Applying data mining to software maintenance records

ABSTRACT

In a system maintained over a long time period, as is the case for legacy software, there will be many unknown and non-trivial relationships among components. Finding such hidden relationships may help software engineers in their maintenance activities. In this paper we present an approach whereby we mine software update records to find relationships between files that are changed together. The generalized models we present as results are obtained by using features extracted from different sources of knowledge such as source code and problem reports. The predictive quality of some of the generated models suggest that they can be deployed to be used in a real world setting. The paper also includes the results of analyzing the structure of some of the best models obtained.

REFERENCES

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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

  I. Computing Methodologies
  I.5 PATTERN RECOGNITION
      I.5.2 Design Methodology

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

General Terms:
Algorithms, Experimentation, Performance