Early estimation of defect density using an in-process Haskell metrics model

ABSTRACT

Early estimation of defect density of a product is an important step towards the remediation of the problem associated with affordably guiding corrective actions in the software development process. This paper presents a suite of in-process metrics that leverages the software testing effort to create a defect density prediction model for use throughout the software development process. A case study conducted with Galois Connections, Inc. in a Haskell programming environment indicates that the resulting defect density prediction is indicative of the actual system defect density.

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INDEX TERMS

Primary Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
      D.2.8 Metrics

General Terms:
Measurement, Reliability

Keywords:
empirical software engineering, haskell, multiple regression, software quality