基于CMM IDEAL模型的中小型企业软件过程改进的方法探究

当前国内中小型软件企业面临的一个重大问题是如何提高软件质量。目前,通过实施CMM来改进软件过程．是提高软件质量的一个有效途径。首先探讨了CMM过程改进的适用范围。基于SEI提出的用于组织过程改进的IDEAL模型。通过对当前国内中小型企业所面临的一些问题的分析,提出了一种适用于国内中小型软件企业的过程改进方法。为企业实施软件过程改进提供了参考思路。     

基于CMM的中小型企业的软件项目管理模型研究

本文以中小型软件企业为研究对象,分析了中小型软件企业软件过程管理存在的问题,提出了一个基于CMM可重复级（2级）的软件项目管理模型,并给出了模型各实施阶段的主要工作和需要注意的问题,对我国中小企业的小型软件项目开发及过程改进具有借鉴意义。     

基于MDA技术的软件过程改进研究

模型驱动架构(MDA)是OMG提出的基于模型驱动(MD)思想的新的方法学。文中在分析和总结中小型软件企业运用MDA技术进行软件开发的基础上,结合软件过程改进的实践经验,提出了基于MDA技术的中小型软件企业过程改进模型。该模型为中小型企业采用MDA技术进行软件开发提出了相应的过程改进模型。企业还可以根据自身的情况对该模型进行裁剪,以便使该模型更加贴近企业的需要。     

一种目标与信息共同驱动的度量模型

目前采用CMMI模型进行过程改进的企业，尤其是中小型企业在实施度量时盲目选择度量元，缺少合适度量过程框架的指导。针对上述问题，结合现有的GQM度量模型及其改进模型,以及PSM实用软件度量模型的特点,提出了一种支持软件过程改进的目标和信息共同驱动的度量模型（GI2M-D）,给出了基于GI2M-D度量模型的软件度量过程框架。该框架使度量人员选取度量元时更有针对性和目的性,为决策者和软件过程改进者，特别是采用CMMI模型的企业在实施度量时提供有效的支持和指导。     

基于MDA技术的软件过程改进研究

模型驱动架构（MDA）是OMG提出的基于模型驱动（MD）思想的新的方法学。文中在分析和总结中小型软件企业运用MDA技术进行软件开发的基础上，结合软件过程改进的实践经验，提出了基于MDA技术的中小型软件企业过程改进模型。该模型为中小型企业采用MDA技术进行软件开发提出了相应的过程改进模型。企业还可以根据自身的情况对该模型进行裁剪，以便使该模型更加贴近企业的需要。     

论软件质量保证

不用实施CMM，不用引进RUP(Rational Llnified Process)，在中小型软件企业如何实施软件过程改进，以提高软件开发质量。这是值得探讨的问题。本文通过在企业内部实施文档模板化、加强技术评审和适当地引进辅助工具三个方面，讨论针对中小型企业的薄弱环节实施质量改进方法，切实降低了项目风险，保证了软件开发质量。本文还着重阐述了如何进行技术评审而不流于形式、走过场以及如何有针对性地引入辅助工具来提高开发和管理工作的效率，对于中小型软件企业在规范公司内部开发过程、提高软件质量和降低项目风险等方面，有一定的借鉴作用。     

浅析中小型软件企业如何运用CMM进行过程改进

对我国中小型软件企业而言,引入能力成熟度模型CMM改进软件过程是保证软件产品质量的关键,是适应市场激烈竞争的需求。通过分析软件企业运用CMM进行过程改进的必要性,对运用CMM改进软件过程的关键步骤做了研究,提出了我国中小型软件企业运用CMM进行过程改进的解决方案。     

基于CMM的中小软件企业过程改进实施方案研究

随着软件工程化进程的推进,各种过程改进模型和方法层出不穷。针对如何将软件能力成熟度模型CMM与我国中小型软件组织相融合这一问题,对CMM中的各关键实践进行了裁剪和重定位。结合软件开发的迭代增量模型,将软件开发过程分为先启阶段、精化阶段、构造阶段和产品提交等阶段,并将需求管理、项目规划管理和项目监控等管理活动与软件开发过程相结合,提出了一种基于CMM模型的适合国内中小型企业的过程改进方案,实践证明了此方案的可行性及经济性。     

基于CMM2过程改进模型的软件实训项目管理系统的研究

本文根据目前中小型软件企业项目管理的实际状况,以及高职院校软件人才培养的定位,提出并分析了CMM2模型,并将该模型进行改进,提出了一个可实施的,运用在软件实训项目管理系统中的方案。     

中小型软件企业知识管理的研究

越来越多的我国中小型软件企业认识到员工的知识是企业最有价值的资产，而且在企业中实施知识管理是十分必要的。首先概括了这些企业在知识管理方面的现状，提出了一个适用于中小型软件企业的知识管理体系，说明了知识管理与CMM／CMMI的关系，并给出了知识管理与软件过程管理的结合模型，介绍了一个软件企业知识管理系统的模型框架，分享了实施知识管理的一些经验。     

基于CMMI的软件质量保证

软件的质量保证是软件业最关注的一个问题。结合软件质量保证体系的国内外现状,以CMMI标准体系的优点与5级成熟度模型为依据,分析出过程是软件项目质量保证的制约因素以及基于CMMI的软件质量保证的具体内容。详细探讨了CMMI模型下项目计划开展与开发流程的问题。最后得出通过过程改进达到管理提高的目的,最终使得软件质量有所保证,结果减低企业的工程成本。该方法不仅适用于规模较大的组织和较大型的项目,而且也可以广泛应用于相当多的小型组织。     

A tool environment for quality assurance based on the Eclipse Modeling Framework

The paradigm of model-based software development has become more and more popular since it promises an increase in the efficiency and quality of software development. Following this paradigm, models become primary artifacts in the software development process. Therefore, software quality and quality assurance frequently leads back to the quality and quality assurance of the involved models. In our approach, we propose a model quality assurance process that can be adapted to project-specific and domain-specific needs. This process is based on static model analysis using model metrics and model smells. Based on the outcome of the model analysis, appropriate model refactoring steps can be performed. In this paper, we present a tool environment conveniently supporting the proposed model quality assurance process. In particular, the presented tools support metrics reporting, smell detection, and refactoring for models being based on the Eclipse Modeling Framework, a widely used open source technology in model-based software development.     

基于EPMM的软件过程模型规范化研究

为了开发高质量的软件过程模型,有必要对软件过程模型的规范化进行研究。本文基于EPMM对过程的形式化定义,考虑到传统软件过程和软件演化过程的特点,给出过程第一范式(1PNF)、过程第二范式(2PNF)、过程第三范式(3PNF)和过程第四范式(4PNF)的定义,并给出它们的判定算法。本文建议:对于传统的软件过程模型,应设计到满足2PNF;而对于软件演化过程模型,应设计到满足3PNF。本文为建模高质量的软件过程模型提供了指南。     

Behavioral economics in software quality engineering

This article describes empirical research results regarding the “history effect” in software quality evaluation processes. Most software quality models and evaluation processes models assume that software quality may be deterministically evaluated, especially when it is evaluated by experts. Consequently, software developers focus on the technical characteristics of the software product. A similar assumption is common in most engineering disciplines. However, in regard to other kinds of goods, direct violations of the assumption about objective evaluation were shown to be affected by the consequences of cognitive processes limitations. Ongoing discussion in the area of behavioral economics raises the question: are the experts prone to observation biases? If they are, then software quality models overlook an important aspect of software quality evaluation. This article proposes an experiment that aims to trace the influence of users’ knowledge on software quality assessment. Measuring the influence of single variables for the software quality perception process is a complex task. There is no valid quality model for the precise measurement of product quality, and consequently software engineering does not have tools to freely manipulate the quality level for a product. This article proposes a simplified method to manipulate the observed quality level, thereby making it possible to conduct research. The proposed experiment has been conducted among professional software evaluators. The results show the significant negative influence (large effect size) of negative experience of users on final opinion about software quality regardless of its actual level.     

The impacts of quality and productivity perceptions on the use of software process improvement innovations

Numerous software process improvement (SPI) innovations have been proposed to improve software development productivity and system quality; however, their diffusion in practice has been disappointing. This research investigates the adoption of the Personal Software Process on industrial software projects. Quantitative and qualitative analyses reveal that perceived increases in software quality and development productivity, project management benefits, and innovation fit to development tasks, enhance the usefulness of the innovation to developers. Results underscore the need to enrich current technology acceptance models with these constructs, and serve to encourage project managers to adopt formal SPI methods if developers perceive the methods will have positive impacts on their productivity and system quality.     

Productivity paradoxes revisited

The adoption of quality assurance methods based on software process improvement models has been regarded as an important source of variability in software productivity. Some companies perceive that their implementation has prohibitive costs, whereas some authors identify in their use a way to comply with software development patterns and standards, produce economic value and lead to corporate performance improvement. In this paper, we investigate the relationship between quality maturity levels and labor productivity, using a data set containing 687 Brazilian software firms. We study here the relationship between labor productivity, as measured through the annual gross revenue per worker ratio, and quality levels, which were appraised from 2006 to 2012 according to two distinct software process improvement models: MPS.BR and CMMI. We perform independent statistical tests using appraisals carried out according to each of these models, consequently obtaining a data set with as many observations as possible, in order to seek strong support for our research. We first show that MPS.BR and CMMI appraised quality maturity levels are correlated, but we find no statistical evidence that they are related to higher labor productivity or productivity growth. On the contrary, we present evidence suggesting that average labor productivity is higher in software companies without appraised quality levels. Moreover, our analyses suggest that companies with appraised quality maturity levels are more or less productive depending on factors such as their business nature, main origin of capital and maintained quality level.     

An ant colony optimization algorithm to improve software quality prediction models: Case of class stability

Context

Assessing software quality at the early stages of the design and development process is very difficult since most of the software quality characteristics are not directly measurable. Nonetheless, they can be derived from other measurable attributes. For this purpose, software quality prediction models have been extensively used. However, building accurate prediction models is hard due to the lack of data in the domain of software engineering. As a result, the prediction models built on one data set show a significant deterioration of their accuracy when they are used to classify new, unseen data.

Objective

The objective of this paper is to present an approach that optimizes the accuracy of software quality predictive models when used to classify new data.

Method

This paper presents an adaptive approach that takes already built predictive models and adapts them (one at a time) to new data. We use an ant colony optimization algorithm in the adaptation process. The approach is validated on stability of classes in object-oriented software systems and can easily be used for any other software quality characteristic. It can also be easily extended to work with software quality predictive problems involving more than two classification labels.

Results

Results show that our approach out-performs the machine learning algorithm C4.5 as well as random guessing. It also preserves the expressiveness of the models which provide not only the classification label but also guidelines to attain it.

Conclusion

Our approach is an adaptive one that can be seen as taking predictive models that have already been built from common domain data and adapting them to context-specific data. This is suitable for the domain of software quality since the data is very scarce and hence predictive models built from one data set is hard to generalize and reuse on new data.     

End-to-end defect modeling

In this context, computer models can help us predict outcomes and anticipate with confidence. We can now use cause-effect modeling to drive software quality, moving our organization toward higher maturity levels. Despite missing good software quality models, many software projects successfully deliver software on time and with acceptable quality. Although researchers have devoted much attention to analyzing software projects' failures, we also need to understand why some are successful - within budget, of high quality, and on time-despite numerous challenges. Restricting software quality to defects, decisions made in successful projects must be based on some understanding of cause-effect relationships that drive defects at each stage of the process. To manage software quality by data, we need a model describing which factors drive defect introduction and removal in the life cycle, and how they do it. Once properly built and validated, a defect model enables successful anticipation. This is why it's important that the model include all variables influencing the process response to some degree.     

Using model transformation to refactor use case models based on antipatterns

Use Case modeling is a popular technique for documenting functional requirements of software systems. Refactoring is the process of enhancing the structure of a software artifact without changing its intended behavior. Refactoring, which was first introduced for source code, has been extended for use case models. Antipatterns are low quality solutions to commonly occurring design problems. The presence of antipatterns in a use case model is likely to propagate defects to other software artifacts. Therefore, detection and refactoring of antipatterns in use case models is crucial for ensuring the overall quality of a software system. Model transformation can greatly ease several software development activities including model refactoring. In this paper, a model transformation approach is proposed for improving the quality of use case models. Model transformations which can detect antipattern instances in a given use case model, and refactor them appropriately are defined and implemented. The practicability of the approach is demonstrated by applying it on a case study that pertains to biodiversity database system. The results show that model transformations can efficiently improve quality of use case models by saving time and effort.     

贝叶斯网络技术在软件测试过程中的应用研究

为使软件测试管理者准确定义并把握软件测试过程中存在大量复杂的相互依赖、相互影响的关系,通过对有经验的测试人员在软件测试过程中的主观判断和从以往客观数据抽象出来的关系进行分析,用贝叶斯网络技术对其建模,并对模型中的关系量化,从而可以利用模型辅助测试过程进行管理,包括进行计划、决策和对软件产品的质量进行预测等.