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1.
In this paper, we investigate the impact of team size on the software development effort. Using field data of over 200 software projects from various industries, we empirically test the impact of team size and other variables—such as software size in function points, ICASE tool and programming language type—on software development effort. Our results indicate that software size in function points significantly impacts the software development effort. The two-way interactions between function points and use of ICASE tool, and function points and language type are significant as well. Additionally, the interactions between team size and programming language type, and team size and use of ICASE tool were all significant.
James A. RodgerEmail:
  相似文献   

2.
Project and teamwork training is recognized as an important aspect in software engineering (SE) education. Senior projects, which often feature industrial involvement, serve the function of a ‘capstone course’ in SE curricula, by offering comprehensive training in collaborative software development. Given the characteristics of student team projects and the social aspects of software development, instructional issues in such a course must include: how to encourage teamwork, how to formalize and streamline stakeholder participation, and how to monitor students’ work, as well as sustain their desired collaborative effort throughout the development. In this paper, we present an exploratory study which highlights a particular case and introduces the meetings-flow approach. In order to investigate how this approach could contribute to the project's results, we examined its quantitative benefits in relation to the development of the project. We also conducted focus group interviews to discuss the humanistic findings and educational effects pertaining to this approach.  相似文献   

3.

Context

One of the difficulties faced by software development Project Managers is estimating the cost and schedule for new projects. Previous industry surveys have concluded that software size and cost estimation is a significant technical area of concern. In order to estimate cost and schedule it is important to have a good understanding of the size of the software product to be developed. There are a number of techniques used to derive software size, with function points being amongst the most documented.

Objective

In this paper we explore the utility of function point software sizing techniques when applied to two levels of software requirements documentation in a commercial software development organisation. The goal of the research is to appraise the value (cost/benefit) which functional sizing techniques can bring to the project planning and management of software projects within a small-to-medium sized software development enterprise (SME).

Method

Functional counts were made at the bid and detailed functional specification stages for each of five commercial projects used in the research. Three variants of the NESMA method were used to determine these function counts. Through a structured interview session, feedback on the sizing results was obtained to evaluate its feasibility and potential future contribution to the company.

Results

The results of our research suggest there is value in performing size estimates at two appropriate stages in the software development lifecycle, with simplified methods providing the optimal return on effort expended.

Conclusion

The ‘Estimated NESMA’ is the most appropriate tool for use in size estimation for the company studied. The use of software sizing provides a valuable contribution which would augment, but not replace, the company’s existing cost estimation approach.  相似文献   

4.
An Empirical Study of Analogy-based Software Effort Estimation   总被引:1,自引:1,他引:0  
Conventional approaches to software cost estimation have focused on algorithmic cost models, where an estimate of effort is calculated from one or more numerical inputs via a mathematical model. Analogy-based estimation has recently emerged as a promising approach, with comparable accuracy to algorithmic methods in some studies, and it is potentially easier to understand and apply. The current study compares several methods of analogy-based software effort estimation with each other and also with a simple linear regression model. The results show that people are better than tools at selecting analogues for the data set used in this study. Estimates based on their selections, with a linear size adjustment to the analogue's effort value, proved more accurate than estimates based on analogues selected by tools, and also more accurate than estimates based on the simple regression model.  相似文献   

5.
余方  李娟  王晓程  王永吉 《计算机科学》2007,34(11):245-251
软件规模度量是估算软件项目工作量、成本和合理策划项目进度的基础。本文针对当前流行的软件规模度量方法——功能点分析方法进行综述,阐述了功能点分析方法的基本概念和分析流程。比较全面地总结了现有的代表性功能点分析方法和工具,对一些重要的方法和工具做了客观分析,探讨了功能点分析方法中存在的一些问题及当前研究情况。最后,总结了功能点分析方法的研究现状并对功能点分析方法的发展方向进行了展望。  相似文献   

6.
软件项目估计是CMM2级软件项目策划KPA的基础,是软件开发中的一个重要环节。合理的估计是保证软件项目符合预算和进度要求的前提条件。描述了基于CMM的软件估计的过程,介绍了一种基于嵌入式软件项目的估计方法,并结合具体实例对规模估计、工作量/成本估计、关键计算机资源估计和进度估计的内容进行了细致的阐述。该研究为有效地规划和管理嵌入式软件项目,制定合理可行的软件开发计划提供了有力的支持。  相似文献   

7.
The ability to accurately and consistently estimate software development efforts is required by the project managers in planning and conducting software development activities. Since software effort drivers are vague and uncertain, software effort estimates, especially in the early stages of the development life cycle, are prone to a certain degree of estimation errors. A software effort estimation model which adopts a fuzzy inference method provides a solution to fit the uncertain and vague properties of software effort drivers. The present paper proposes a fuzzy neural network (FNN) approach for embedding artificial neural network into fuzzy inference processes in order to derive the software effort estimates. Artificial neural network is utilized to determine the significant fuzzy rules in fuzzy inference processes. We demonstrated our approach by using the 63 historical project data in the well-known COCOMO model. Empirical results showed that applying FNN for software effort estimates resulted in slightly smaller mean magnitude of relative error (MMRE) and probability of a project having a relative error of less than or equal to 0.25 (Pred(0.25)) as compared with the results obtained by just using artificial neural network and the original model. The proposed model can also provide objective fuzzy effort estimation rule sets by adopting the learning mechanism of the artificial neural network.  相似文献   

8.
The mean magnitude of relative error, MMRE, is the de facto standard evaluation criterion to assess the accuracy of software project prediction models. The fundamental metric of MMRE is MRE, a relative residual error. For MMRE to be a meaningful summary statistic, it is a necessary, but not sufficient, condition that MRE and project size are uncorrelated. Except for two previous conference studies done by the same authors, it has never been empirically validated that MRE and project size really are uncorrelated. In this paper, we extend the previous studies using the same data sets as before: Albrecht, Kemerer, Finnish, DMR and Accenture-ERP. Unlike the previous studies, we plot MRE against the predicted effort rather than against the actual effort and, in so doing, we obtain very different results from the previous studies. The results of this study suggest that MRE and project size are uncorrelated, which apparently is contradictory to the previous results where we found a negative correlation. The explanation for these seemingly contradictory results is presented in this study.  相似文献   

9.

Context

Software maintenance is an important software engineering activity that has been reported to account for the majority of the software total cost. Thus, understanding the factors that influence the cost of software maintenance tasks helps maintainers to make informed decisions about their work.

Objective

This paper describes a controlled experiment of student programmers performing maintenance tasks on a C++ program. The objective of the study is to assess the maintenance size, effort, and effort distributions of three different maintenance types and to describe estimation models to predict the programmer’s effort spent on maintenance tasks.

Method

Twenty-three graduate students and a senior majoring in computer science participated in the experiment. Each student was asked to perform maintenance tasks required for one of the three task groups. The impact of different LOC metrics on maintenance effort was also evaluated by fitting the data collected into four estimation models.

Results

The results indicate that corrective maintenance is much less productive than enhancive and reductive maintenance and program comprehension activities require as much as 50% of the total effort in corrective maintenance. Moreover, the best software effort model can estimate the time of 79% of the programmers with the error of or less than 30%.

Conclusion

Our study suggests that the LOC added, modified, and deleted metrics are good predictors for estimating the cost of software maintenance. Effort estimation models for maintenance work may use the LOC added, modified, deleted metrics as the independent parameters instead of the simple sum of the three. Another implication is that reducing business rules of the software requires a sizable proportion of the software maintenance effort. Finally, the differences in effort distribution among the maintenance types suggest that assigning maintenance tasks properly is important to effectively and efficiently utilize human resources.  相似文献   

10.
The ability to respond to changes in the environment during the development of software is crucial in achieving a quality product. Putting the project team together to achieve the ability to react effectively requires an understanding of the nature of flexibility and capabilities that might promote the ability to respond to changing requirements and conditions. Based on dynamic capability theory, we build a model of software quality that is dependent on the flexibility of the team, with the flexibility of the team dependent on reactive and anticipatory capabilities of the team members. A questionnaire administered to 119 software development team members indicates strong linkages from reactive capabilities and mixed results for anticipatory capabilities to team flexibility. Both flexibility components of a comprehensive response and efficient response to changes are critical in achieving quality software. The items comprising the capabilities can serve to guide management in building flexible development teams.  相似文献   

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