TY  - JOUR
T1  - Creation of Software Testing Environment in Cloud Platform
AU - Vijay, J. Frank AU - Hariharan, B. 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 13
SP  - 2228
EP  - 2237
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.2228.2237
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.2228.2237
KW  - K-medoid
KW  -attribute-based Elliptic Curve Cryptography (ECC)
KW  -cosine similarity
KW  -weight-based prioritization technique
KW  -Test Case Prioritization (TCP) technique
KW  -Adaptive Random Test case prioritization (ART)
KW  -Local Beam Search (LBM)
AB  - Cloud computing is a novel computing standard that provides major support for the software testing and development. In this study, an efficient software testing framework with weight-based prioritization technique is proposed for performing software testing in the distributed cloud environment. At first, thetest case dataset is initialized then the frequent test case in the dataset is estimated. The weight of the similar test cases are determined using the cosine similarity. With the estimated weight values, the weight based prioritization technique is applied for prioritizing the test cases. After prioritization, the K-Medoid clustering algorithm is deployed for clustering the similar test cases. To provide security for the test cases, an Attribute key based Elliptic Curve Cryptography (ECC) algorithm is used for encryption and decryption. Further, a cache memory is exploited for optimizing the memory consumption of the test case execution. The proposed framework is deployed in cloudsim and the experimental results prove that the proposed framework provides optimal results than the existing random, prioritized techniques, K-mean algorithm, Hierarchical algorithm, Test Case Prioritization (TCP) technique, Adaptive Random Test case prioritization (ART), Local Beam Search (LBM) and greedy approaches.
ER  -