Beyond the Personal Software Process: metrics collection and analysis for the differently disciplined

  • Authors:

  • Philip M. Johnson;Hongbing Kou;Joy Agustin;Christopher Chan;Carleton Moore;Jitender Miglani;Shenyan Zhen;William E. J. Doane

  • Affiliations:

  • University of Hawai'i, Honolulu, HI;University of Hawai'i, Honolulu, HI;University of Hawai'i, Honolulu, HI;University of Hawai'i, Honolulu, HI;University of Hawai'i, Honolulu, HI;University of Hawai'i, Honolulu, HI;University of Hawai'i, Honolulu, HI;University of Hawai'i, Honolulu, HI

  • Venue:
  • Proceedings of the 25th International Conference on Software Engineering
  • Year:
  • 2003

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Abstract

Pedagogies such as the Personal Software Process (PSP) shift metrics definition, collection, and analysis from the organizational level to the individual level. While case study research indicates that the PSP can provide software engineering students with empirical support for improving estimation and quality assurance, there is little evidence that many students continue to use the PSP when no longer required to do so. Our research suggests that this "PSP adoption problem" may be due to two problems: the high overhead of PSP-style metrics collection and analysis, and the requirement that PSP users "context switch" between product development and process recording. This paper overviews our initial PSP experiences, our first attempt to solve the PSP adoption problem with the LEAP system, and our current approach called Hackystat. This approach fully automates both data collection and analysis, which eliminates overhead and context switching. However, Hackystat changes the kind of metrics data that is collected, and introduces new privacy-related adoption issues of its own.