{"id":"https://openalex.org/W2006750785","doi":"https://doi.org/10.1109/snpd.2014.6888690","title":"A machine learning technique for predicting the productivity of practitioners from individually developed software projects","display_name":"A machine learning technique for predicting the productivity of practitioners from individually developed software projects","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W2006750785","doi":"https://doi.org/10.1109/snpd.2014.6888690","mag":"2006750785"},"language":"en","primary_location":{"id":"doi:10.1109/snpd.2014.6888690","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd.2014.6888690","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","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/A5018662615","display_name":"Cuauht\u00e9moc L\u00f3pez\u2010Mart\u00edn","orcid":"https://orcid.org/0000-0001-6172-9899"},"institutions":[{"id":"https://openalex.org/I193181351","display_name":"Universidad de Guadalajara","ror":"https://ror.org/043xj7k26","country_code":"MX","type":"education","lineage":["https://openalex.org/I193181351"]}],"countries":["MX"],"is_corresponding":true,"raw_author_name":"Cuauhtemoc Lopez-Martin","raw_affiliation_strings":["Information Systems Department CUCEA, Universidad de Guadalajara Guadalajara, Jalisco, Mexico","Inf. Syst. Dept. CUCEA, Univ. de Guadalajara Guadalajara, Jalisco, Mexico"],"affiliations":[{"raw_affiliation_string":"Information Systems Department CUCEA, Universidad de Guadalajara Guadalajara, Jalisco, Mexico","institution_ids":["https://openalex.org/I193181351"]},{"raw_affiliation_string":"Inf. Syst. Dept. CUCEA, Univ. de Guadalajara Guadalajara, Jalisco, Mexico","institution_ids":["https://openalex.org/I193181351"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064910390","display_name":"Arturo Chavoya","orcid":"https://orcid.org/0000-0003-0084-3932"},"institutions":[{"id":"https://openalex.org/I193181351","display_name":"Universidad de Guadalajara","ror":"https://ror.org/043xj7k26","country_code":"MX","type":"education","lineage":["https://openalex.org/I193181351"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Arturo Chavoya","raw_affiliation_strings":["Information Systems Department CUCEA, Universidad de Guadalajara Guadalajara, Jalisco, Mexico","Inf. Syst. Dept. CUCEA, Univ. de Guadalajara Guadalajara, Jalisco, Mexico"],"affiliations":[{"raw_affiliation_string":"Information Systems Department CUCEA, Universidad de Guadalajara Guadalajara, Jalisco, Mexico","institution_ids":["https://openalex.org/I193181351"]},{"raw_affiliation_string":"Inf. Syst. Dept. CUCEA, Univ. de Guadalajara Guadalajara, Jalisco, Mexico","institution_ids":["https://openalex.org/I193181351"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002524547","display_name":"Mar\u00eda Elena Meda-Campa\u00f1a","orcid":"https://orcid.org/0000-0001-8684-8296"},"institutions":[{"id":"https://openalex.org/I193181351","display_name":"Universidad de Guadalajara","ror":"https://ror.org/043xj7k26","country_code":"MX","type":"education","lineage":["https://openalex.org/I193181351"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Maria Elena Meda-Campana","raw_affiliation_strings":["Information Systems Department CUCEA, Universidad de Guadalajara Guadalajara, Jalisco, Mexico","Inf. Syst. Dept. CUCEA, Univ. de Guadalajara Guadalajara, Jalisco, Mexico"],"affiliations":[{"raw_affiliation_string":"Information Systems Department CUCEA, Universidad de Guadalajara Guadalajara, Jalisco, Mexico","institution_ids":["https://openalex.org/I193181351"]},{"raw_affiliation_string":"Inf. Syst. Dept. CUCEA, Univ. de Guadalajara Guadalajara, Jalisco, Mexico","institution_ids":["https://openalex.org/I193181351"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5018662615"],"corresponding_institution_ids":["https://openalex.org/I193181351"],"apc_list":null,"apc_paid":null,"fwci":1.5778,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.87481198,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9995999932289124,"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":0.9995999932289124,"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/T10430","display_name":"Software Engineering Techniques and Practices","score":0.9958000183105469,"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":0.9940999746322632,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6613079309463501},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6562958359718323},{"id":"https://openalex.org/keywords/productivity","display_name":"Productivity","score":0.5930477976799011},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5588875412940979},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.5527556538581848},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5352571606636047},{"id":"https://openalex.org/keywords/source-lines-of-code","display_name":"Source lines of code","score":0.5268258452415466},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5260845422744751},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5066233277320862},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.48211073875427246},{"id":"https://openalex.org/keywords/regression-testing","display_name":"Regression testing","score":0.4300047755241394},{"id":"https://openalex.org/keywords/software-development","display_name":"Software development","score":0.38432955741882324},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35784757137298584},{"id":"https://openalex.org/keywords/software-construction","display_name":"Software construction","score":0.1320277452468872}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6613079309463501},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6562958359718323},{"id":"https://openalex.org/C204983608","wikidata":"https://www.wikidata.org/wiki/Q2111958","display_name":"Productivity","level":2,"score":0.5930477976799011},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5588875412940979},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.5527556538581848},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5352571606636047},{"id":"https://openalex.org/C199519371","wikidata":"https://www.wikidata.org/wiki/Q942695","display_name":"Source lines of code","level":3,"score":0.5268258452415466},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5260845422744751},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5066233277320862},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.48211073875427246},{"id":"https://openalex.org/C161821725","wikidata":"https://www.wikidata.org/wiki/Q917415","display_name":"Regression testing","level":5,"score":0.4300047755241394},{"id":"https://openalex.org/C529173508","wikidata":"https://www.wikidata.org/wiki/Q638608","display_name":"Software development","level":3,"score":0.38432955741882324},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35784757137298584},{"id":"https://openalex.org/C186846655","wikidata":"https://www.wikidata.org/wiki/Q3398377","display_name":"Software construction","level":4,"score":0.1320277452468872},{"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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/snpd.2014.6888690","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd.2014.6888690","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.6299999952316284,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321739","display_name":"Consejo Nacional de Ciencia y Tecnolog\u00eda","ror":"https://ror.org/059ex5q34"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W117716889","https://openalex.org/W1522500515","https://openalex.org/W1977217383","https://openalex.org/W1994885765","https://openalex.org/W2063315020","https://openalex.org/W2068426139","https://openalex.org/W2073128029","https://openalex.org/W2079104416","https://openalex.org/W2103502342","https://openalex.org/W2104236502","https://openalex.org/W2149723649","https://openalex.org/W2162430279","https://openalex.org/W2163004671","https://openalex.org/W2227589632","https://openalex.org/W2487328426","https://openalex.org/W4210735789","https://openalex.org/W4213328286","https://openalex.org/W6689070502"],"related_works":["https://openalex.org/W4232229155","https://openalex.org/W643015529","https://openalex.org/W2045239961","https://openalex.org/W2162694379","https://openalex.org/W2186442870","https://openalex.org/W1560412976","https://openalex.org/W2951653635","https://openalex.org/W3190859260","https://openalex.org/W1935050324","https://openalex.org/W4293580152"],"abstract_inverted_index":{"Context:":[0],"Productivity":[1,32],"management":[2],"of":[3,15,66,72,91,128,139,163,170,182,189,203,211,230,237,245],"software":[4,67,92,99,107],"developers":[5],"is":[6,75],"a":[7,52,73,78,126,153,158,171,196],"challenge":[8],"in":[9,28,135],"Information":[10],"and":[11,24,46,114,195,234,241],"Communication":[12],"Technology.":[13],"Predictions":[14],"productivity":[16,65,90,229],"can":[17],"be":[18,224],"useful":[19],"to":[20,25,192],"determine":[21],"corrective":[22],"actions":[23],"assist":[26],"managers":[27],"evaluating":[29,179],"improvement":[30],"alternatives.":[31],"prediction":[33],"models":[34,85,185],"have":[35,95],"been":[36],"based":[37,151],"on":[38],"statistical":[39,41,79,198],"regressions,":[40],"time":[42],"series,":[43],"fuzzy":[44],"logic,":[45],"machine":[47,53],"learning.":[48],"Goal:":[49],"To":[50],"propose":[51],"learning":[54],"model":[55,81,174,214],"termed":[56],"general":[57],"regression":[58,80,173],"neural":[59],"network":[60],"(GRNN)":[61],"for":[62,88,121,143,178,226],"predicting":[63,89,227],"the":[64,111,123,136,145,164,180,187,193,216,228],"practitioners.":[68],"Hypothesis:":[69],"Prediction":[70,201],"accuracy":[71,162,181,202],"GRNN":[74,165,205,222],"better":[76,208],"than":[77,209],"when":[82,232],"these":[83,183],"two":[84,184],"are":[86,247],"applied":[87,225],"practitioners":[93,118,134,231,246],"who":[94],"individually":[96],"developed":[97,109,131,150],"their":[98],"projects.":[100],"Method:":[101],"A":[102],"sample":[103,127],"obtained":[104],"from":[105],"396":[106],"projects":[108,130,148],"between":[110],"years":[112],"2005":[113],"2011":[115],"by":[116,132],"99":[117],"was":[119,141,166,206],"used":[120,142,248],"training":[122],"models,":[124],"whereas":[125],"60":[129],"15":[133],"first":[137],"months":[138],"2012":[140],"testing":[144],"models.":[146],"All":[147],"were":[149,186],"upon":[152],"disciplined":[154],"development":[155],"process":[156],"within":[157],"controlled":[159],"environment.":[160],"The":[161,176],"compared":[167],"against":[168],"that":[169,210],"multiple":[172],"(MLR).":[175],"criteria":[177],"Magnitude":[188],"Error":[190],"Relative":[191],"estimate":[194],"t-paired":[197],"test.":[199],"Results:":[200],"an":[204,212],"statistically":[207],"MLR":[213],"at":[215],"99%":[217],"confidence":[218],"level.":[219],"Conclusion:":[220],"An":[221],"could":[223],"New":[233],"Changed":[235],"lines":[236],"code,":[238,240],"reused":[239],"programming":[242],"language":[243],"experience":[244],"as":[249],"independent":[250],"variables.":[251]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}