Automated Software Engineering

, Volume 19, Issue 2, pp 141–165

Applying the Mahalanobis-Taguchi strategy for software defect diagnosis

Article

DOI: 10.1007/s10515-011-0091-2

Cite this article as:
Liparas, D., Angelis, L. & Feldt, R. Autom Softw Eng (2012) 19: 141. doi:10.1007/s10515-011-0091-2

Abstract

The Mahalanobis-Taguchi (MT) strategy combines mathematical and statistical concepts like Mahalanobis distance, Gram-Schmidt orthogonalization and experimental designs to support diagnosis and decision-making based on multivariate data. The primary purpose is to develop a scale to measure the degree of abnormality of cases, compared to “normal” or “healthy” cases, i.e. a continuous scale from a set of binary classified cases. An optimal subset of variables for measuring abnormality is then selected and rules for future diagnosis are defined based on them and the measurement scale. This maps well to problems in software defect prediction based on a multivariate set of software metrics and attributes. In this paper, the MT strategy combined with a cluster analysis technique for determining the most appropriate training set, is described and applied to well-known datasets in order to evaluate the fault-proneness of software modules. The measurement scale resulting from the MT strategy is evaluated using ROC curves and shows that it is a promising technique for software defect diagnosis. It compares favorably to previously evaluated methods on a number of publically available data sets. The special characteristic of the MT strategy that it quantifies the level of abnormality can also stimulate and inform discussions with engineers and managers in different defect prediction situations.

Keywords

Software defect prediction Fault-proneness Software testing Mahalanobis-Taguchi strategy 

Abbreviations

MT

Mahalanobis-Taguchi;

MD

Mahalanobis distance;

MTS

Mahalanobis-Taguchi system;

MTGS

Mahalanobis-Taguchi Gram-Schmidt process;

ROC

Receiver Operating Characteristic;

AUC

Area under the curve

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Dimitris Liparas
    • 1
  • Lefteris Angelis
    • 1
  • Robert Feldt
    • 2
  1. 1.Department of InformaticsAristotle University of ThessalonikiThessalonikiGreece
  2. 2.Department of Computer Science and EngineeringChalmers University of TechnologyGothenburgSweden

Personalised recommendations