预测软件开发生命周期模型的深度学习方法

Jainam Dhami, Nishant Dave, Onkar Bagwe, Abhijit Joshi, Prachi Tawde
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引用次数: 0

摘要

软件开发生命周期(SDLC)是一个定义良好的、系统的过程,用于开发优先考虑质量的软件。它由多种可供选择的模型组成,这些模型以多种方式相互区分。作为项目开发人员,必须根据即将到来的软件需求,从这些SDLC模型中选择一个特定的模型。这引发了为软件开发选择最合适的模型的需求,以便简化整个软件构建过程,坚持模型定义的指导方针及其时间轴。本文提出了一种基于深度学习的方法,通过根据用户的需求推荐最合适的SDLC模型,使SDLC模型选择过程自动化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep Learning Approach To Predict Software Development Life Cycle Model
The Software Development Life Cycle (SDLC) is a well-defined, methodical procedure for developing software that prioritizes quality. It consists of a variety of models to choose from, which differentiate among themselves in multiple ways. As a project developer, one has to choose a particular model from these SDLC models according to the forthcoming software’s requirements. This initiates a need for choosing the most appropriate model for the development of the software, so as to streamline the entire software building process, adhering to the model’s defined guidelines and its timeline. This paper presents a deep learning-based approach that automates the SDLC model selection process by recommending the most appropriate SDLC model as per the users’ requirements.
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