Title : ( A Semantic Web Enabled Approach to Automate Test Script Generation for Web Applications )
Authors: Mahboubeh Dadkhah , Saeed Araban , Samad Paydar ,Abstract
Software testing is one of the most important activities for ensuring quality of software products. It is a complex and knowledge-intensive activity which can be improved by reusing tester knowledge. Generally, testing web applications involves writing manual test scripts which is a tedious and labor- intensive process. Manually written test scripts are valuable assets encapsulating the knowledge of the testers. Reusing these scripts to automatically generate new test scripts can improve the effectiveness of software testing and reduce the cost of required manual interventions. In this paper, a semantic web enabled approach is proposed for automatically adapting and generating test scripts. It reduces the cost of human intervention across multiple scripts by accumulating the human knowledge as semantic annotations on test scripts. This is supported by designing an ontology which defines the concepts and relationships required for test script annotation. The proposed approach is based on novel algorithms for adapting and generating new test scripts. The initial experiments show that the proposed approach is promising as it successfully increases the level of test automation.
Keywords
, Automated testing, semantic web, Test adaptation, Test generation, Test ontology@article{paperid:1087247,
author = {Dadkhah, Mahboubeh and Araban, Saeed and Paydar, Samad},
title = {A Semantic Web Enabled Approach to Automate Test Script Generation for Web Applications},
journal = {Journal of Computer and Knowledge Engineering},
year = {2020},
volume = {3},
number = {1},
month = {December},
issn = {2538-5453},
pages = {11--24},
numpages = {13},
keywords = {Automated testing; semantic web; Test adaptation; Test generation; Test ontology},
}
%0 Journal Article
%T A Semantic Web Enabled Approach to Automate Test Script Generation for Web Applications
%A Dadkhah, Mahboubeh
%A Araban, Saeed
%A Paydar, Samad
%J Journal of Computer and Knowledge Engineering
%@ 2538-5453
%D 2020