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Process Modelling and Empirical Studies of Software Evolution (PMESSE'97): Workshop Report

  • R. Harrison
  • , L. Briand
  • , J. Daly
  • , M. Kellner
  • , D. M. Raffo
  • , M. J. Shepperd
  • University of Southampton
  • University of Oxford
  • University of London
  • IEEE
  • Fraunhofer Institute for Experimental Software Engineering
  • Sorbonne Université
  • Université Paris-Saclay
  • CISI Ingénierie
  • NASA Software Engineering Laboratory
  • NASA Goddard Space Flight Center
  • Computer Research Institute of Montreal
  • University of Strathclyde
  • Carnegie Mellon University
  • University of Texas at Austin
  • Portland State University
  • Bournemouth University

Research output: Contribution to journalArticlepeer-review

Abstract

Much progress is being made in both the areas of process modelling and software metrics. However, neither of these concepts is complete without the other: processes cannot be improved if no assessment of quality is available, and metrics are useless if they cannot be applied in order to assess the evolution of systems. The PMESSE (Process Modelling and Empirical Studies of Software Evolution) Workshop, held in Boston MA, on May 18, 1997, brought together researchers and practitioners from both of these fields, and stimulated some very lively debate on these issues. This collection of reports reflects the work done by the Workshops five Working Groups. Dialogue between the software metrics and process modelling communities is essential. This workshop succeeded in bringing together researchers with a wide range of research interests, and the resulting discussions were very animated. Perhaps the most contentious point of discussion lay in the 'level of granularity' question; some suggested that only high-level measurements were sensible, whereas others preferred to 'divide and conquer' the system, providing detailed process measurement schemas. No doubt this debate will continue.

Original languageEnglish
Pages (from-to)381-403
Number of pages23
JournalEmpirical Software Engineering
Volume2
Issue number4
DOIs
Publication statusPublished - 1997
Externally publishedYes

Keywords

  • Empirical studies
  • Legacy systems
  • Maintenance
  • Metrics

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