Improving Test Automation using Algorithms

The research topic is to improve test automation using algorithms, aiming to provide a strategy for automaters to follow and enhance the efficiency of software testing processes. The current research discusses the steps of software automation and proposes an algorithm to address issues faced in system management automation for services like Firewall, DHCP, and DNS. It also references previous studies on statistical tests, automated test case generation, and genetic algorithms for software testing.

Research 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 thus 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 automaters
should be made to work using that process. This research will try to portray that 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
the 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 about the steps of software automation and the algorithm for
addressing the issues will be discussed that are face in the system management automation
for the 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.
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.
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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
genetic algorithm. arXiv preprint arXiv:1411.1154.
Tretmans, J. and Brinksma, E., 2003. Torx: Automated model-based testing.
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