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The research is devoted to the development of the formalized and ontological models of the software quality according to ISO 25010. These models provide the possibility of the formalization of the software quality assessment according to ISO 25010. This standard would benefit from a formal description. The paper proves that information sufficiency is a critical aspect of software quality assessment. The methods and system of evaluating the sufficiency of the information for software quality assessment according to ISO 25010 are developed. The developed methods and tools provide the increasing the veracity of software quality assessment. The conducted experiments confirm that the developed methodology of evaluating the sufficiency of information for software quality assessment increased the veracity of the software quality assessment in 12% for the automated system for large-format photo print.

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This paper proves the dependence of successful of software project implementation on the software requirements specification (SRS), the actuality and importance of the skill to evaluate the possible success of software project based on the specifications. The neural network model of prediction of the software project characteristics for evaluating the success of its implementation based on analysis of specifications is first time proposed and implemented in Matlab. ConclusionThe proposed model provides prediction of the success of software projects implementation based only on the SRS and provides complex comparison of software projects taking into account of the predicted values of the main characteristics of the software project. The evaluations of all main characteristics, provided by ANN, help to "cut off" the software projects with failed SRS. The results of project development confirmed the ANN results.