Information Systems Frontiers

, Volume 4, Issue 4, pp 409–423 | Cite as

Intelligent Search Methods for Software Maintenance

Article
  • 48 Downloads

Abstract

This paper describes a study of what we call intelligent search techniques as implemented in a software maintenance environment. The techniques studied include abbreviation concatenation and abbreviation expansion. We also describe rating algorithms used to prioritize the query results. To evaluate our approach, we present a series of experiments in which we compare our algorithms' ratings of results to ratings provided by software engineers.

information retrieval software maintenance intelligent search abbreviation expansion software engineering tools 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Albrechtsen H. Software information systems: Information retrieval techniques. In: Hall P, ed. Software Reuse and Reverse Engineering. London: Chapman & Hall, 1992.Google Scholar
  2. Anquetil N, Lethbridge T. Extracting concepts from file names; a new file clustering criterion. In: ICSE'98, 1998:84-93.Google Scholar
  3. Baeza-Yates R. Introduction to data structures and algorithms related to information retrieval. In: Frakes W, Baeza-Yates R, eds. Information Retrieval: Data Structure and Algorithms. Englewood, NJ: Prentice Hall, 1992.Google Scholar
  4. Baeza-Yates R. Modern Information Retrieval. New York: Addison-Wesley, 1999.Google Scholar
  5. Frakes WB, Nehmeh BA. Software reuse through information retrieval. SIGIR FORUM 1987;21(1/2):30-36.Google Scholar
  6. Korfhage RR. Research in relevance feedback and query modification. In: Information Storage and Retrieval. NY: Wiley, 1997.Google Scholar
  7. Lethbridge T. Integrated personal work management in the TkSee software exploration tool. In: Second International Symposium on (CoSET2000), ICSE 2000, 2000:31-38.Google Scholar
  8. Lethbridge T, Anquetil N. Architecture of a source code exploration tool: A software engineering case study. University of Ottawa, CS Technical Report TR-97-07, 1997. Also available at http://www.site.uottawa.ca/∼tcl/papers/Cascon/TR-97-07.htmlGoogle Scholar
  9. Lethbridge T, Singer J. Studies of the work practices of software engineers. In: Erdogmus H, Tanir O, eds. Advances in Software Engineering: Comprehension, Evaluation, and Evolution. Springer-Verlag, 2001:53-76.Google Scholar
  10. Liu H. Intelligent search techniques for large software systems. M.Sc. Thesis, School of Information Technology and Engineering, University of Ottawa, 2001. Also available at http://www.site.uottawa.ca/∼tcl/gradtheses/hliu/Google Scholar
  11. Maletic JI, Marcus A. Supporting program comprehension using semantic and structural information. In: Proc. of 23rd ICSE, Toronto, 2001:103-112.Google Scholar
  12. Sayyad-Shirabad J, Lethbridge T, Lyon S. A little knowledge can go a long way towards program understanding. In: IWPC, Dearborn, MI, 1997:111-117.Google Scholar

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  1. 1.School of Information Technology and EngineeringUniversity of OttawaOttawaCanada

Personalised recommendations