Model-Based Project Process Analysis Using Project Tracking Data

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dc.contributor.authorYoon, Kyung-A-
dc.contributor.authorMin, Sang-Yoon-
dc.contributor.authorBae, Doo-Hwan-
dc.date.accessioned2009-12-23-
dc.date.available2009-12-23-
dc.date.issued2003-06-
dc.identifier.citationLecture Notes in Computer Science, Vol.3026, pp.148-167en
dc.identifier.isbn978-3-540-21975-0-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10203/15663-
dc.description.abstractIn software process improvement, accumulating and analyzing the historical data from past projects are essential work. However, setting up the systematic and logical measurement and analysis program is very difficult. Many mature organizations have their own measurement program for the process improvement. However, most of them are based on the statistical metricsdriven approach that consequently limits logical reasoning on the detailed analysis on the process. In this paper, we propose a process analysis approach called MPAF(Model-based Process Analysis Framework), based on formal process modeling. In MPAF, the corresponding formal process instance model is recovered through data gathering from a project execution. Various formal analysis can be performed on the recovered and reconstructed process instance model for diagnosing the vitality of the project. We also performed experimental case study by applying MPAF to real world industry projects.en
dc.language.isoen_USen
dc.publisherSpringer Verlag (Germany)en
dc.subjectModel-Based Project Process Analysisen
dc.subjectProject Tracking Dataen
dc.titleModel-Based Project Process Analysis Using Project Tracking Dataen
dc.typeArticleen

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