{"id":"https://openalex.org/W4308627400","doi":"https://doi.org/10.1145/3558489.3559070","title":"Predicting build outcomes in continuous integration using textual analysis of source code commits","display_name":"Predicting build outcomes in continuous integration using textual analysis of source code commits","publication_year":2022,"publication_date":"2022-11-07","ids":{"openalex":"https://openalex.org/W4308627400","doi":"https://doi.org/10.1145/3558489.3559070"},"language":"en","primary_location":{"id":"doi:10.1145/3558489.3559070","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3558489.3559070","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3558489.3559070","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 18th International Conference on Predictive Models and Data Analytics in Software Engineering","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3558489.3559070","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031241279","display_name":"Khaled Al-Sabbagh","orcid":"https://orcid.org/0000-0003-2571-5099"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]},{"id":"https://openalex.org/I881427289","display_name":"University of Gothenburg","ror":"https://ror.org/01tm6cn81","country_code":"SE","type":"education","lineage":["https://openalex.org/I881427289"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Khaled Al-Sabbagh","raw_affiliation_strings":["Chalmers University of Technology, Sweden / University of Gothenburg, Sweden"],"affiliations":[{"raw_affiliation_string":"Chalmers University of Technology, Sweden / University of Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912","https://openalex.org/I881427289"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074020697","display_name":"Miroslaw Staron","orcid":"https://orcid.org/0000-0002-9052-0864"},"institutions":[{"id":"https://openalex.org/I881427289","display_name":"University of Gothenburg","ror":"https://ror.org/01tm6cn81","country_code":"SE","type":"education","lineage":["https://openalex.org/I881427289"]},{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Miroslaw Staron","raw_affiliation_strings":["Chalmers University of Technology, Sweden / University of Gothenburg, Sweden"],"affiliations":[{"raw_affiliation_string":"Chalmers University of Technology, Sweden / University of Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912","https://openalex.org/I881427289"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017449010","display_name":"Regina Hebig","orcid":"https://orcid.org/0000-0002-1459-2081"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]},{"id":"https://openalex.org/I881427289","display_name":"University of Gothenburg","ror":"https://ror.org/01tm6cn81","country_code":"SE","type":"education","lineage":["https://openalex.org/I881427289"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Regina Hebig","raw_affiliation_strings":["Chalmers University of Technology, Sweden / University of Gothenburg, Sweden"],"affiliations":[{"raw_affiliation_string":"Chalmers University of Technology, Sweden / University of Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912","https://openalex.org/I881427289"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5031241279"],"corresponding_institution_ids":["https://openalex.org/I66862912","https://openalex.org/I881427289"],"apc_list":null,"apc_paid":null,"fwci":1.515,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.86687997,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"42","last_page":"51"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":1.0,"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":1.0,"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/T12423","display_name":"Software Reliability and Analysis Research","score":0.9959999918937683,"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":0.9886000156402588,"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":0.7353098392486572},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5869659185409546},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.5860879421234131},{"id":"https://openalex.org/keywords/software-metric","display_name":"Software metric","score":0.5555551052093506},{"id":"https://openalex.org/keywords/java","display_name":"Java","score":0.554888129234314},{"id":"https://openalex.org/keywords/source-lines-of-code","display_name":"Source lines of code","score":0.5324206352233887},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.5204901099205017},{"id":"https://openalex.org/keywords/software-quality","display_name":"Software quality","score":0.5120170712471008},{"id":"https://openalex.org/keywords/product-metric","display_name":"Product metric","score":0.446217805147171},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4365622401237488},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4233022630214691},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4059509336948395},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.40236666798591614},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3828210234642029},{"id":"https://openalex.org/keywords/software-development","display_name":"Software development","score":0.3495956063270569},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.263949990272522},{"id":"https://openalex.org/keywords/metric-space","display_name":"Metric space","score":0.13968104124069214},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08623209595680237},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07600757479667664}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7353098392486572},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5869659185409546},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.5860879421234131},{"id":"https://openalex.org/C82214349","wikidata":"https://www.wikidata.org/wiki/Q657339","display_name":"Software metric","level":5,"score":0.5555551052093506},{"id":"https://openalex.org/C548217200","wikidata":"https://www.wikidata.org/wiki/Q251","display_name":"Java","level":2,"score":0.554888129234314},{"id":"https://openalex.org/C199519371","wikidata":"https://www.wikidata.org/wiki/Q942695","display_name":"Source lines of code","level":3,"score":0.5324206352233887},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.5204901099205017},{"id":"https://openalex.org/C117447612","wikidata":"https://www.wikidata.org/wiki/Q1412670","display_name":"Software quality","level":4,"score":0.5120170712471008},{"id":"https://openalex.org/C154497576","wikidata":"https://www.wikidata.org/wiki/Q7247777","display_name":"Product metric","level":3,"score":0.446217805147171},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4365622401237488},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4233022630214691},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4059509336948395},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.40236666798591614},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3828210234642029},{"id":"https://openalex.org/C529173508","wikidata":"https://www.wikidata.org/wiki/Q638608","display_name":"Software development","level":3,"score":0.3495956063270569},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.263949990272522},{"id":"https://openalex.org/C198043062","wikidata":"https://www.wikidata.org/wiki/Q180953","display_name":"Metric space","level":2,"score":0.13968104124069214},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08623209595680237},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07600757479667664},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3558489.3559070","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3558489.3559070","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3558489.3559070","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 18th International Conference on Predictive Models and Data Analytics in Software Engineering","raw_type":"proceedings-article"},{"id":"pmh:oai:research.chalmers.se:533607","is_oa":false,"landing_page_url":"https://research.chalmers.se/en/publication/533607","pdf_url":null,"source":{"id":"https://openalex.org/S4306402469","display_name":"Chalmers Research (Chalmers University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66862912","host_organization_name":"Chalmers University of Technology","host_organization_lineage":["https://openalex.org/I66862912"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"doi:10.1145/3558489.3559070","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3558489.3559070","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3558489.3559070","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 18th International Conference on Predictive Models and Data Analytics in Software Engineering","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4308627400.pdf","grobid_xml":"https://content.openalex.org/works/W4308627400.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W1965854491","https://openalex.org/W1993220166","https://openalex.org/W2161538570","https://openalex.org/W2601606535","https://openalex.org/W2703757306","https://openalex.org/W2726948491","https://openalex.org/W2727682072","https://openalex.org/W2732522303","https://openalex.org/W2745000922","https://openalex.org/W2772064075","https://openalex.org/W2798183573","https://openalex.org/W3009290003","https://openalex.org/W3093849270","https://openalex.org/W4211173503","https://openalex.org/W4229772528"],"related_works":["https://openalex.org/W2078744341","https://openalex.org/W2159730313","https://openalex.org/W2968707180","https://openalex.org/W2975512365","https://openalex.org/W3205493779","https://openalex.org/W3023494354","https://openalex.org/W2036609589","https://openalex.org/W4376606579","https://openalex.org/W2172691564","https://openalex.org/W2356036115"],"abstract_inverted_index":{"Machine":[0],"learning":[1],"has":[2],"been":[3],"increasingly":[4],"used":[5],"to":[6,18,32,47,89,112,132],"solve":[7],"various":[8],"software":[9,53,81,123,143],"engineering":[10],"tasks.":[11],"One":[12],"example":[13],"of":[14,22,43,51,73,98,102,165,181],"its":[15],"usage":[16],"is":[17,30,46,176],"predict":[19,33],"the":[20,49,71,106,119,141,147,154,169,173],"outcome":[21,61],"builds":[23],"in":[24,55],"continuous":[25],"integration,":[26],"where":[27],"a":[28,57,74,134,177],"classifier":[29,58],"built":[31],"whether":[34],"new":[35],"code":[36],"commits":[37],"will":[38],"successfully":[39],"compile.":[40],"The":[41],"aim":[42],"this":[44],"study":[45],"investigate":[48],"effectiveness":[50,72],"fifteen":[52],"metrics":[54,82,129,161],"building":[56],"for":[59,109,118,140,153,168],"build":[60,85,166],"prediction.":[62],"Particularly,":[63],"we":[64,69],"implemented":[65],"an":[66,95],"experiment":[67],"wherein":[68],"compared":[70,111],"line-level":[75,107,148,174],"metric":[76,108,149,175],"and":[77,100,115],"fourteen":[78],"other":[79],"traditional":[80,122],"on":[83],"49,040":[84],"records":[86],"that":[87,159],"belong":[88],"117":[90],"Java":[91],"projects.":[92],"We":[93,157],"achieved":[94],"average":[96],"precision":[97,114],"91%":[99],"recall":[101,117],"80%":[103],"when":[104],"using":[105,127],"training,":[110],"90%":[113],"76%":[116],"next":[120],"best":[121,142],"metric.":[124],"In":[125],"contrast,":[126],"file-level":[128,160],"was":[130],"found":[131],"yield":[133],"higher":[135],"predictive":[136],"quality":[137],"(average":[138,150],"MCC":[139],"metric=":[144],"68%)":[145],"than":[146],"MCC=":[151],"16%)":[152],"failed":[155,170],"builds.":[156,183],"conclude":[158],"are":[162],"better":[163,179],"predictors":[164],"outcomes":[167],"builds,":[171],"whereas":[172],"slightly":[178],"predictor":[180],"passed":[182]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
