Open Access
ARTICLE
The Genetic Algorithm and Binary Search Technique in the Program Path Coverage for Improving Software Testing Using Big Data
Aysh Alhroob1,*, Wael Alzyadat2, Ayad Tareq Imam1, Ghaith M. Jaradat3
1 Faculty of Information Technology, Isra University, Amman, Jordan
2 Faculty of Science and Information Technology, Al-Zaytoonah University, Amman, Jordan
3 Faculty of Computer Science and Information Technology, Jerash University, Jerash, Jordan
* Corresponding Author: Aysh Alhroob,
Intelligent Automation & Soft Computing 2020, 26(4), 725-733. https://doi.org/10.32604/iasc.2020.010106
Abstract
Software program testing is the procedure of exercising a software component
with a selected set of test cases as a way to discover defects and assess
quality. Using software testing automation, especially the generating of testing
data increases the effectiveness and efficiency of software testing as a whole.
Instead of creating testing data from scratch, Big Data (BD) offers an important
source of testing data. Although it is a good source, there is a need to select a
proper set of testing data for the sake of selecting an optimal sub-domain input
values from the BD. To refine the efficiency of software testing, this paper
proposes a hybrid Genetic Algorithm and Binary Search (BSGA) technique that
is used for detecting the error-prone path in a program. The BSGA combines
the Genetic Algorithm (GA) with the Binary Search (BS) algorithm that uses the
BD as input values for the program path coverage, and thus enhances the
software testing. The BSGA represents a robust nonlinear search technique
and a better quality solution, which therefore results in a cost reduction in the
software testing industry. The experiments show that the results approved the
impact of using the BS to enhance the performance of the GA, in terms of
finding optimal test cases and test data for the input Big Data domain values.
Whereas, these results minimize the cost of testing.
Keywords
Cite This Article
A. Alhroob, W. Alzyadat, A. Tareq Imam and G. M. Jaradat, "The genetic algorithm and binary search technique in the program path coverage for improving software testing using big data,"
Intelligent Automation & Soft Computing, vol. 26, no.4, pp. 725–733, 2020.
Citations