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

Abstract

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.

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

“…In [15], Badri et al investigated the capability of lack of cohesion metrics to predict testability using logistic regression methods. More recently, Badri et al [16,47] investigate the effect of control flow of the unit testing effort of classes.…”

An Empirical Analysis of the Relationship between Cohesion and Testing Effort

“…The results indicated that complexity, size, cohesion, and (to some extent) coupling were found to be significant predictors of the testing effort of classes. Later, Badri et al [18], [19] studied the effect of control flow of the unit testing effort of classes. They classified the classes into low and high according to the required testing effort.…”

Metrics and Software Quality Evolution: A Case Study on Open Source Software

“…For more details see [12], [22], [23]. The Qi metric is based on Control Call Graphs (CCG), which are a reduced form of traditional Control Flow Graphs (CFG).…”

“…Testability was measured (inversely) by the number of lines of test code (JUnit test suites) and the number of assert statements in the test code. More recently, we investigated the capacity of the Qi metric in predicting the unit testing effort of classes using regression analysis techniques [23].…”