A multi-dimensional software project health assessment method based on convolutional neural network

A convolutional neural network, software project technology, applied in the field of multi-dimensional software project health assessment, can solve the problem of ignoring important quality assessment data and other problems

Active Publication Date: 2022-03-29
北京中软国际信息技术有限公司
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Problems solved by technology

However, most of the current software quality assessment methods only focus on the quality of software products, such as measuring the reliability and security of software systems through codes, but ignore some important quality assessment data in other dimensions in the entire software development process.

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  • A multi-dimensional software project health assessment method based on convolutional neural network
  • A multi-dimensional software project health assessment method based on convolutional neural network
  • A multi-dimensional software project health assessment method based on convolutional neural network

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Embodiment Construction

[0065] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0066] This embodiment provides a method for assessing the health of a multi-dimensional software project based on a convolutional neural network, the main steps of which are: artificially defining a software project health model (Factor-Criteria-Metrics , FCM) framework; collect the development data of historically completed software projects, and calculate the metric value of each project based on the health metrics (Metrics) defined in the FCM model framework; The mutual evaluation and scoring of the two parties calculates the scores of each element and the total health score of each completed project; based on the software project data obtained from the above calculati...

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Abstract

The invention relates to a multi-dimensional software project health assessment method based on convolutional neural network, including: defining the structure of the FCM model framework; collecting the development source data of completed historical software projects according to the FCM model framework, and calculating the measurement element value; using the mutual evaluation of the completed historical software project during acceptance, the comprehensive health score and the multi-dimensional element health score of each completed historical software project are calculated; the one-dimensional convolutional neural network model is used to calculate the The weight of the model is used for training; the linear regression model is used to train the weight of the comprehensive health sub-model; the appropriate FCM model is selected to calculate the metric element of the software item to be evaluated, and the software item health score is calculated by using the FCM model. The invention can perform fair and objective automatic evaluation of the health degree of software items in a large-scale crowdsourcing platform system, and has the characteristics of high efficiency and high accuracy.

Description

technical field [0001] The present invention relates to a method for evaluating the health degree of a multi-dimensional software project, in particular to a method for evaluating the health degree of a multi-dimensional software project based on a convolutional neural network. Background technique [0002] Software project health and quality assessment methods are very important research areas in software engineering. A set of good software project health evaluation methods can effectively evaluate the health and quality of software projects in progress systematically and comprehensively, provide necessary quality references for project monitors and software acceptance personnel, and provide timely support for software developers. Identifying problems and continuously improving software development practices provides the means to ultimately ensure project success. [0003] However, with the continuous increase in software size and complexity, some current software quality ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/06G06N3/04
CPCG06Q10/0639G06N3/045
Inventor 韩鹏钱卫春潘高展王红
Owner 北京中软国际信息技术有限公司
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