid":null},"institutions":[{"id":"https://openalex.org/I30181195","display_name":"Ohu University","ror":"https://ror.org/01fe6f215","country_code":"JP","type":"education","lineage":["https://openalex.org/I30181195"]},{"id":"https://openalex.org/I4210098241","display_name":"Fukushima Prefectural Asaka High School","ror":"https://ror.org/013ch2r08","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210098241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuki Shimizu","raw_affiliation_strings":["Graduate Schools of Engineering, Nihon University, Koriyama, Fukushima, Japan"],"raw_orcid":"https://orcid.org/0009-0008-3865-791X","affiliations":[{"raw_affiliation_string":"Graduate Schools of Engineering, Nihon University, Koriyama, Fukushima, Japan","institution_ids":["https://openalex.org/I4210098241","https://openalex.org/I30181195"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5124796693"],"corresponding_institution_ids":["https://openalex.org/I30181195","https://openalex.org/I4210098241"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.83362338,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"44","last_page":"51"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.46720001101493835,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.46720001101493835,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.18050000071525574,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.07339999824762344,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5902000069618225},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.5515999794006348},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4964999854564667},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.4560000002384186},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4406000077724457},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.3659999966621399}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7620000243186951},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6995000243186951},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5902000069618225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5591999888420105},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.5515999794006348},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4964999854564667},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.4560000002384186},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4406000077724457},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4108000099658966},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.3659999966621399},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.36550000309944153},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C128942645","wikidata":"https://www.wikidata.org/wiki/Q1568346","display_name":"Test case","level":3,"score":0.31060001254081726}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3787256.3787263","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3787256.3787263","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 8th International Conference on Computational Intelligence and Intelligent Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3787256.3787263","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3787256.3787263","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 8th International Conference on Computational Intelligence and Intelligent Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1504779339","https://openalex.org/W2091879664","https://openalex.org/W2509076037","https://openalex.org/W2995539992","https://openalex.org/W2995607718","https://openalex.org/W2998823187","https://openalex.org/W3021389383","https://openalex.org/W3032170634","https://openalex.org/W3131256561","https://openalex.org/W3161913203","https://openalex.org/W4237492309","https://openalex.org/W4388792466","https://openalex.org/W4392248313","https://openalex.org/W4402629335","https://openalex.org/W4414272335"],"related_works":[],"abstract_inverted_index":{"We":[0,119],"aim":[1],"to":[2,65,90],"enhance":[3],"the":[4,41,96,108,122,129,155,162,165],"accuracy":[5,63],"of":[6,9,43,77,107,124,164],"automatic":[7],"structuring":[8],"requirement":[10,86,93,144],"specifications":[11,145],"and":[12,35,99,137],"automated":[13,114,170],"test":[14,91,115,171],"case":[15,116,172],"generation":[16,58,117],"by":[17,128],"leveraging":[18],"machine":[19],"learning":[20],"techniques.":[21],"Training":[22],"with":[23,149],"large":[24],"datasets":[25],"often":[26],"faces":[27],"challenges":[28],"such":[29],"as":[30],"overfitting,":[31],"extended":[32],"training":[33,44,56,78,97,125,147,157],"time,":[34],"high":[36],"computational":[37],"cost.":[38],"Thus,":[39],"improving":[40,169],"quality":[42,123],"data":[45,57,79,92,126,148],"is":[46,80,111],"a":[47,55,74],"critical":[48],"issue.":[49],"In":[50],"this":[51],"study,":[52],"we":[53],"propose":[54],"method":[59,110,167],"that":[60,66,142],"can":[61],"achieve":[62],"comparable":[64],"obtained":[67],"from":[68],"large-scale":[69],"datasets,":[70],"even":[71],"when":[72],"only":[73],"limited":[75],"amount":[76],"available.":[81],"Our":[82],"approach":[83],"incorporates":[84],"structured":[85],"specification":[87],"documents,":[88],"similar":[89],"specifications,":[94],"into":[95],"set,":[98],"applies":[100],"four":[101,130],"different":[102],"vectorization":[103],"procedures.":[104],"The":[105,139],"effectiveness":[106,163],"proposed":[109,166],"validated":[112],"through":[113],"experiments.":[118],"quantitatively":[120],"evaluate":[121],"produced":[127],"procedures":[131],"using":[132],"two":[133],"least-squares-based":[134],"approximations:":[135],"quadratic":[136],"logarithmic.":[138],"results":[140],"demonstrate":[141],"selecting":[143],"for":[146,168],"Latent":[150],"Dirichlet":[151],"Allocation":[152],"(LDA)":[153],"yields":[154],"highest-quality":[156],"data.":[158],"These":[159],"findings":[160],"confirm":[161],"generation.":[173]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2026-02-03T00:00:00"}