Advanced quality prediction model for software architectural knowledge sharing

  • Authors:

  • Peng Liang;Anton Jansen;Paris Avgeriou;Antony Tang;Lai Xu

  • Affiliations:

  • Wuhan University, State Key Lab of Software Engineering, School of Computer, 430072 Wuhan, China;ABB Corporate Research, Industrial Software Systems, Forskargränd 8, SE-72178 Västerås, Sweden;University of Groningen, Department of Mathematics and Computing Science, Nijenborgh 9, 9700 AK Groningen, The Netherlands;Swinburne University of Technology, Faculty of Information and Communication Technologies, VIC 3122, Melbourne, Australia;SAP Research Switzerland, Blumenbergplatz 9, 9000 St. Gallen, Switzerland

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2011

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Abstract

In the field of software architecture, a paradigm shift is occurring from describing the outcome of architecting process to describing the Architectural Knowledge (AK) created and used during architecting. Many AK models have been defined to represent domain concepts and their relationships, and they can be used for sharing and reusing AK across organizations, especially in geographically distributed contexts. However, different AK domain models can represent concepts that are different, thereby making effective AK sharing challenging. In order to understand the mapping quality from one AK model to another when more than one AK model coexists, AK sharing quality prediction based on the concept differences across AK models is necessary. Previous works in this area lack validation in the actual practice of AK sharing. In this paper, we carry out validation using four AK sharing case studies. We also improve the previous prediction models. We developed a new advanced mapping quality prediction model, this model (i) improves the prediction accuracy of the recall rate of AK sharing quality; (ii) provides a better balance between prediction effort and accuracy for AK sharing quality.