A quantitative model for the support of software management

The software production and maintenance management support project (SPMMS) will define and produce a complete, consistent and efficient information system supporting all management activities in the life cycle of software.Adequate management of the production and maintenance of software can be achieved only with the support of quantitative analysis. This analysis must examine all attributes of the process by which software is developed and maintained. Initial results are available of an investigation into the use of quantitative models within an SPMMS.There are several issues and problems of project management. Existing models for cost and some approaches to the measurement of quality have disadvantages. An experience database helps estimating and planning and control. Criteria for model selection can be given (as a basis for assessing external and internal models). A CQA model is incorporated within SPMMS. This is part of the SPMMS approach to integrated and automatic management support.     

Finding the right data for software cost modeling

Good software cost models can significantly help software project managers. With good models, project stakeholders can make informed decisions about how to manage resources, how to control and plan the project, or how to deliver the project on time, on schedule, and on budget. Real-world data sets, such as those coming from software engineering projects, often contain noisy, irrelevant, or redundant variables. We propose that cost modelers should perform data-pruning experiments after data collection and before model building. Such pruning experiments are simple and fast.     

Preliminary Data Analysis Methods in Software Estimation

Software is quite often expensive to develop and can become a major cost factor in corporate information systems budgets. With the variability of software characteristics and the continual emergence of new technologies the accurate prediction of software development costs is a critical problem within the project management context. In order to address this issue a large number of software cost prediction models have been proposed. Each model succeeds to some extent but they all encounter the same problem, i.e., the inconsistency and inadequacy of the historical data sets. Often a preliminary data analysis has not been performed and it is possible for the data to contain non-dominated or confounded variables. Moreover, some of the project attributes or their values are inappropriately out of date, for example the type of computer used for project development in the COCOMO 81 (Boehm, 1981) data set. This paper proposes a framework composed of a set of clearly identified steps that should be performed before a data set is used within a cost estimation model. This framework is based closely on a paradigm proposed by Maxwell (2002). Briefly, the framework applies a set of statistical approaches, that includes correlation coefficient analysis, Analysis of Variance and Chi-Square test, etc., to the data set in order to remove outliers and identify dominant variables. To ground the framework within a practical context the procedure is used to analyze the ISBSG (International Software Benchmarking Standards Group data—Release 8) data set. This is a frequently used accessible data collection containing information for 2,008 software projects. As a consequence of this analysis, 6 explanatory variables are extracted and evaluated.     

浅谈软件项目的需求分析

当今世界各行各业对软件的依赖程度急剧增长,而在规定的时间和预算内开发出可靠并满足用户需求的软件系统,对于许多开发者来说都是一件非常困难的事情。由于软件项目中的需求变更而导致软件项目失败的案例越来越多,所以如何高质量完成需求分析已经被许多软件公司列入了重要的流程化管理中。需求分析的任务还不是确定系统怎样完成它的工作,而仅仅是确定系统必须完成哪些工作,也就是对目标系统提出完整、准确、清晰、具体的要求。     

软件项目进度风险的定量分析方法

软件项目超期仍然是业界的一个普遍现象,进度延期可能直接导致项目质量下降、费用超支甚至失败,因此项目执行过程中对于进度的风险控制至关重要。从定量分析的角度探讨项目进度管理的风险管理方法,并对3种主要的进度管理方法和模型—PERT/CPM方法、关键链方法、事件链方法—进行了调研和对比。其中,事件链是近年来新提出的一种针对风险事件进行建模和分析的方法,为进一步研究有效的进度风险管理控制方法和技术提供了新的思路和视角。     

A Simulation Tool for Efficient Analogy Based Cost Estimation

Estimation of a software project effort, based on project analogies, is a promising method in the area of software cost estimation. Projects in a historical database, that are analogous (similar) to the project under examination, are detected, and their effort data are used to produce estimates. As in all software cost estimation approaches, important decisions must be made regarding certain parameters, in order to calibrate with local data and obtain reliable estimates. In this paper, we present a statistical simulation tool, namely the bootstrap method, which helps the user in tuning the analogy approach before application to real projects. This is an essential step of the method, because if inappropriate values for the parameters are selected in the first place, the estimate will be inevitably wrong. Additionally, we show how measures of accuracy and in particular, confidence intervals, may be computed for the analogy-based estimates, using the bootstrap method with different assumptions about the population distribution of the data set. Estimate confidence intervals are necessary in order to assess point estimate accuracy and assist risk analysis and project planning. Examples of bootstrap confidence intervals and a comparison with regression models are presented on well-known cost data sets.     

Prioritizing and Assessing Software Project Success Factors and Project Characteristics using Subjective Data

This paper presents a method for analyzing the impact software project factors have on project success as defined by project success factors that have been prioritized. It is relatively easy to collect measures of project attributes subjectively (i.e., based on expert judgment). Often Likert scales are used for that purpose. It is much harder to identify whether and how a large number of such ranked project factors influence project success, and to prioritize their influence on project success. At the same time, it is desirable to use the knowledge of project personnel effectively. Given a prioritization of project goals, it is shown how some key project characteristics can be related to project success. The method is applied in a case study consisting of 46 projects. For each project, six success factors and 27 project attributes were measured. Successful projects show common characteristics. Using this knowledge can lead to better control and software project management and to an increased likelihood of project success.     

软件项目管理及风险分析

软件项目的有效管理,对项目的成败具有至关重要的作用。软件项目的风险体现在哪些方面,如何回避这些风险,在本文中进行了探讨,最后指出建立合理的管理流程,对软件项目的管理来说,是非常重要的。     

Accuracy and efficiency comparisons of single- and multi-cycled software classification models

Software classification models have been regarded as an essential support tool in performing measurement and analysis processes. Most of the established models are single-cycled in the model usage stage, and thus require the measurement data of all the model’s variables to be simultaneously collected and utilized for classifying an unseen case within only a single decision cycle. Conversely, the multi-cycled model allows the measurement data of all the model’s variables to be gradually collected and utilized for such a classification within more than one decision cycle, and thus intuitively seems to have better classification efficiency but poorer classification accuracy. Software project managers often have difficulties in choosing an appropriate classification model that is better suited to their specific environments and needs. However, this important topic is not adequately explored in software measurement and analysis literature. By using an industrial software measurement dataset of NASA KC2, this paper explores the quantitative performance comparisons of the classification accuracy and efficiency of the discriminant analysis (DA)- and logistic regression (LR)-based single-cycled models and the decision tree (DT)-based (C4.5 and ECHAID algorithms) multi-cycled models. The experimental results suggest that the re-appraisal cost of the Type I MR, the software failure cost of Type II MR and the data collection cost of software measurements should be considered simultaneously when choosing an appropriate classification model.     

贝叶斯网络在软件项目风险评估中的应用

在软件项目生存周期早期或创新型项目的研发过程中,可用的案例数据很少或很不完整,项目风险多由专家经验进行主观评估,给风险的客观度量带来了很大的困难。提出了一种基于贝叶斯网络的软件项目风险评估方法,不仅可度量风险影响程度的风险当量,还能度量出多种风险对某种风险后果的组合影响以及单个风险对整体后果的综合影响,从而增强了软件项目风险的预测和应变能力,为有效地降低风险发生概率、提高软件开发成功率提供了一种新的途径。     

Experimental design and analysis in software engineering

The paper presents key activities necessary for designing and analyzing an experiment in software engineering. After explaining how to choose an appropriate research technique to fit project goals, the paper shows how to state a hypothesis and determine how much control is needed over the variables involved. If control is not possible, then a formal experiment is not possible; a case study may be a better approach. Next, the six stages of an experiment (conception, design, preparation, execution, analysis and dissemination) are described, with design examined in detail. Design considerations such as replication, randomization and local control are discussed, and design techniques such as crossing and nesting are explained. Finally, data analysis is shown to be a function both of the experimental design and the distribution of the data. Throughout, examples are given to show how the techniques are interpreted and used in software engineering.     

证据理论在软件项目风险分析中的应用

软件项目由于其产品的智力密集性和项目的复杂性,在开发过程中,进行风险分析时不同于一般项目有很多客观的指标可供参考,更多地是借助于专家的意见,从而使得专家意见的综合成为软件项目风险分析中一个急需解决的问题。给出了一个基于证据理论的软件项目风险分析模型,通过引入模糊评语集及该集合上的模糊效用值,使用Dempster规则更好地融合各个专家的意见,从而得出了更加合理的风险概率和风险损失评价值。该方法强调了关键专家意见在决策中的重要性,较好地解决了分析结果过于依赖专家选择的问题,从而减少了风险因素量化的复杂性,为风险控制策略的制定提供了依据。并通过算例加以验证。     

USING MULTIPLE CORRESPONDENCE ANALYSIS WITH MEMBERSHIP VALUES WHEN THE SYSTEM STUDY YIELDS MISCELLANEOUS DATASETS

This article explains the main role that space windowing plays in preliminary knowledge extraction from multifactor and multivariate databases coming from complex system empirical studies. The explanation is based on the general case of a database with a hyperparallelepipedic structure in which the directions correspond to the factors and where the measurement variables may be quantitative or qualitative, temporal or nontemporal, and objective or subjective. First, the data in each cell of the hyperparallelepiped is transformed into membership values that can be averaged over factors, such as time or individual. Then, several graphic techniques can be exploited to investigate membership values. This article mainly focuses on the use of multiple correspondence analysis (MCA). A didactic example with several factors and several kinds of variables—nontemporal vs. temporal where each one may be either quantitative or qualitative—is used to illustrate the widespread use of the pair “space windowing/MCA.” The discussion presents the advantages and disadvantages of using space windowing to perform a preliminary analysis of a multifactor multivariate system study.     

Developing Project Duration Models in Software Engineering

Based on the empirical analysis of data contained in the International Software Benchmarking Standards Group （ISBSG） repository, this paper presents software engineering project duration models based on project effort. Duration models are built for the entire dataset and for subsets of projects developed for personal computer, mid-range and mainframe platforms. Duration models are also constructed for projects requiring fewer than 400 person-hours of effort and for projects requiring more than 400 person-hours of effort. The usefulness of adding the maximum number of assigned resources as a second independent variable to explain duration is also analyzed. The opportunity to build duration models directly from project functional size in function points is investigated as well.     

基于Linux的嵌入式实时数据库的设计

实时数据库是嵌入式系统的核心,用来定义数据变量,负责与外部设备进行实时数据交换。在用组态软件开发嵌入式应用时,在开发环境中定义实时数据库结构、数据来源及类型,在嵌入式运行环境获取实时数据库的数据,并进行显示、报警、存盘等操作。着重介绍了基于Linux的嵌入式组态软件中实时数据库的设计及其实现。     

Developer Role Evolution in Open Source Software Ecosystem: An Explanatory Study on GNOME

An open source software (OSS) ecosystem refers to an OSS development community composed of many software projects and developers contributing to these projects. The projects and developers co-evolve in an ecosystem. To keep healthy evolution of such OSS ecosystems, there is a need of attracting and retaining developers, particularly project leaders and core developers who have major impact on the project and the whole team. Therefore, it is important to figure out the factors that influence developers’ chance to evolve into project leaders and core developers. To identify such factors, we conducted a case study on the GNOME ecosystem. First, we collected indicators reflecting developers’ subjective willingness to contribute to the project and the project environment that they stay in. Second, we calculated such indicators based on the GNOME dataset. Then, we fitted logistic regression models by taking as independent variables the resulting indicators after eliminating the most collinear ones, and taking as a dependent variable the future developer role (the core developer or project leader). The results showed that part of such indicators (e.g., the total number of projects that a developer joined) of subjective willingness and project environment significantly influenced the developers’ chance to evolve into core developers and project leaders. With different validation methods, our obtained model performs well on predicting developmental core developers, resulting in stable prediction performance (0.770, F-value).     

软件项目质量保证的策略与实践

对软件项目实施全过程的质量管理作了详细论述：在需求分析阶段通过结对分析与需求评审来保证需求分析的质量;在设计与开发阶段,制订相应的软件开发规范,并严格执行,保证实现代码的质量;在测试环节上,强调测试与软件实现同步,强化Bug管理,以进一步提高软件质量。软件开发全程要做到＂有法可依,有法必依＂。以上措施是开发出高质量软件系统的重要保证。     

The Cactis project: database support for software environments

The Cactis project is an on-going effort oriented toward extending database support from traditional business-oriented applications to software environments. The main goals of the project are to construct an appropriate model, and develop new techniques to support the unusual data management needs of software environments, including program compilations, software configurations, load modules, project schedules, software versions, nested and long transactions, and program transformations. The ability to manage derived information is common to many of these data needs, and the Cactis database management system has the ability to represent and maintain derived data in a time- and space-efficient fashion. A central contribution of Cactis is its integration of the type constructors of semantic models and the localized behavior capabilities of object-oriented database management systems     

软件项目费用风险混合评估方法

在软件工程领域摹于公式模型预测的结果往往并不比人的经验准确,然而基于经验的预测方法也存在不少问题.提出的软件项目费用风险评估方法基于专家知识经验和历史项目数据,综合利用功能点分析方法以统计或估箅项目的大小,建立了由专家评估预测费用超出的BN模型,由历史数据得到费用超出与生产力之间的关系,从而计算计划项目的生产力.进而估计项目的计划费用,通过对项目当前生产力与计划生产力的比较,评估项目当前是否存在费用风险.方法与费用预测模型无关,费用预算和项目最终实际费用以相对应的理想项目费用为参照物,与在不确定性费用预算基础上进行费用风险分析评估的方法相比,具有较高的可靠性.