一种需求文档质量评估模型的研究

需求是软件开发的基础,而需求文档的质量直接关系到软件产品的质量.本文在分析了需求文档的11个质量属性之后,针对那些客观可度量的属性,提出了一套需求文档质量评估模型.该模型从5个基于统计的度量对需求文档的质量进行评估.用该模型对既往项目的需求文档进行了全面的评测,结果从一定程度上正确反映了软件需求文档的质量.     

类设计质量评估方法的研究

详细介绍了C&K度量方法,结合灰色关联分析的相关理论,提出了一种基于C&K度量方法和灰色关联分析的类设计质量评估方法。依据C&K度量阈值及可接受类的定义,可以推导出面向对象程序设计中的最佳类设计标准。将各个类与最佳类设计标准进行灰色关联分析,从而评估类设计质量的优劣。该方法为程序设计人员提供了类设计质量优劣的判定依据,并保证其在软件生命周期的早期阶段及时发现设计质量低劣的类并做相应的处理,避免后期开发的软件产品出现故障,能显著提高软件产品的可靠性和可维护性。     

基于模糊层次分析法的软件易用性过程综合评价方法

对软件易用性过程进行综合评价是开发可信软件产品的必要因素。通过构建软件易用性生命周期模型和软件易用性度量模型搭建软件易用性过程综合评价模型, 通过此模型对软件开发中的易用性问题进行有效的指导, 规范易用性开发过程, 从而保证能够产出高易用性的产品; 利用模糊层次分析法对此模型进行度量评价, 量化评估易用性过程优劣; 通过一个实例分析说明该方法可以有效地应用于软件开发过程中, 能够尽早地确保软件产品的易用性, 为开发高易用度的软件产品指明了方向。     

CMM用于评估CAD软件有新进展

CMM(Capability Maturity Model for Software)是软件能力成熟度模型 .该模型是由美国卡内基 -梅隆大学软件工程研究所制定 ,在世界范围推广实施的一种软件评估标准 ,主要用于对软件产品的测试 ,以促进软件产品走向成熟、规范 .CMM评估包括 6个模型、5个等级、18个过程域、5 2个目标和 30 0多个关键实践 .评估过程包括员工培训 (含企业高层领导 )、问卷填写和统计、文档审查、数据分析、撰写评估报告等 ,一个评估周期约需 12— 30个月 ,评估结果由主任评估师签字生效 .目前 ,全球一级 CMM评估企业只有 10多家 ,主任评估师 30 0多人 ,…     

元数据驱动的数据质量评估体系架构研究

到目前为止,国际上既没有形成系统化的数据质量评估标准,也没有建立完整的数据质量评估体系。通过对国际和国内数据质量相关内容的研究,分析了大型企业对数据质量的需求,提出了一个数据质量元模型框架结构,构建了数据质量评估体系。该体系包括数据质量的分类和定义、数据质量评估指标算法和数据质量评估体系及流程,为企业对数据质量进行评估提供了可靠的依据。     

PDCA循环在软件质量管理中的应用

为了加强软件产品的质量,提高软件质量管理的水平;在软件质量管理活动中应用PDCA（Plan,Do,Check,Action）循环理论,并建立软件质量管理的PDCA循环模型,在此基础上根据软件产品的特点提出了具体的PDCA循环步骤;实际应用效果表明,软件质量管理的PDCA循环模型不仅可以提升软件产品的质量以及软件企业的质量管理水平,还可以降低软件开发成本、提高软件开发效率。     

基于模式的软件质量模型研究与应用

在软件开发周期中的早期进行质量评估对提高软件的质量非常重要.传统的软件质量模型在早期获得的质量信息较少,很难有效、准确地评价软件的质量.针对此问题,本文提出了一种新的基于模式的软件质量模型,通过模式提供的丰富信息,在产品的设计阶段完成对软件质量准确、有效的评估,指导软件的开发,最终提高软件产品的质量.     

面向服务的过程引擎模型设计

随着大规模软件的出现,软件质量成为软件行业倍受关注的重点问题之一。在基于一种粗粒度松耦合的面向服务体系结构,构建了一个主动过程引擎系统模型。该模型既可以完成软件开发过程的定义、解析和组装,也提供软件过程的主动执行和行为监控,同时也支持软件过程的演化,从项目的整体过程保证软件开发任务的顺利完成和软件产品质量。     

基于产品线体系结构的软件工程过程模型研究

在借鉴现代工业的组织体系、管理规范、生产流程的基础上,针对基于软件产品线体系结构的软件工程方法和开发过程进行了系统研究,提出了基于产品线体系结构而实现软件工程化生产的N-生命周期模型.该模型的建立,对研究基于软件产品线体系结构的集成化软件工程环境,进而实现软件产品的工业化生产是非常有益且重要的.     

军用软件质量特性和设计属性的研究

提出了软件的“可视性、可测性和可维性”是军用软件产品基本的质量特性和设计属性的概念及软件“可视性、可测性和可维性”应作为评定军作软件产品的质量和技术状态的前提条件和基础的观点。基于以上概念和观点,给出了“可视性、可测性和可维性”的定义、工程意义和成熟度模型,以解决军用软件定型过程中的“评定难、测试难和定型的软件产品以服务部队”等问题。     

Model-based verification of quantitative non-functional properties for software product lines

Evaluating quality attributes of a design model in the early stages of development can significantly reduce the cost and risks of developing a low quality product. To make this possible, software designers should be able to predict quality attributes by reasoning on a model of the system under development. Although there exists a variety of quality-driven analysis techniques for software systems, only a few work address software product lines. This paper describes how probabilistic model checking techniques and tools can be used to verify non-functional properties of different configurations of a software product line. We propose a model-based approach that enables software engineers to assess their design solutions for software product lines in the early stages of development. Furthermore, we discuss how the analysis time can be surprisingly reduced by applying parametric model checking instead of classic model checking. The results show that the parametric approach is able to substantially alleviate the verification time and effort required to analyze non-functional properties of software product lines.     

Architectural-level risk analysis using UML

Risk assessment is an essential part in managing software development. Performing risk assessment during the early development phases enhances resource allocation decisions. In order to improve the software development process and the quality of software products, we need to be able to build risk analysis models based on data that can be collected early in the development process. These models will help identify the high-risk components and connectors of the product architecture, so that remedial actions may be taken in order to control and optimize the development process and improve the quality of the product. In this paper, we present a risk assessment methodology which can be used in the early phases of the software life cycle. We use the Unified Modeling Language (UML) and commercial modeling environment Rational Rose Real Time (RoseRT) to obtain UML model statistics. First, for each component and connector in software architecture, a dynamic heuristic risk factor is obtained and severity is assessed based on hazard analysis. Then, a Markov model is constructed to obtain scenarios risk factors. The risk factors of use cases and the overall system risk factor are estimated using the scenarios risk factors. Within our methodology, we also identify critical components and connectors that would require careful analysis, design, implementation, and more testing effort. The risk assessment methodology is applied on a pacemaker case study.     

Construction of a Systemic Quality Model for Evaluating a Software Product

Quality is currently considered one of the main assets with which a firm can enhance its competitive global position. This is one reason why quality has become essential for ensuring that a company's products and processes meet customers' needs. A recent innovation in the systems area is the development of a set of mechanisms and models for evaluating quality. This article describes the design of a Quality Model with a systemic approach to software products that assesses a product's efficiency and effectiveness. Different quality models were studied: McCall, Boehm, FURPS, ISO 9126, Dromey, ISO 15504 in an attempt to identify the aspects present in these models that are deemed important in a Systemic Quality model. We designed a model prototype that reflects the essential attributes of quality. This model was evaluated using a method so it can be validated and also enhanced. The evaluation method consisted of: designing a survey, formulating, validating and applying the measurement instruments; defining an algorithm to obtain the quality estimate and analyzing the results. The model prototype enabled the strengths and weaknesses of the software products studied to be identified. When evaluating a software product using the model prototype, it was possible to ascertain its compliance with the standards and use the results to improve it. Since the evaluation was systemic, processes that affect certain characteristics of the product could be identified. Companies can benefit from the model proposed because it serves as a benchmark that allows their products to evolve and be competitive.     

A software product certification model

Certification of software artifacts offers organizations more certainty and confidence about software. Certification of software helps software sales, acquisition, and can be used to certify legislative compliance or to achieve acceptable deliverables in outsourcing. In this article, we present a software product certification model. This model has evolved from a maturity model for product quality to a more general model with which the conformance of software product artifacts to certain properties can be assessed. Such a conformance assessment we call a ‘software product certificate’. The practical application of the model is demonstrated in concrete software certificates for two software product areas that are on different ends of the software product spectrum (ranging from a requirements definition to an executable). For each certificate, a concrete case study has been performed. We evaluate the use of the model for these certificates. It will be shown that the model can be used satisfactorily for quite different kinds of certificates.     

业务流程模型中生成特征模型方法的研究

目前的软件产品系统中,由于现有的造型系统研究的只是单一系统的开发,因此使用现有的方法进行特征造型时就会导致最终开发出来的产品的质量和产量比较低。通过使用增加产品复用性的软件产品线,提出了从业务流程模型中生成特征模型的方法。该方法通过使用重叠操作算法,将业务流程中相似的功能编成一个用例组,清晰地显示了业务流程中的共性和差异性,从而为整个业务流程实现了软件化,提高了产品的质量和产量。     

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.     

Improving quality of software product line by analysing inconsistencies in feature models using an ontological rule‐based approach

In software product line engineering, feature models (FMs) represent the variability and commonality of a family of software products. The development of FMs may introduce inaccurate feature relationships. These relationships may cause various types of defects such as inconsistencies, which deteriorate the quality of software products. Several researchers have worked on the identification of defects due to inconsistency in FMs, but only a few of them have explained their causes. In this paper, FM is transformed to predicate‐based feature model ontology using Prolog. Further, first‐order logic is employed for defining rules to identify defects due to inconsistency, the explanations for their causes, and suggestions for their corrections. The proposed approach is explained using an FM available in Software Product Line Online Tools repository. It is validated using 26 FMs of discrete sizes up to 5,543 features, generated using the FeatureIDE tool and real‐world FMs. Results indicate that the proposed methodology is effective, accurate, and scalable and improves software product line.     

Quality-aware analysis in product line engineering with the orthogonal variability model

Software product line engineering is about producing a set of similar products in a certain domain. A variability model documents the variability amongst products in a product line. The specification of variability can be extended with quality information, such as measurable quality attributes (e.g., CPU and memory consumption) and constraints on these attributes (e.g., memory consumption should be in a range of values). However, the wrong use of constraints may cause anomalies in the specification which must be detected (e.g., the model could represent no products). Furthermore, based on such quality information, it is possible to carry out quality-aware analyses, i.e., the product line engineer may want to verify whether it is possible to build a product that satisfies a desired quality. The challenge for quality-aware specification and analysis is threefold. First, there should be a way to specify quality information in variability models. Second, it should be possible to detect anomalies in the variability specification associated with quality information. Third, there should be mechanisms to verify the variability model to extract useful information, such as the possibility to build a product that fulfils certain quality conditions (e.g., is there any product that requires less than 512?MB of memory?). In this article, we present an approach for quality-aware analysis in software product lines using the orthogonal variability model (OVM) to represent variability. We propose to map variability represented in the OVM associated with quality information to a constraint satisfaction problem and to use an off-the-shelf constraint programming solver to automatically perform the verification task. To illustrate our approach, we use a product line in the automotive domain which is an example that was created in a national project by a leading car company. We have developed a prototype tool named FaMa-OVM, which works as a proof of concepts. We were able to identify void models, dead and false optional elements, and check whether the product line example satisfies quality conditions.     

基于USDP的软件质量控制

在研究软件质量控制的过程中，CMM是一个很重要的成果。作为一种框架性标准，并不具备可操作性，需要结合一种具体的可操作性过程来实现CMM。在统一建模语言UML的基础上产生了统一软件开发过程USDP。为了达到软件过程控制软件质最的目的。在基于USDP实现了CMM可重复级基础上给出了简化的企业软件过程模型，试图为企业软件过程的确立提供基础。