Software project development is very crucial, and measuring the exact cost and effort of development is becoming tedious and challenging. Organizations are trying to wind up their project of software development within the agreed budget and schedule successfully. Traditional practices are inadequate to achieve the current needs of the software industry. Underestimation and overestimation of software development effort lead to financial implications in the form of resources, cost of staffing, and budget of developing the software project. Soft computing (SC) approaches and tools deliver an addition of techniques for anticipating resistance to the deception, defect, incomplete truth for traceability and ambiguity, low arrangement cost, and strength. A large amount of SC approaches is prevailing in the literature to accomplish way-out to difficulties precisely, practically, and speedily. The approaches of SC can give better prediction, high performance, and dynamic behavior. SC deals with computational intelligence which integrates the concept of agent paradigm and SC. The proposed study presents a systematic literature review (SLR) of the approaches, tools, and techniques of SC used in the literature. The study presented a comprehensive review by searching the defined keywords in the popular libraries, filtered the paper, and obtained most relevant papers. After the selection of the papers, the quality assessment process of the included papers has been done in order to determine the relevancy of the papers. The study will help researchers in the area of research to devise novel ideas and solutions to overcome the existing issue on the basis of this study as evidence of the literature.

中文翻译：

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用于软件过程改进的软计算和决策支持系统：系统文献综述

软件项目开发非常重要，衡量开发的确切成本和工作量变得乏味和具有挑战性。组织正试图在商定的预算和时间表内成功地结束他们的软件开发项目。传统做法不足以满足软件行业的当前需求。低估和高估软件开发工作会导致资源、人员成本和软件项目开发预算等方面的财务影响。软计算 (SC) 方法和工具提供了额外的技术，用于预测对欺骗、缺陷、可追溯性和歧义的不完整真相、低安排成本和强度的抵抗力。大量的SC方法在文献中普遍存在，以精确、实用、快速地解决困难。SC 的方法可以提供更好的预测、高性能和动态行为。SC 处理集成了代理范式和 SC 概念的计算智能。拟议的研究对文献中使用的 SC 的方法、工具和技术进行了系统的文献综述 (SLR)。该研究通过在流行图书馆中搜索定义的关键字、过滤论文并获得最相关的论文来进行全面审查。论文入选后，对纳入论文进行质量评估，以确定论文的相关性。