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-