SOFTWARE TESTING RESULTS ANALYSIS FOR THE REQUIREMENTS CONFORMITY USING NEURAL NETWORKS

The relevance of scientific work lies in the need to improve existing software designed analyze compliance results testing ofthe stated requirements. For implementation this goal, neural networks can be used by quality control specialists make decisions aboutsoftware quality, or project managers as an expert system, for one indicators customer. article deals with testingwhich is a process validation and verification application business program technical requirements thatguided its design development, expected, identifies important errors deficiencies classified severity befixed. Existing systems do not provide have only partial integration analysis requirements, which should ensurethe formation assessment opportunity justify product. Thus, data processing model based on afuzzy network was proposed. An approach allow determining developed functional non-functionalrequirements proposed, taking into account how successfully unsuccessfully implemented that requirement. ultimate goal ofscientific development algorithmic support thedecisions taken. following tasks are solved work: advantages disadvantages using when workingwith requirements; definition general structure classification characteristic main features use neuralnetworks; designing architecture, module research conformity