Abstract
By ordering test cases, early fault detection is focused on test case prioritization. In this field, it is widely known that algorithm and coverage criteria focused works are common. Previous works, which are related to test case prioritization, showed that practitioners need a novel method that optimizes test cases according to the cost of each test case instead of regarding the total cost of a test suite. In this work, by utilizing local and global search properties of a bat algorithm, a new bat-inspired test cases prioritization algorithm (BITCP) is proposed. In order to develop BITCP, test case execution time and the number of faults were adapted to the distance from the prey and loudness, respectively. The proposed method is then compared with four methods which are commonly used in this field. According to the results of the experiment, BITCP is superior to the conventional methods. In addition, as the complexity of the code of test cases increases, the decline in average percentage of fault detection is less in BITCP than the other four comparison algorithms produced.
Highlights
As the number of versions of a software increases, it is expected to reduce the number of defects
The paper will contribute to the existing literature by presenting the following: (1) presentation of a natureinspired test case prioritization algorithm which has not been employed in this field previously, (2) presentation of a proposed method that considers the individual cost of test cases rather than using total cost of test suites, (3) development of a better algorithm than traditional ones in terms of APFD by addressing some of the issues which have been encountered so far, and (4) presentation of a investigation of how faults revealed by test cases change depending on the complexity of code
A new nature-inspired test case prioritization algorithm, namely bat-inspired test cases prioritization algorithm (BITCP), is proposed by considering the basic steps of bat algorithm. Some properties such as test execution time and code defectiveness are adapted to notions of the algorithm
Summary
As the number of versions of a software increases, it is expected to reduce the number of defects. It is quite difficult to develop a prioritization algorithm which yields high APFD in various data sets, because the common methods are focused on the total cost of test cases rather than the individual cost of test cases. The paper will contribute to the existing literature by presenting the following: (1) presentation of a natureinspired test case prioritization algorithm which has not been employed in this field previously, (2) presentation of a proposed method that considers the individual cost of test cases rather than using total cost of test suites, (3) development of a better algorithm than traditional ones in terms of APFD by addressing some of the issues which have been encountered so far, and (4) presentation of a investigation of how faults revealed by test cases change depending on the complexity of code.
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