Authors:
Arnold Szederjesi-Dragomir
;
Radu Găceanu
and
Andreea Vescan
Affiliation:
Computer Science Department, Faculty of Mathematics and Computer Science, Babeş-Bolyai University, Cluj-Napoca, România
Keyword(s):
Test Case Prioritization, Continuous Integration, Neural Network, Elixir.
Abstract:
Test Case Prioritization (TCP) is crucial in the fast-paced world of software development to speed up and optimize testing procedures, particularly in Continuous Integration (CI) setups. This paper aims to first validate a state-of-the-art neural network model to TCP in CI environments, by applying it into a real-world industrial context, and second to propose MixTCP, a tool that integrates the neural network model and significantly enhances the regression testing experience from the software developer perspective. MixTCP is implemented in the Elixir programming language and employs the NEUTRON model, a state-of-the-art approach that uses neural networks to intelligently prioritize test cases, effectively improving fault detection and reducing testing time. The tool is composed of loosely coupled components (Mix TCP task, TCP Server, and NEUTRON model), thus enabling the integration of other Test Case Prioritization solutions too. The results show that MixTCP has the potential to be
a valuable asset to modern software development methods, offering software engineers a more efficient, a more user-friendly, and an overall easier to integrate TCP approach.
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