Agile effort estimation in Colombia: An assessment and opportunities for improvement

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Juan Cubillos, Jairo Aponte, Diana Gomez, Edwar Rojas
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引用次数: 0

Abstract

Effort estimation is fundamental for the development of software projects and critical to their success. The objective of this paper is to understand how Colombian agile practitioners perform effort estimates and to identify opportunities for improvement based on these results. For this purpose, we conducted an exploratory survey study using as instrument an on-line questionnaire answered by agile practitioners with experience in effort estimation. Data was collected from 60 agile practitioners and the main findings are: (1) Agile practitioners prefer non-algorithmic estimation techniques, mainly those based on Expert Judgment. (2) Most of the respondents perceive that their estimates have a medium accuracy level; however, in most cases, no formal analysis of the accuracy level is carried out. (3) The determining effort predictors/cost drivers are characteristics of the project team (size, experience, and skills) and attributes of the software to be built (complexity, type, and domain). (4) The use of datasets for estimation is not common; proprietary datasets predominate and are used for productivity comparisons within the company. (5) Most of the results of related studies are comparable with ours; however, there are significant differences in terms of the roles involved and the techniques used in the effort estimation process. Based on the results and findings of the survey, we identified key opportunities to improve estimation accuracy through (1) software measurement standardization, (2) use of effort datasets, (3) implementation of techniques for measuring accuracy levels, and (4) knowledge management in effort estimation.

哥伦比亚的敏捷努力估算:评估与改进机会
努力估算是软件项目开发的基础,也是项目成功的关键。本文旨在了解哥伦比亚敏捷实践者是如何进行努力估算的,并在此基础上找出改进的机会。为此,我们开展了一项探索性调查研究,使用的工具是一份在线问卷,由具有努力估算经验的敏捷实践者回答。我们收集了 60 位敏捷实践者的数据,主要发现有(1) 敏捷实践者更喜欢非算法估算技术,主要是基于专家判断的估算技术。(2) 大多数受访者认为他们的估算具有中等准确度;但在大多数情况下,没有对准确度进行正式分析。(3) 决定工作量的预测因素/成本驱动因素是项目团队的特点(规模、经验和技能)以及要构建的软件的属性(复杂性、类型和领域)。(4) 使用数据集进行估算并不常见;专有数据集占主导地位,用于公司内部的生产率比较。(5) 相关研究的大部分结果与我们的研究结果具有可比性;但是,在工作量估算过程中所涉及的角色和使用的技术方面存在显著差异。根据调查结果和发现,我们确定了通过以下途径提高估算准确性的关键机会:(1) 软件测量标准化;(2) 使用工作量数据集;(3) 实施测量准确性水平的技术;(4) 工作量估算中的知识管理。
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来源期刊
Science of Computer Programming
Science of Computer Programming 工程技术-计算机:软件工程
CiteScore
3.80
自引率
0.00%
发文量
76
审稿时长
67 days
期刊介绍: Science of Computer Programming is dedicated to the distribution of research results in the areas of software systems development, use and maintenance, including the software aspects of hardware design. The journal has a wide scope ranging from the many facets of methodological foundations to the details of technical issues andthe aspects of industrial practice. The subjects of interest to SCP cover the entire spectrum of methods for the entire life cycle of software systems, including • Requirements, specification, design, validation, verification, coding, testing, maintenance, metrics and renovation of software; • Design, implementation and evaluation of programming languages; • Programming environments, development tools, visualisation and animation; • Management of the development process; • Human factors in software, software for social interaction, software for social computing; • Cyber physical systems, and software for the interaction between the physical and the machine; • Software aspects of infrastructure services, system administration, and network management.
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