{"id":"https://openalex.org/W3094700291","doi":"https://doi.org/10.1145/3416505.3423563","title":"Singling the odd ones out: a novelty detection approach to find defects in infrastructure-as-code","display_name":"Singling the odd ones out: a novelty detection approach to find defects in infrastructure-as-code","publication_year":2020,"publication_date":"2020-11-06","ids":{"openalex":"https://openalex.org/W3094700291","doi":"https://doi.org/10.1145/3416505.3423563","mag":"3094700291"},"language":"en","primary_location":{"id":"doi:10.1145/3416505.3423563","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3416505.3423563","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th ACM SIGSOFT International Workshop on Machine-Learning Techniques for Software-Quality Evaluation","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077406242","display_name":"Stefano Dalla Palma","orcid":"https://orcid.org/0000-0002-5611-0546"},"institutions":[{"id":"https://openalex.org/I193700539","display_name":"Tilburg University","ror":"https://ror.org/04b8v1s79","country_code":"NL","type":"education","lineage":["https://openalex.org/I193700539"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Stefano Dalla Palma","raw_affiliation_strings":["Tilburg University, Netherlands / JADS, Netherlands"],"affiliations":[{"raw_affiliation_string":"Tilburg University, Netherlands / JADS, Netherlands","institution_ids":["https://openalex.org/I193700539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034361899","display_name":"Majid Mohammadi","orcid":"https://orcid.org/0000-0002-7131-8724"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Majid Mohammadi","raw_affiliation_strings":["Eindhoven University of Technology, Netherlands / JADS, Netherlands"],"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology, Netherlands / JADS, Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072127726","display_name":"Dario Di Nucci","orcid":"https://orcid.org/0000-0002-3861-1902"},"institutions":[{"id":"https://openalex.org/I193700539","display_name":"Tilburg University","ror":"https://ror.org/04b8v1s79","country_code":"NL","type":"education","lineage":["https://openalex.org/I193700539"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Dario Di Nucci","raw_affiliation_strings":["Tilburg University, Netherlands / JADS, Netherlands"],"affiliations":[{"raw_affiliation_string":"Tilburg University, Netherlands / JADS, Netherlands","institution_ids":["https://openalex.org/I193700539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000349425","display_name":"Damian A. Tamburri","orcid":"https://orcid.org/0000-0003-1230-8961"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Damian A. Tamburri","raw_affiliation_strings":["Eindhoven University of Technology, Netherlands / JADS, Netherlands"],"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology, Netherlands / JADS, Netherlands","institution_ids":["https://openalex.org/I83019370"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5077406242"],"corresponding_institution_ids":["https://openalex.org/I193700539"],"apc_list":null,"apc_paid":null,"fwci":0.5338,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.75628842,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"31","last_page":"36"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9961000084877014,"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":0.9961000084877014,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9952999949455261,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9861999750137329,"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/novelty","display_name":"Novelty","score":0.8434728384017944},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7914358377456665},{"id":"https://openalex.org/keywords/novelty-detection","display_name":"Novelty detection","score":0.6387289762496948},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.626000702381134},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6185502409934998},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.5849905014038086},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5802363753318787},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.490550696849823},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.45147034525871277},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34349697828292847},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.16305217146873474},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08930525183677673}],"concepts":[{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.8434728384017944},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7914358377456665},{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.6387289762496948},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.626000702381134},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6185502409934998},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.5849905014038086},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5802363753318787},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.490550696849823},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.45147034525871277},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34349697828292847},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.16305217146873474},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08930525183677673},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3416505.3423563","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3416505.3423563","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th ACM SIGSOFT International Workshop on Machine-Learning Techniques for Software-Quality Evaluation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6299999952316284}],"awards":[{"id":"https://openalex.org/G5670458902","display_name":null,"funder_award_id":"825040","funder_id":"https://openalex.org/F4320338335","funder_display_name":"H2020 European Research Council"}],"funders":[{"id":"https://openalex.org/F4320338335","display_name":"H2020 European Research Council","ror":"https://ror.org/0472cxd90"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W73403477","https://openalex.org/W2095345875","https://openalex.org/W2115627867","https://openalex.org/W2161948305","https://openalex.org/W2402800985","https://openalex.org/W2559885217","https://openalex.org/W2807298173","https://openalex.org/W2897961188","https://openalex.org/W2955656327","https://openalex.org/W2963995913","https://openalex.org/W2993710525","https://openalex.org/W2999309192","https://openalex.org/W3041762618","https://openalex.org/W4238083912","https://openalex.org/W4393497451"],"related_works":["https://openalex.org/W2064636555","https://openalex.org/W2585503716","https://openalex.org/W1939982668","https://openalex.org/W2105014086","https://openalex.org/W2076090200","https://openalex.org/W3025682415","https://openalex.org/W2081173909","https://openalex.org/W4389009659","https://openalex.org/W198251434","https://openalex.org/W4312933423"],"abstract_inverted_index":{"Infrastructure-as-Code":[0],"(IaC)":[1],"is":[2,7,123],"increasingly":[3],"adopted.":[4],"However,":[5],"little":[6,125],"known":[8],"about":[9],"how":[10],"to":[11,24,62,127,172,178],"best":[12],"maintain":[13],"and":[14,39,52,60,80,90,92,167,174,192],"evolve":[15],"it.":[16],"Previous":[17],"studies":[18],"focused":[19],"on":[20,135],"defining":[21],"Machine-Learning":[22],"models":[23,103],"predict":[25],"defect-prone":[26],"blueprints":[27],"using":[28,77,106],"supervised":[29],"binary":[30,100],"classification.":[31],"This":[32],"class":[33],"of":[34,84,120,140,149,165],"techniques":[35,157],"uses":[36],"both":[37],"defective":[38,51,110,121,128,150],"non-defective":[40,53,108],"instances":[41],"in":[42,189],"the":[43,47,56,70,82,118,186],"training":[44,57],"phase.":[45],"Furthermore,":[46],"high":[48,163],"imbalance":[49],"between":[50],"samples":[54,122],"makes":[55],"more":[58],"difficult":[59],"leads":[61],"unreliable":[63],"classifiers.":[64],"In":[65],"this":[66,202],"work,":[67],"we":[68],"tackle":[69],"defect-prediction":[71],"problem":[72],"from":[73],"a":[74,97,162,195],"different":[75],"perspective":[76],"novelty":[78,116,155],"detection":[79,156,191],"evaluate":[81],"performance":[83,95],"three":[85],"techniques,":[86],"namely":[87],"OneClassSVM,":[88],"LocalOutlierFactor,":[89],"IsolationForest,":[91],"compare":[93],"their":[94],"with":[96,161,201],"baseline":[98],"RandomForest":[99],"classifier.":[101],"Such":[102],"are":[104,113],"trained":[105],"only":[107,146],"samples:":[109],"data":[111],"points":[112],"treated":[114],"as":[115],"because":[117],"number":[119],"too":[124],"compared":[126],"ones.":[129],"We":[130,152,180],"conduct":[131],"an":[132,136,169,175],"empirical":[133],"study":[134],"extremely-imbalanced":[137],"dataset":[138],"consisting":[139],"85":[141],"real-world":[142],"Ansible":[143],"projects":[144],"containing":[145],"small":[147],"amounts":[148],"instances.":[151],"found":[153],"that":[154],"can":[158,184],"recognize":[159],"defects":[160],"level":[164],"precision":[166],"recall,":[168],"AUC-PR":[170],"up":[171,177],"0.86,":[173],"MCC":[176],"0.31.":[179],"deem":[181],"our":[182],"results":[183],"influence":[185],"current":[187],"trends":[188],"defect":[190],"put":[193],"forward":[194],"new":[196],"research":[197],"path":[198],"toward":[199],"dealing":[200],"problem.":[203]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
