软件质量的模糊属性及其表示

软件质量是一个模糊的概念,其主要表现是：软件质量等级通常以某一质量特性的指标值来划分,然而用户对软件质量的评价却是模糊的,为了处理软件质量的模糊属性,提出了3种描述软件质量（子）特性的模糊表示方法,并给出了这些表示方法的示例。     

计算机软件质量模糊综合评价方法

软件产品质量是软件企业的生命 .本文通过对软件质量特性的分析 ,提出了软件质量的综合评价指标体系 ,并讨论怎样根据该指标体系收集有关数据 ,采用二级模糊综合评判法处理所得数据 ,得出定量评价结果 .     

基于模糊神经网络的软件质量评价方法

为了对计算机软件质量进行更加精确、客观、科学的评价,综合模糊逻辑推理的结构性知识表达能力和神经网络的自学习能力,提出一种基于模糊神经网络的软件质量评价方法。首先筛选软件质量评价的指标建立评价等级模糊级,然后利用神经网络的学习能力,通过网络的训练样本,确定评价中的变量参数;训练好的网络就可用来对软件质量进行评价。应用表明,该方法克服了由专家确定变量参数的缺点,达到评价结果更高的客观性、科学性,具有很高的应用价值。     

基于模糊神经网络的软件质量评价方法

为了对计算机软件质量进行更加精确、客观、科学的评价，综合模糊逻辑推理的结构性知识表达能力和神经网络的自学习能力，提出一种基于模糊神经网络的软件质量评价方法。首先筛选软件质量评价的指标建立评价等级模糊级，然后利用神经网络的学习能力，通过网络的训练样本，确定评价中的变量参数；训练好的网络就可用来对软件质量进行评价。应用表明，该方法克服了由专家确定变量参数的缺点，达到评价结果更高的客观性、科学性，具有很高的应用价值。     

基于投影的软件易用性评价方法

随着IT行业的不断发展,软件的易用性越来越受到用户和专家的关注与重视。如何科学地量化软件产品的易用性,进而对产品质量进行综合地测评,决定了软件产品的竞争力和用户的满意度。针对软件的易用性,提出了一种基于投影和直觉模糊理论的评价方法。首先,依据用户调查得到的信息,给出评价软件易用性的直觉模糊评价矩阵,并在此基础上建立了评价矩阵的理想决策。其次,借助群决策的框架,给出评价矩阵到理想决策上的投影。然后,基于投影给出测评软件的优劣序。最后,用一个测评实例展示出本方法的有效性和实用性。结果表明,本文提出的模型是一种软件质量综合评价的有效方法。     

ERP软件质量模糊综合评价方法

为给ERP软件供应商和应用ERP软件的企业提供一种定量的ERP软件质量评价方法,基于Waiters和McCall3层软件质量度量模型,建立了适用于ERP软件的质量评价模型。研究了运用模糊理论对ERP软件质量进行评价的方法。通过模糊运算获得了ERP软件质量的评价结果。通过一个典型ERP软件实例,验证了该方法的有效性和可行性。     

广义回归神经网络在软件质量预测中的应用

软件质量预测技术是软件质量评价体系中的关键技术,它能够对用户所关心的软件质量特性进行评价。广义回归神经网络在逼近能力、分类能力和学习速度方面具有较强优势。采用基于软件度量的广义回归神经网络构造质量预测模型能够从历史数据中寻找软件度量之间的相关关系。对软件缺陷数进行预测的实验说明了模型的有效性、精确性,实验结果令人满意。     

三角直觉模糊决策的权重函数方法

研究了属性值为三角直觉模糊数的多属性决策问题,提出了一种基于权重函数的决策方法。给出了三角直觉模糊数的定义、运算法则和截集;定义了三角直觉模糊数关于隶属函数和非隶属函数的精确值和模糊度,以及精确值的指标和模糊度的指标,给出了三角直觉模糊数的排序方法,并将其应用到属性值为三角直觉模糊数的多属性决策问题中;给出了属性值为三角直觉模糊数的多属性决策的步骤;通过数值算例分析和验证了该方法的有效性。     

软件质量方案模糊决策模型的研究

为了解决由于软件质量概念的模糊性而导致的软件质量方案决策困难的难题,从3个方面对软件质量方案模糊决策模型进行了研究.首先,采用L-R模糊数建立模糊权集,解决了经典决策方法存在的精确权集缺陷和模糊综合评价方法存在的伪模糊权集缺陷.其次,采用Bonissone方法简化了模糊运算.再者,采用模糊排序方法进行方案选择.从而全面提高了软件质量方案决策的准确性.最后,以一实例进行了验证.     

三角模糊数直觉模糊Bonferroni平均算子及其应用

针对决策信息为三角模糊数直觉模糊数(TFNIFN)且属性间存在相互关联的多属性群决策(MAGDM)问题,提出了一种基于三角模糊数直觉模糊加权Bonferroni平均(TFNIFWBM)算子的决策方法。首先,基于TFNIFN的运算法则和Bonferroni平均(BM)算子,定义了三角模糊数直觉模糊BM算子和TFNIFWBM算子;然后,研究了这些算子的一些性质,建立基于TFNIFWBM算子的MAGDM模型,结合排序方法进行决策。最后通过MAGDM算例验证了该算子的有效性与可行性。     

基于模糊推理的软件质量评价模型

通过成立由开发商、用户和评价方组成的专家组,在国际通用的软件质量评价标准和模糊综合评价的基础上,建立的模糊规则,利用模糊推理技术,寻求不同评价空间之间的映射,构建了基于模糊推理的软件质量评价模型。该模型符合人们在处理复杂问题的逻辑思维方式,有利于合理准确地评价软件质量。     

Evaluation of design requirements using fuzzy outranking methods

To increase customer satisfaction, quality function deployment is used to translate customer needs into technical design requirements (DRs). Determination of DRs for product development is very important because these requirements are the vital keys to successful products. The methods used to evaluate DRs in the literature can be categorized into multicriteria evaluation methods such as scoring methods, the analytic hierarchy method, analytic network process, and so forth. There are few papers using fuzzy multi‐attribute outranking methods to evaluate DRs. This article aims to compare the results of three different fuzzy outranking methods to evaluate the DRs in the PVC windows industry. A sensitivity analysis is also made by using the software, FOuR. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 1229–1250, 2007.     

A fuzzy regression and optimization approach for setting target levels in software quality function deployment

With the rapid development of the software industry, improving the quality of software development has gained increasing importance. Software manufacturers have recently applied quality improvement techniques to software development to respond to the needs for software quality. Software quality function deployment (SQFD), as a technique for improving the quality of the software development process to create products responsive to customer expectations, is used to maximize customer satisfaction. This paper presents a fuzzy regression and optimization approach to determine target levels in SQFD. The inherent fuzziness of relationships in SQFD modeling justifies the use of fuzzy regression. Fuzzy regression is used to identify the functional relationships between customer requirements and technical attributes, and among technical attributes. Then, a mathematical programming model is developed to determine target levels of technical attributes using the functional relationships obtained by fuzzy regression. A search engine quality improvement problem is presented to illustrate the application of the proposed approach.     

A design model of FBS based on interval-valued Pythagorean fuzzy sets

The FBS (Function-Behaviour-Structure) model is a research model that stimulates creative thinking of designers in the design process. In order to reduce the influence of user requirement ambiguity on design results in the product design process and improve the accuracy of user requirements in the function-behavior-structure (FBS) design model, this paper proposes an interval-valued Pythagorean fuzzy set-based FBS model integrating AHP and HOQ methods. Firstly, the design model will use IVPF-AHP method to study user requirements and use interval-valued Pythagorean linguistic terms to replace the traditional scoring method of AHP to get the weight of each user requirement. Secondly, the conversion between user requirements and functions will be realized by IVPF-HOQ method, which converts customer requirements into functional characteristics and calculates the weights of each functional characteristic. Finally, the design focus will be filtered according to the order of importance of the functional characteristics, which will be used as functions to guide the development of the FBS model. In this paper, the feasibility and effectiveness of the proposed method will be verified by an application example of a hand-held fluorescence spectrometer. The results show that the proposed FBS model can effectively reduce the subjectivity and ambiguity in the decision-making process, improve the accuracy and information richness of user requirements, and effectively highlight the focus of the design study. The innovation of the proposed method is to provide a more objective and accurate innovative design method for user requirements through the integration of AHP, HOQ and FBS to effectively explore and analyze user requirements. The use of IVPFS to deal with fuzzy information in the design process in a more flexible manner can reduce the ambiguity of requirements when user data is small, and effectively improve the limitations of the FBS design model which is more subjective.     

基于犹豫模糊集的软件质量评价模型

提出一种基于犹豫模糊集的软件质量评价模型。首先,根据专家打分,将犹豫模糊集与直觉模糊集相结合,得出软件质量特性的综合犹豫模糊评价矩阵;然后,通过计算犹豫模糊广义比较表,得出软件各质量属性得分;最后根据得分情况给出软件的质量排序。该模型较好地解决了专家对软件质量指标进行评价时的犹豫性问题。具体的案例分析表明,所提出的软件质量评价模型是可行、有效的。     

软件质量的模糊综合评判研究与应用

通过软件质量的模糊综合评估实践,首先分析了原模糊综合评判算法模型中以“取大取小”运算而使评估过程中产生大量有效信息丢失并导致评估结果出现过于简单化、绝对化的不足和缺陷,进而重点研究如何在保留原模糊综合评估算法良好结构的基础上将“取大取小”运算转变为矩阵乘法运算的改造,并以此建立适应现代软件质量综合评估需求的新算法模型实施软件质量的可计算化评估,提高了软件质量评估的准确性、实用性和可靠性。     

基于舰载装备军用软件典型的质量评价技术

阐述了军用软件发展现状,指出了研究软件评价技术[2]研究的重用性,并分析了三种常用的软件质量评价方法,提出了舰载装备军用软件质量评价模型.舰载装备军用软件质量评价模型评价的对象为软件研制过程产品,不针对软件研制过程的评价,专家组根据软件产品的质量需求,确定度量元和评价等级,并对度量元进行集体打分,利用加权和的方法算出被评软件质量分数.文章提出的软件质量评价模型是为了保证产品能提供用户所要求的质量,及满足用户(包括操作人员、维护人员)明确的或隐含的要求.     

A combined fuzzy linear regression and fuzzy multiple objective programming approach for setting target levels in quality function deployment

Quality function deployment (QFD) is a systematic process for translating customer needs into engineering characteristics, and then communicating them throughout the enterprise in a way to ensure that details are quantified and controlled. The inherent fuzziness of relationships in QFD modeling justifies the use of fuzzy regression for estimating the relationships between both customer needs and engineering characteristics, and among engineering characteristics. Albeit QFD aims to maximize customer satisfaction, requirements related to enterprise satisfaction such as cost budget, extendibility, and technical difficulty also need to be considered. This paper presents a fuzzy multiple objective decision framework that includes not only fulfillment of engineering characteristics to maximize customer satisfaction, but also maximization of extendibility and minimization of technical difficulty of engineering characteristics as objectives subject to a financial budget constraint to determine target levels of engineering characteristics in product design. A real-world quality improvement problem is presented to illustrate the application of the decision approach.     

A hybrid methodology of fuzzy grey relation for determining multi attribute customer preferences of edible oil

The main idea behind this study is to introduce a fuzzy grey relational methodology (FGRM) to determine the importance of customer attributes’ (CAs) for edible oil, particularly for defining the opportunity of competitiveness which has recently become one of an important concern of manufacturing companies. It was also aimed to seek high quality level of product and process characteristics for meeting the desirability of attributes and for health care. A fuzzy grey inference system was employed with the support of fuzzy quality function (QFD) deployment to interpret the qualitative and imprecise customer attributes. Fuzzy QFD is relatively a recent methodology offering a more in-depth analysis and investigation into the handling of customer requirements and engineering characteristics. The attributes then were defuzzified into quantitative values by amalgamating the knowledge of the customers and the product designers.Customer needs (CNs) are the voice of customers and tend to be linguistic naturally. In this study, fuzzy inference system (FIS) along with fuzzy QFD was employed to determine the desirability of edible oil by consumers. Fuzzy QFD is a powerful tool for improving product design and quality, and procuring a customer-driven quality system. The integrated framework based on FIS, fuzzy QFD and FGRM determined the CAs relations, and desirability level of edible oil by consumers. The findings are not only meaningful for customers, but also important for market position of product. The methodology significantly reduces the complexity of decision making and increase the production efficiency and overall competitiveness.     

基于置信度的软件质量模糊评价模型研究

通过软件质量模糊综合评价实践和对模糊综合评价模型算法的分析,重点研究了在模糊综合评价算法的基础上进行改进并引入置信度进行置信分析的新方法,建立了适合系统化应用的软件质量评价模型,并使用该模型实施软件质量结果评价.由于应用模糊综合模型会产生大量有效信息丢失,从而导致评价结果过于简单化、绝对化,该模型解决了这一不足,并提高了软件质量评价的客观性和准确性.