Welcome to the InfoSci Platform
Reference Hub3
Model Driven Approach to Secure Optimized Test Paths for Smart Samsung Pay using Hybrid Genetic Tabu Search Algorithm

Model Driven Approach to Secure Optimized Test Paths for Smart Samsung Pay using Hybrid Genetic Tabu Search Algorithm

Nisha Rathee, Rajender Singh Chhillar
Copyright: © 2018 |Volume: 9 |Issue: 1 |Pages: 15
ISSN: 1947-8186|EISSN: 1947-8194|EISBN13: 9781522545088|DOI: 10.4018/IJISMD.2018010104
Cite Article Cite Article

MLA

Rathee, Nisha, and Rajender Singh Chhillar. "Model Driven Approach to Secure Optimized Test Paths for Smart Samsung Pay using Hybrid Genetic Tabu Search Algorithm." IJISMD vol.9, no.1 2018: pp.77-91. http://doi.org/10.4018/IJISMD.2018010104

APA

Rathee, N. & Chhillar, R. S. (2018). Model Driven Approach to Secure Optimized Test Paths for Smart Samsung Pay using Hybrid Genetic Tabu Search Algorithm. International Journal of Information System Modeling and Design (IJISMD), 9(1), 77-91. http://doi.org/10.4018/IJISMD.2018010104

Chicago

Rathee, Nisha, and Rajender Singh Chhillar. "Model Driven Approach to Secure Optimized Test Paths for Smart Samsung Pay using Hybrid Genetic Tabu Search Algorithm," International Journal of Information System Modeling and Design (IJISMD) 9, no.1: 77-91. http://doi.org/10.4018/IJISMD.2018010104

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Smart mobile pay applications on smart devices have been considered as the most efficient and secure mode of contactless payment. To safeguard customer credit/ debit card details, testing of mobile pay solutions like Samsung Pay is most important and critical task for testers. Testing of all the test cases is very tedious and a time-consuming task, therefore optimization techniques have been used to identify most optimized test paths. In this article, a hybrid genetic and tabu search optimization (HGTO) algorithm is proposed to secure optimized test paths using activity diagram of the smart Samsung Pay application. The proposed approach has been implemented using C++ language on the case study of the Smart Samsung Pay and an online airline reservation system. The experimental results show that the proposed technique is more effective in automatic generation and optimization of test paths, as compared to a simple genetic algorithm.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.