ABC-CAG: Covering Array Generator for Pair-wise Testing Using Artificial Bee Colony Algorithm

Journal Title: e-Informatica Software Engineering Journal - Year 2016, Vol 10, Issue 1

Abstract

Testing is an indispensable part of the software development life cycle. It is performed to improve the performance, quality and reliability of the software. Various types of testing such as functional testing and structural testing are performed on software to uncover the faults caused by an incorrect code, interaction of input parameters, etc. One of the major factors in deciding the quality of testing is the design of relevant test cases which is crucial for the success of testing. In this paper we concentrate on generating test cases to uncover faults caused by the interaction of input parameters. It is advisable to perform thorough testing but the number of test cases grows exponentially with the increase in the number of input parameters, which makes exhaustive testing of interaction of input parameters imprudent. An alternative to exhaustive testing is combinatorial interaction testing (CIT) which requires that every $t$-way interaction of input parameters be covered by at least one test case. Here, we present a novel strategy ABC-CAG (Artificial Bee Colony-Covering Array Generator) based on the Artificial Bee Colony (ABC) algorithm to generate covering an array and a mixed covering array for pair-wise testing. The proposed ABC-CAG strategy is implemented in a tool and experiments are conducted on various benchmark problems to evaluate the efficacy of the proposed approach. Experimental results show that ABC-CAG generates better/comparable results as compared to the existing state-of-the-art algorithms.

Authors and Affiliations

Priti Bansal, Sangeeta Sabharwal, Nitish Mittal, Sarthak Arora

Keywords

Related Articles

Measuring Goal-Oriented Requirements Language Actor Stability

Background: Goal models describe interests, preferences, intentions, desired goals and strategies of intervening stakeholders during the early requirements engineering stage. When capturing the requirements of real-world...

Software Startups -- A Research Agenda

Software startup companies develop innovative, software-intensive products within limited time frames and with few resources, searching for sustainable and scalable business models. Software startups are quite distinct f...

Model Driven Web Engineering: A Systematic Mapping Study

Background: Model Driven Web Engineering (MDWE) is the application of the model driven paradigm to the domain of Web software development, where it is particularly helpful because of the continuous evolution of Web techn...

Using the Cognitive Walkthrough Method in Software Process Improvement

In the past years, efforts in the field of Software Process Improvement were increasingly focusing on human aspects making one aware that people participating in the processes have a high impact on the success of any imp...

Automatic SUMO to UML Translation

Existing ontologies are a valuable source of domain knowledge. This knowledge could be extracted and reused to create domain models. The extraction process can be aided by tools that enable browsing ontology, marking int...

Download PDF file
  • EP ID EP201183
  • DOI 10.5277/e-Inf160101
  • Views 92
  • Downloads 0

How To Cite

Priti Bansal, Sangeeta Sabharwal, Nitish Mittal, Sarthak Arora (2016). ABC-CAG: Covering Array Generator for Pair-wise Testing Using Artificial Bee Colony Algorithm. e-Informatica Software Engineering Journal, 10(1), 9-29. https://europub.co.uk/articles/-A-201183