Predicting Testability of Eclipse: A Case Study

Singh, Yogesh; Saha, Anju

doi:10.3923/jse.2010.122.136

Cited by 20 publications

(13 citation statements)

References 11 publications

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“…The testing effort is measured in terms of lines of code added or changed during the life cycle of a defect. In [19], Singh et al attempt to predict testability of Eclipse at the package level. Badri et al [14] performed a similar study to that conducted by Bruntink et al [7] using two open source Java software systems in order to explore the relationship between lack of cohesion metrics and testability of classes.…”

Section: Software Testabilitymentioning

confidence: 99%

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Empirical Analysis of Object-Oriented Design Metrics for Predicting Unit Testing Effort of Classes

Badri¹,

Touré²

2012

JSEA

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In this paper, we investigate empirically the relationship between object-oriented design metrics and testability of classes. We address testability from the point of view of unit testing effort. We collected data from three open source Java software systems for which JUnit test cases exist. To capture the testing effort of classes, we used metrics to quantify the corresponding JUnit test cases. Classes were classified, according to the required unit testing effort, in two categories: high and low. In order to evaluate the relationship between object-oriented design metrics and unit testing effort of classes, we used logistic regression methods. We used the univariate logistic regression analysis to evaluate the individual effect of each metric on the unit testing effort of classes. The multivariate logistic regression analysis was used to explore the combined effect of the metrics. The performance of the prediction models was evaluated using Receiver Operating Characteristic analysis. The results indicate that: 1) complexity, size, cohesion and (to some extent) coupling were found significant predictors of the unit testing effort of classes and 2) multivariate regression models based on object-oriented design metrics are able to accurately predict the unit testing effort of classes.

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Section: Software Testabilitymentioning

confidence: 99%

“…ing, cohesion and inheritance) were already used in recent years to assess (predict) testability of OO software systems [7,8,[14][15][16][17][18][19][20]. Software testability has been addressed from different point of views.…”

Section: Introductionmentioning

confidence: 99%

Empirical Analysis of Object-Oriented Design Metrics for Predicting Unit Testing Effort of Classes

Badri¹,

Touré²

2012

JSEA

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show abstract

“…The testing effort was measured in terms of lines of code added or changed during the lifecycle of a defect. Singh and Saha (2010) focused on the prediction of the testability of Eclipse at the package level. Testability was measured using several metrics including the number of lines of test code, the number of assert statements in the test code, the number of test methods and the number of test classes.…”

Section: Related Workmentioning

confidence: 99%

“…TNOO: This metric counts the number of methods in a test class (Singh and Saha 2010). It reflects another perspective of the size of a test class.…”

Section: Unit Test Case Metricsmentioning

confidence: 99%

A metrics suite for JUnit test code: a multiple case study on open source software

Touré

Badri

Lamontagne

2014

J Softw Eng Res Dev

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“…Singh et al conclude that the performance of the developed model is to a large degree dependent on the data used. In [41], Singh and Saha attempt to predict the testability of Eclipse at package level. This study was, however, limited to a correlation analysis between source code metrics and test metrics.…”

Section: Software Testabilitymentioning

confidence: 99%

Evaluating the Effect of Control Flow on the Unit Testing Effort of Classes: An Empirical Analysis

Badri

Touré

2012

Advances in Software Engineering

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The aim of this paper is to evaluate empirically the relationship between a new metric (Quality Assurance Indicator-Qi) and testability of classes in object-oriented systems. The Qi metric captures the distribution of the control flow in a system. We addressed testability from the perspective of unit testing effort. We collected data from five open source Java software systems for which JUnit test cases exist. To capture the testing effort of classes, we used different metrics to quantify the corresponding JUnit test cases. Classes were classified, according to the required testing effort, in two categories: high and low. In order to evaluate the capability of the Qi metric to predict testability of classes, we used the univariate logistic regression method. The performance of the predicted model was evaluated using Receiver Operating Characteristic (ROC) analysis. The results indicate that the univariate model based on the Qi metric is able to accurately predict the unit testing effort of classes.

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Predicting Testability of Eclipse: A Case Study

Cited by 20 publications

References 11 publications

Empirical Analysis of Object-Oriented Design Metrics for Predicting Unit Testing Effort of Classes

Empirical Analysis of Object-Oriented Design Metrics for Predicting Unit Testing Effort of Classes

A metrics suite for JUnit test code: a multiple case study on open source software

Evaluating the Effect of Control Flow on the Unit Testing Effort of Classes: An Empirical Analysis

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