Supporting maintenance of legacy software with data mining techniques

ABSTRACT

Software maintenance is a very costly and time consuming part of the software life cycle. The problems with software maintenance are even more pressing in the case of legacy software systems. This paper describes our research towards application of inductive methods to the data extracted from source code, software maintenance records, and software developers activities to learn a Maintenance Relevance Relation among files in a software system. We discuss the methodology employed, and some of the encountered problems and our solutions for them. The paper will also present some of the results that we have obtained.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining

Additional Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
      D.2.7 Distribution, Maintenance, and Enhancement
          Subjects: Documentation

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.6 Learning
          Subjects: Knowledge acquisition; Induction

  K. Computing Milieux
  K.6 MANAGEMENT OF COMPUTING AND INFORMATION SYSTEMS
      K.6.3 Software Management
          Subjects: Software maintenance

General Terms:
Algorithms, Design, Experimentation, Measurement, Performance, Theory