Automated test control of software systems using neural networks
Abstract
Automated test control of software systems using neural networks
Incoming article date: 12.11.2018The article is devoted to solving the actual problem of improving the efficiency of software testing based on the development of an automated control system for this process. The structure of the created system is proposed, which allows specialists to form the advising effects for the best implementation of each of the software testing stages. Optimization models are presented that ensure the correct selection of the values of various attributes of test plans, test cases, defect reports and other documents created during the testing process. The structure of the neural network and the concept of its application for the most accurate selection of attribute values are described. The research is supported by a stipend of the President of the Russian Federation to young scientists and post-graduate students (No. SP-100.2018.5), which was assigned by the grants Council of the President of the Russian Federation.
Keywords: software testing, optimization methods, automated control system, neural networks, test coverage