{"id":"https://openalex.org/W2010741406","doi":"https://doi.org/10.1109/icsm.2010.5609732","title":"Using multivariate time series and association rules to detect logical change coupling: An empirical study","display_name":"Using multivariate time series and association rules to detect logical change coupling: An empirical study","publication_year":2010,"publication_date":"2010-09-01","ids":{"openalex":"https://openalex.org/W2010741406","doi":"https://doi.org/10.1109/icsm.2010.5609732","mag":"2010741406"},"language":"en","primary_location":{"id":"doi:10.1109/icsm.2010.5609732","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsm.2010.5609732","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Software Maintenance","raw_type":"proceedings-article"},"type":"conference-paper","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/A5006915371","display_name":"Gerardo Canfora","orcid":"https://orcid.org/0000-0003-0049-1279"},"institutions":[{"id":"https://openalex.org/I16337185","display_name":"University of Sannio","ror":"https://ror.org/04vc81p87","country_code":"IT","type":"education","lineage":["https://openalex.org/I16337185"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Gerardo Canfora","raw_affiliation_strings":["Department of Engineering RCOST, University of Sannio, Italy","Dept. of Engineering-RCOST, University of Sannio, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering RCOST, University of Sannio, Italy","institution_ids":["https://openalex.org/I16337185"]},{"raw_affiliation_string":"Dept. of Engineering-RCOST, University of Sannio, Italy","institution_ids":["https://openalex.org/I16337185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085527072","display_name":"Michele Ceccarelli","orcid":"https://orcid.org/0000-0002-4702-6617"},"institutions":[{"id":"https://openalex.org/I16337185","display_name":"University of Sannio","ror":"https://ror.org/04vc81p87","country_code":"IT","type":"education","lineage":["https://openalex.org/I16337185"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Michele Ceccarelli","raw_affiliation_strings":["Department of Biological and Environmental Studies, University of Sannio, Italy","Dept. of Biological and Environmental Studies, University of Sannio, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biological and Environmental Studies, University of Sannio, Italy","institution_ids":["https://openalex.org/I16337185"]},{"raw_affiliation_string":"Dept. of Biological and Environmental Studies, University of Sannio, Italy","institution_ids":["https://openalex.org/I16337185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025973233","display_name":"Luigi Cerulo","orcid":"https://orcid.org/0000-0001-8342-3487"},"institutions":[{"id":"https://openalex.org/I16337185","display_name":"University of Sannio","ror":"https://ror.org/04vc81p87","country_code":"IT","type":"education","lineage":["https://openalex.org/I16337185"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luigi Cerulo","raw_affiliation_strings":["Department of Biological and Environmental Studies, University of Sannio, Italy","Dept. of Biological and Environmental Studies, University of Sannio, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biological and Environmental Studies, University of Sannio, Italy","institution_ids":["https://openalex.org/I16337185"]},{"raw_affiliation_string":"Dept. of Biological and Environmental Studies, University of Sannio, Italy","institution_ids":["https://openalex.org/I16337185"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025099559","display_name":"Massimiliano Di Penta","orcid":"https://orcid.org/0000-0002-0340-9747"},"institutions":[{"id":"https://openalex.org/I16337185","display_name":"University of Sannio","ror":"https://ror.org/04vc81p87","country_code":"IT","type":"education","lineage":["https://openalex.org/I16337185"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Massimiliano Di Penta","raw_affiliation_strings":["Department of Engineering RCOST, University of Sannio, Italy","Dept. of Engineering-RCOST, University of Sannio, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering RCOST, University of Sannio, Italy","institution_ids":["https://openalex.org/I16337185"]},{"raw_affiliation_string":"Dept. of Engineering-RCOST, University of Sannio, Italy","institution_ids":["https://openalex.org/I16337185"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I16337185"],"apc_list":null,"apc_paid":null,"fwci":5.0329,"has_fulltext":false,"cited_by_count":65,"citation_normalized_percentile":{"value":0.9612919,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9940000176429749,"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":0.9940000176429749,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9484999775886536,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9247999787330627,"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/granger-causality","display_name":"Granger causality","score":0.823685884475708},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.722224235534668},{"id":"https://openalex.org/keywords/artifact","display_name":"Artifact (error)","score":0.7016855478286743},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6567894220352173},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.5840103030204773},{"id":"https://openalex.org/keywords/association","display_name":"Association (psychology)","score":0.5812722444534302},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5538203716278076},{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.553661048412323},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4717743396759033},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42865097522735596},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4276137948036194},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.4186720848083496},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41150227189064026},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.41045716404914856},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33424195647239685},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2159920036792755},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19296535849571228},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.12530618906021118},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07440534234046936}],"concepts":[{"id":"https://openalex.org/C129824826","wikidata":"https://www.wikidata.org/wiki/Q2630107","display_name":"Granger causality","level":2,"score":0.823685884475708},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.722224235534668},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.7016855478286743},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6567894220352173},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.5840103030204773},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.5812722444534302},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5538203716278076},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.553661048412323},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4717743396759033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42865097522735596},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4276137948036194},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.4186720848083496},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41150227189064026},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.41045716404914856},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33424195647239685},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2159920036792755},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19296535849571228},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.12530618906021118},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07440534234046936},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsm.2010.5609732","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsm.2010.5609732","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Software Maintenance","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1528580914","https://openalex.org/W1533432827","https://openalex.org/W1548254758","https://openalex.org/W1677598599","https://openalex.org/W1981547652","https://openalex.org/W2009543464","https://openalex.org/W2022313601","https://openalex.org/W2044503966","https://openalex.org/W2070948110","https://openalex.org/W2078882461","https://openalex.org/W2097608484","https://openalex.org/W2099358823","https://openalex.org/W2100849134","https://openalex.org/W2101567517","https://openalex.org/W2104830231","https://openalex.org/W2116303933","https://openalex.org/W2116574572","https://openalex.org/W2116759993","https://openalex.org/W2119070456","https://openalex.org/W2133961160","https://openalex.org/W2141558501","https://openalex.org/W2152096275","https://openalex.org/W2166559705","https://openalex.org/W2178225550","https://openalex.org/W2184389790","https://openalex.org/W2495580237","https://openalex.org/W3146166473","https://openalex.org/W4229861793","https://openalex.org/W4233240690","https://openalex.org/W4238127296","https://openalex.org/W4241115065"],"related_works":["https://openalex.org/W52840052","https://openalex.org/W3162837891","https://openalex.org/W1687852313","https://openalex.org/W3029243869","https://openalex.org/W2502336004","https://openalex.org/W2035792466","https://openalex.org/W2977645287","https://openalex.org/W4251418261","https://openalex.org/W1972675643","https://openalex.org/W2154758532"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"techniques":[3],"based":[4],"on":[5,76,86,96],"association":[6,24,120,130],"rules":[7,25,131],"discovery":[8],"have":[9],"been":[10],"extensively":[11],"used":[12],"to":[13,33,70,83,111,119,137],"determine":[14,71],"change-coupling":[15],"relations":[16,37],"between":[17,38],"artifacts":[18,39],"that":[19,105],"often":[20],"changed":[21],"together.":[22],"Although":[23],"worked":[26],"well":[27],"in":[28,41,62],"many":[29],"cases,":[30],"they":[31],"fail":[32],"capture":[34],"logical":[35],"coupling":[36],"modified":[40],"subsequent":[42],"change":[43,74,116],"sets.":[44],"To":[45],"overcome":[46],"such":[47],"a":[48,73,77,113,123,139],"limitation,":[49],"we":[50],"propose":[51],"the":[52,64,143],"use":[53,65],"of":[54,66,91,115],"multivariate":[55],"time":[56],"series":[57],"analysis":[58],"and":[59,61,99,122,132],"forecasting,":[60],"particular":[63],"Granger":[67,106,133],"causality":[68,107,134],"test,":[69],"whether":[72],"occurred":[75,85],"software":[78],"artifact":[79],"was":[80],"consequentially":[81],"related":[82],"changes":[84],"some":[87],"other":[88],"artifacts.":[89],"Results":[90],"an":[92],"empirical":[93],"study":[94],"performed":[95],"four":[97],"Java":[98],"C":[100],"open":[101],"source":[102],"systems":[103],"show":[104],"test":[108],"is":[109,135],"able":[110,136],"provide":[112],"set":[114],"couplings":[117],"complementary":[118],"rules,":[121],"hybrid":[124],"recommender":[125],"built":[126],"combining":[127],"recommendations":[128],"from":[129],"achieve":[138],"higher":[140],"recall":[141],"than":[142],"two":[144],"single":[145],"techniques.":[146]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":10},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":8},{"year":2012,"cited_by_count":9}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}