Reliance on correlation data for complexity metric use and validation

MacDonell, Stephen G.

doi:10.1145/122598.122613

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…eLOC counts the effective lines of source code, i.e. source lines without purely comments, braces and blanks [33]. For each class we consider a faulty version with five injected faults available from previous studies [23,24].…”

Section: Study Contextmentioning

confidence: 99%

The impact of test case summaries on bug fixing performance

Panichella

Beller

et al. 2016

Proceedings of the 38th International Conference on Software Engineering

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Automated test generation tools have been widely investigated with the goal of reducing the cost of testing activities. However, generated tests have been shown not to help developers in detecting and finding more bugs even though they reach higher structural coverage compared to manual testing. The main reason is that generated tests are difficult to understand and maintain. Our paper proposes an approach, coined TestScribe, which automatically generates test case summaries of the portion of code exercised by each individual test, thereby improving understandability. We argue that this approach can complement the current techniques around automated unit test generation or search-based techniques designed to generate a possibly minimal set of test cases. In evaluating our approach we found that (1) developers find twice as many bugs, and (2) test case summaries significantly improve the comprehensibility of test cases, which is considered particularly useful by developers. PeerJ PrePrints | https://doi.org/10.7287/peerj.preprints.1467v3 | CC-BY 4.0 Open Access | rec ABSTRACT Automated test generation tools have been widely investigated with the goal of reducing the cost of testing activities. However, generated tests have been shown not to help developers in detecting and finding more bugs even though they reach higher structural coverage compared to manual testing. The main reason is that generated tests are difficult to understand and maintain. Our paper proposes an approach, coined TestDescriber, which automatically generates test case summaries of the portion of code exercised by each individual test, thereby improving understandability. We argue that this approach can complement the current techniques around automated unit test generation or search-based techniques designed to generate a possibly minimal set of test cases. In evaluating our approach we found that (1) developers find twice as many bugs, and (2) test case summaries significantly improve the comprehensibility of test cases, which is considered particularly useful by developers.

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Section: Study Contextmentioning

confidence: 99%

The impact of test case summaries on bug fixing performance

Panichella

Beller

et al. 2016

Proceedings of the 38th International Conference on Software Engineering

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A set of complexity metrics for guiding the software test process

Liggesmeyer

1995

Software Qual J

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Five principles for the formal validation of models of software metrics

Ejiogu¹

1993

SIGPLAN Not.

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The goal of software metrics is the improvement of the software process. Five principles are fundamental to the formal validation of models of software metrics:-- Attribute Type --what attribute(s) of software behavior are we measuring?; The mathematical postulates of a measure function --a model must have the utility for comparison; this unique criterion must be passed by every effective model of measure; Metrical Vindication --applying the model directly to measure actual software module(s); how consistent and reliable are the results of the measures?; Feedback Effect --how does the metric help us to identify faults and errors (of design) or improve testing and maintenance; what is a metric if it is just a number?; Units of Measure --what are we measuring with respect to dimensions: size, length/depth, extent, degree of variation, degradation, etc.?; a measure without unit(s) is like a building without a roof.Without principles, there is nothing to validate. Every good science is a body of relevant principles. Some worked examples on some of these principles are presented. Some of these examples in a way, expose the failures or frustrations resulting from the applications of some models of measure presently being used in industry and science. Not every mathematical function can be used as a model of measurement.

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Reliance on correlation data for complexity metric use and validation

Abstract: Abstract

Cited by 3 publications

References 15 publications

The impact of test case summaries on bug fixing performance

The impact of test case summaries on bug fixing performance

A set of complexity metrics for guiding the software test process

Five principles for the formal validation of models of software metrics

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