Test Efficiency Improved by the Automation Process


Research on Topic: Improving test automation using algorithms


It has been observed that the many automation testers have been given this job without giving them proper guidelines about the automation test process. They do not follow and process or strategy to do this work. After some time, they do not observe any improvement in the cycle time or the execution time. So, an efficient method needs to be deployed and the automakers should be made to work using that process. This research will try to portray how the test automation can be improved using the algorithms. 
In the software industry, the test efficiency can be improved by the automation process. This test is the testing of the software in the companies. To ensure that the coverage of the test is satisfactory and to reduce the risks related to the projects, the companies use either manual or automated tools for improving their test automation level.  The selection of either of them depends on the reduction in the cycle time of the project and the time taken for the test. The current research will discuss the steps of software automation and the algorithm for addressing the issues will be discussed that are face in the system management automation for services like Firewall, DHCP and DNS. The research will be done using the secondary sources of information and the experience of various researchers and experimenters of using the various automation frameworks.

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List of papers:

Arcuri, A. and Briand, L., 2014. A hitchhiker's guide to statistical tests for assessing randomized algorithms in software engineering. Software Testing, Verification and Reliability, 24(3), pp.219-250.
Anand, S., Burke, E.K., Chen, T.Y., Clark, J., Cohen, M.B., Grieskamp, W., Harman, M., Harrold, M.J. and McMinn, P., 2013. An orchestrated survey of methodologies for automated software test case generation. Journal of Systems and Software, 86(8), pp.1978-2001.
Sharma, C., Sabharwal, S. and Sibal, R., 2014. A survey on software testing techniques using a genetic algorithm. arXiv preprint arXiv:1411.1154.
Tretmans, J. and Brinksma, E., 2003. Torx: Automated model-based testing

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