Prioritizing Program Elements: A Pretesting Effort to Improve Software Quality

Abstract

Improving the efficiency of a testing process is a challenging task. Prior work has shown that often, a small number of bugs account for the majority of the reported software failures; and often, most bugs are found in a small portion of the source code of a program. First, prioritizing the code elements according to their criticality and then conducting testing, will promote to reveal the important bugs at the early phase of testing. Keeping it in view, we propose an efficient test effort prioritization method that give a chance to the tester to focus more on the parts of the source code that are highly influenced towards the system failures or in which, the failures have high impact on the system. We consider five important factors such as influence towards system failures, average execution time, structural complexity, severity, and business value associated with a component and estimates the criticality of the component within a system. We have experimentally proved that our proposed test effort prioritization approach is effective in revealing important bugs at the early phase of testing as it is linked to external measure of defect severity and business value, internal measure of frequency, complexity, and coupling.

Prioritizing Unit Testing Effort Using Software Metrics and Machine Learning Classifiers (S)

“…Boehm and Basili [20] proposed a Pareto distribution in which 80% of all defects within software are found in 20% of the modules. Ray and Mohapatra [21] rely on that Pareto distribution to address the question of components prioritization. Shihab et al [22] explored the prioritization for unit testing phase in the context of legacy systems.…”

“…Ray and Mohapatra' approach [21] ignores the history of the software, whereas the approach of Shihab et al [22] is not suitable for new software. Moreover, neither approach takes advantage of the large amount of information available in the public open source repositories.…”

Ocl Formal Specification Based Metrics as a Measure of Complexity and Fault-Proneness

“…Ray el al. [11] have proposed a software component prioritization method as a pretesting activity to prioritize critical components. They have predicted critical components in source code of the system based on two criteria such as influence metric and operational profile.…”