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Framework for cloud‐based software test data generation service
Author(s) -
Chawla Priyanka,
Chana Inderveer,
Rana Ajay
Publication year - 2019
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.2708
Subject(s) - cloud computing , computer science , service provider , service (business) , cloud testing , software as a service , software , computer security , database , cloud computing security , operating system , software development , economy , economics
Summary This paper presents the framework of cloud‐based software test data generation service (CSTS) that caters to cost‐effective test data generation service in a cloud environment. In contrast to existing conventional or cloud‐based testing frameworks, CSTS has a number of unique benefits. First, CSTS is designed to facilitate test data generation in minimum time and cost. Second, unlike existing frameworks which mandates clients to opt for resources to test their jobs, CSTS guides customer for selecting best cluster configuration in order to minimize the cost. While the existing models do not provide any solution for trust establishment in cloud computing services, CSTS delivers it by implementing security mechanism with the provision of role based access control. The security mechanism proposed in this paper ensures the protection of data and code of different users. Third, CSTS provides a mathematical pricing model to fulfill the expectations of customers and also to maximize the net profit of service providers. Cloud service request model has also been designed that postulates service level agreements between customers and service providers. We have evaluated, compared, and analyzed our framework and have found that it outperforms other existing cloud‐based frameworks.