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Software fault prediction metrics

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TLDR
Object-oriented and process metrics have been reported to be more successful in finding faults compared to traditional size and complexity metrics and seem to be better at predicting post-release faults than any static code metrics.
Abstract
ContextSoftware metrics may be used in fault prediction models to improve software quality by predicting fault location. ObjectiveThis paper aims to identify software metrics and to assess their applicability in software fault prediction. We investigated the influence of context on metrics' selection and performance. MethodThis systematic literature review includes 106 papers published between 1991 and 2011. The selected papers are classified according to metrics and context properties. ResultsObject-oriented metrics (49%) were used nearly twice as often compared to traditional source code metrics (27%) or process metrics (24%). Chidamber and Kemerer's (CK) object-oriented metrics were most frequently used. According to the selected studies there are significant differences between the metrics used in fault prediction performance. Object-oriented and process metrics have been reported to be more successful in finding faults compared to traditional size and complexity metrics. Process metrics seem to be better at predicting post-release faults compared to any static code metrics. ConclusionMore studies should be performed on large industrial software systems to find metrics more relevant for the industry and to answer the question as to which metrics should be used in a given context.

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Citations
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Using metrics in Agile and Lean Software Development - A systematic literature review of industrial studies

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Identifying, categorizing and mitigating threats to validity in software engineering secondary studies

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The impact of information security events to the stock market

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References
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Journal ArticleDOI

The measurement of observer agreement for categorical data

TL;DR: A general statistical methodology for the analysis of multivariate categorical data arising from observer reliability studies is presented and tests for interobserver bias are presented in terms of first-order marginal homogeneity and measures of interob server agreement are developed as generalized kappa-type statistics.
Journal ArticleDOI

A Coefficient of agreement for nominal Scales

TL;DR: In this article, the authors present a procedure for having two or more judges independently categorize a sample of units and determine the degree, significance, and significance of the units. But they do not discuss the extent to which these judgments are reproducible, i.e., reliable.
Book

A metrics suite for object oriented design

TL;DR: This research addresses the needs for software measures in object-orientation design through the development and implementation of a new suite of metrics for OO design, and suggests ways in which managers may use these metrics for process improvement.
Book

A complexity measure

TL;DR: In this paper, a graph-theoretic complexity measure for managing and controlling program complexity is presented. But the complexity is independent of physical size, and complexity depends only on the decision structure of a program.
Journal ArticleDOI

A Complexity Measure

TL;DR: Several properties of the graph-theoretic complexity are proved which show, for example, that complexity is independent of physical size and complexity depends only on the decision structure of a program.
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