Empirical project monitor A tool for mining multiple project
时间:2025-04-02
时间:2025-04-02
Project management for effective software process improvement must be achieved based on quantitative data. However, because data collection for measurement requires high costs and collaboration with developers, it is difficult to collect coherent, quantita
EmpiricalProjectMonitor:AToolforMiningMultipleProjectData
MasaoOhira ,ReishiYokomori ,MakotoSakai ,Ken-ichiMatsumoto ,KatsuroInoue ,KojiTorii
NaraInstituteofScienceandTechnology
ohira@empirical.jp,{matumoto,torii}@is.aist-nara.ac.jp
GraduateSchoolofInformationScienceandTechnology,OsakaUniversity
{yokomori,inoue}@ist.osaka-u.ac.jp
SRAKeyTechnologyLaboratory,Inc.
sakai@sra.co.jp
Abstract
Projectmanagementforeffectivesoftwareprocessim-provementmustbeachievedbasedonquantitativedata.However,becausedatacollectionformeasurementrequireshighcostsandcollaborationwithdevelopers,itisdif culttocollectcoherent,quantitativedatacontinuouslyandtoutilizethedataforpracticingsoftwareprocessimprove-ment.Inthispaper,wedescribeEmpiricalProjectMoni-tor(EPM)whichautomaticallycollectsandmeasuresdatafromthreekindsofrepositoriesinwidelyusedsoftwaredevelopmentsupportsystemssuchascon gurationman-agementsystems,mailinglistmanagersandissuetrackingsystems.Providingintegratedmeasurementresultsgraphi-cally,EPMhelpsdevelopers/managerskeepprojectsundercontrolinrealtime.
1Introduction
Insoftwaredevelopmentinrecentyears,improvementofsoftwareprocessisincreasinglygainingattention.Itsprac-ticeinsoftwareorganizationsconsistsofrepeatedlymea-suringthedevelopmentactivities, ndingpotentialprob-lemsintheprocesses,assessingimprovementplans,andprovidingfeedbackintotheprocesses.Projectmanage-mentforeffectivesoftwareprocessimprovementmustbeachievedbasedonquantitativedata.
Manysoftwaremeasurementmethodshavebeenpro-posedtobetterunderstand,monitor,control,andpredictsoftwareprocessesandproducts[4].Forinstance,theGoal-Question-Metric(GQM)paradigm[2]providesasophisti-catedmeasurementtechnique.GQMguidestosetupmea-surementgoals,createquestionsbasedonthegoals,andde-terminemeasurementmodelsandproceduresbasedonthe
questions.ThemeasurementbasedonGQMisalogicalandreasonablemethod.
However,initspractice,memberswhoparticipateinmeasurementactivitiesneedtostriveforthemeasurementprocessesoneverylastdetail.Datacollectionformeasure-mentingeneralrequireshighcostsandcollaborationwithdevelopers.Itisdif culttocollectcoherent,quantitativedatacontinuouslyandmoreovertoutilizethecollecteddataforpracticingsoftwareprocessimprovement.Fewstudieshaveproposedmeasurementtoolsfordealingwithanumberofprojectdataespeciallyintermsofalarge-scalesoftwareorganization.
Asameasurement-basedapproachtotheaboveis-sues,wehavebeenstudyingempiricalsoftwareengineer-ing[1,3]whichevaluatesvarioustechnologiesandtoolsbasedonquantitativedataobtainedthroughactualuse.Ourgoalistodevelopanenvironmentcomposedofavarietyoftoolsforsupportingmeasurementbasedsoftwareprocessimprovement,whichwecallEmpiricalsoftwareEngineer-ingEnvironment(ESEE).
Inthispaper,weintroduceEmpiricalProjectMonitor(EPM)asapartialimplementationofESEE,whichau-tomaticallycollectsandmeasuresquantitativedatafromthreekindsofrepositoriesinwidelyusedsoftwaredevel-opmentsupportsystemssuchascon gurationmanagementsystems,mailinglistmanagersandissuetrackingsystems.Collectingsuchthedatainsoftwaredevelopmentautomat-icallyandprovidingintegratedmeasurementresultsgraph-ically,EPMhelpsdevelopers/managerskeeptheirprojectsundercontrolinrealtime.
2EmpiricalProjectMonitor(EPM)
WehavedevelopedEmpiricalProjectMonitor(EPM)[9]whichautomaticallycollectsandanalyzesdatafrommulti-
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