支持成本度量和过程改进的软件工程环境

描述了如何在软件工程环境中增加面向软件过程的成本度量和成本控制功能。阐述了面向软件过程的成本模型,与产品分解的成本模型不同,提出把可复用的软件过程作为成本度量的对象;介绍了软件过程及成本度量的本体,使得度量的对象和度量数据都有语义背景,并说明如何在软件工程环境下进行成本度量和过程改进,最后给出了功能模块。     

支持成本度量和过程改进的软件工程环境

描述了如何在软件工程环境中增加面向软件过程的成本度量和成本控制功能。阐述了面向软件过程的成本模型，与产品分解的成本模型不同，提出把可复用的软件过程作为成本度量的对象；介绍了软件过程及成本度量的本体，使得度量的对象和度量数据都有语义背景，并说明如何在软件工程环境下进行成本度量和过程改进，最后给出了功能模块。     

项目度量中对基本COCOMO进行校准的研究

所有成功的软件组织都将度量作为保证自己管理和技术质量的重要手段,软件成本估计则是软件度量[1,2]的核心任务。为了提高成本估算的准确性,文中根据特定软件企业中的历史项目数据对基本COCOMO模型进行校准,在具体的参数修正方法上利用对数数据相关算法进行校正,并与其它方法进行了比较,得到了满意的结果。校准后的模型对项目开发成本的预测将会更加准确,从而切实体现COCOMO成本度量工作对于软件项目的指导价值。因此,文中所做的成本估算模型的校准工作,对软件开发企业非常具有实用价值。     

项目度量中对基本COCOMO进行校准的研究

所有成功的软件组织都将度量作为保证自己管理和技术质量的重要手段，软件成本估计则是软件度量的核心任务。为了提高成本估算的准确性，文中根据特定软件企业中的历史项目数据对基本COCOMO模型进行校准，在具体的参数修正方法上利用对数数据相关算法进行校正，并与其它方法进行了比较，得到了满意的结果。校准后的模型对项目开发成本的预测将会更加准确，从而切实体现COCOMO成本度量工作对于软件项目的指导价值。因此，文中所做的成本估算模型的校准工作，对软件开发企业非常具有实用价值。     

基于软件构件质量模型的度量及应用

随着软件复用实践的深入,可复用构件数量不断增加,构件库规模也不断扩大。构件的质量将影响到最终的软件质量和CBSD的推广应用,但是目前缺乏对构件质量有效的评价模型。本文基于ISO／IEC9126软件质量度量模型,提出了软件构件质量模型,及专门针对软件构件质量模型的可操作的度量方法,重点描述了构件可复用性的度量,并将该方法实际应用于上海构件库部分构件,本文提出的度量模型和方法可作为构件库管理者和构件用户在管理及使用构件时对构件进行评价参考。     

应用IFPUG功能点方法的军用软件规模估算

IFPUG功能点方法是国际功能点用户协会提出的一种广泛使用的度量软件功能大小的方法,它不依赖于实现语言,度量出来的结果也可以在不同的开发过程之间进行比较,该文提供了使用该方法对军用软件系统进行规模估算的实施框架,开发者使用该方法在开发的早期能够估算出系统的规模,为后期工作量与成本估算提供可靠依据,在系统完成后可作为系统其他度量和评估的有效输入。     

基于复用的软件过程改进方法

本文从改善CMM的实施和提高过程控制能力入手,给出一个基于复用的软件过程改进框架,该框架将复用技术应用于软件过程改进与控制中,将当前模型驱动的自顶向下的过程改进模式与度量驱动的自底向上的过程改进模式有机整合,它由组织层面的持续过程改进（大循环）嵌套项目层面的过程不断调整与优化（小循环）构成。以CMM为基础,定义了实施新的过程改进方法的组织与角色。设计一个支持过程复用的软件过程及项目管理支持系统。     

基于CMM的EWPCA故障诊断可靠性的研究

软件度量是软件项目管理的关键技术,它是对软件开发项目、过程及其产品进行数据定义、收集以及分析的持续性定量化过程。利用度量可控制和改进软件过程,在介绍度量基本理论与相关知识的基础上重点分析了对软件过程的度量,并设计完成了软件过程度量系统,根据统计过程控制思想以及能力成熟度模型(CMM)的过程评估标准,把指数加权主元分析方法应用于故障诊断的可靠性进行分析,取得了良好的效果。     

一种分布式数据库管理系统体系结构

本文介绍了我们设计的军用共性软件型号项目军用数据库管理系统ＤＭ２基于消息通信的客户／服务器模型的分布式数据库管理系统体系结构，详细介绍并分析了其核心系统的组成及总体结构。     

基于模型的软件成本估计方法

准确的估计是进行有效的项目计划、跟踪和控制的基础.基于模型的成本估计方法是软件成本估计研究的重点,它可分为算法驱动式模型、数据驱动式模型以及复合式模型.依照该分类模式,介绍了典型的软件成本估计方法,并从内部属性及外部评价两个维度共计11个指标对每类方法的假设前提、适用范围、优势及局限性进行深入的分析.最后,对软件成本估计研究的未来发展进行探讨.     

中等COCOMO模型在中小型软件项目投资决策中的应用探讨

中等COCOMO模型是经过实际软件项目验证和修正的软件成本估算模型.文章将中等COCOMO模型应用于中小型软件项目投资决策,提出了一套简便而完整的中小型软件项目投资分析方法.     

Cost models for future software life cycle processes: COCOMO 2.0

Current software cost estimation models, such as the 1981 Constructive Cost Model (COCOMO) for software cost estimation and its 1987 Ada COCOMO update, have been experiencing increasing difficulties in estimating the costs of software developed to new life cycle processes and capabilities. These include non-sequential and rapid-development process models; reuse-driven approaches involving commercial off-the-shelf (COTS) packages, re-engineering, applications composition, and applications generation capabilities; object-oriented approaches supported by distributed middleware; and software process maturity initiatives. This paper summarizes research in deriving a baseline COCOMO 2.0 model tailored to these new forms of software development, including rationale for the model decisions. The major new modeling capabilities of COCOMO 2.0 are a tailorable family of software sizing models, involving Object Points, Function Points, and Source Lines of Code; nonlinear models for software reuse and re-engineering; an exponentdriver approach for modeling relative software diseconomies of scale; and several additions, deletions and updates to previous COCOMO effort-multiplier cost drivers. This model is serving as a framework for an extensive current data collection and analysis effort to further refine and calibrate the model's estimation capabilities.     

非基于软件复用的成本估算模型的复用改造模型及模型系数修正策略

作为软件成本控制管理的重要措施,软件开发成本的估算技术已经成为软件工程领域的一个重要课题。当前基于复用的软件开发正在成为软件工程的主流,但将软件复用考虑进成本估算的模型较少。提出一个基于软件复用的成本估算模型,并应用该模型对COCOMO模型进行复用改造,之后通过实例进行验证。给出了使用存储过程技术对模型参数进行修正的策略,以为各类基于复用的软件开发成本估算提供依据。     

结构型软件成本估算模型的研究与改进

阐述了软件成本估算的过程和方法，详细介绍了结构型软件成本估算模型（COCOMO），并在COCOMO模型基础上，考虑代码复用和软件再工程等因素，对COCOMO模型进行改进，提高了估算精度。     

An Artificial Neural Network-Based Model for Effective Software Development Effort Estimation

In project management, effective cost estimation is one of the most crucial activities to efficiently manage resources by predicting the required cost to fulfill a given task. However, finding the best estimation results in software development is challenging. Thus, accurate estimation of software development efforts is always a concern for many companies. In this paper, we proposed a novel software development effort estimation model based both on constructive cost model II (COCOMO II) and the artificial neural network (ANN). An artificial neural network enhances the COCOMO model, and the value of the baseline effort constant A is calibrated to use it in the proposed model equation. Three state-of-the-art publicly available datasets are used for experiments. The backpropagation feedforward procedure used a training set by iteratively processing and training a neural network. The proposed model is tested on the test set. The estimated effort is compared with the actual effort value. Experimental results show that the effort estimated by the proposed model is very close to the real effort, thus enhanced the reliability and improving the software effort estimation accuracy.     

Improving the COCOMO model using a neuro-fuzzy approach

Accurate software development cost estimation is important for effective project management such as budgeting, project planning and control. So far, no model has proved to be successful at effectively and consistently predicting software development cost. A novel neuro-fuzzy Constructive Cost Model (COCOMO) is proposed for software cost estimation. This model carries some of the desirable features of a neuro-fuzzy approach, such as learning ability and good interpretability, while maintaining the merits of the COCOMO model. Unlike the standard neural network approach, the proposed model can be interpreted and validated by experts, and has good generalization capability. The model deals effectively with imprecise and uncertain input and enhances the reliability of software cost estimates. In addition, it allows input to have continuous rating values and linguistic values, thus avoiding the problem of similar projects having large different estimated costs. A detailed learning algorithm is also presented in this work. The validation using industry project data shows that the model greatly improves estimation accuracy in comparison with the well-known COCOMO model.     

Knowledge-based risk assessment and cost estimation

A knowledge-based method for software project risk assessment and cost estimation has been implemented on multiple platforms. As an extension to the Constructive Cost Model (COCOMO), it aids in project planning by identifying, categorizing, quantifying and prioritizing project risks. It also detects cost estimate input anomalies and provides risk control advice in addition to conventional COCOMO cost and schedule calculation.The method has been developed in conjunction with a system dynamics model of the software development process, and serves as an intelligent front end to the simulation model. It extends previous research in the knowledge-based cost estimation domain by focusing on risk assessment, incorporating substantially more rules, going beyond standard COCOMO, performing quantitative validation, providing a user-friendly interface, and integrating it with a dynamic simulation model.Results of the validation are promising, and the method is being used at Litton Data Systems and other industrial environments. It will be undergoing further enhancement as part of an integrated capability for software engineering to assist in system acquisition, project planning and risk management.     

构建基于软件过程的成本模型

在分析COCOMOⅡ模型的基础上,提出了一个基于软件过程的成本模型,其中的数量模型既可以避免COCOMO模型度量的复杂性,又可以根据实际数据描述非线性的成本与驱动因素之间的映射关系.该模型还描述了在实际软件过程中成本度量方法,以及利用过程成本度量数据实现估算和成本控制的机制.     

Software project development cost estimation

This paper reports the results of an empirical investigation of the relationships between effort expended, time scales, and project size for software project development. The observed relationships were compared with those predicted by Lawrence Putnam's Rayleigh curve model and Barry Boehm's COCOMO model. The results suggested that although the form of the basic empirical relationships were consistent with the cost models, the COCOMO model was a poor estimator of cost for the current data set and the data did not follow the Rayleigh curve suggested by Putnam. However, the results did suggest that it was possible to develop cost models tailored to a particular environment and to improve the precision of the models as they are used during the development cycle by including additional information such as the known effort for the early development phases. The paper finishes by discussing some of the problems involved in developing useful cost models.