对软件开发动机的大规模调查

IF 4.1 2区 计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Idan Amit, Dror G. Feitelson
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引用次数: 0

摘要

背景:众所周知,动机可以提高表现。特别是在软件开发中,人们对开源贡献者的动机非常感兴趣。目的:我们想要预测在不同环境下的动机。我们从文献中确定了11种激励因素(享受编程、拥有代码、学习、自我使用等),并使用监督学习评估了它们对动机的相对影响。方法:对521名开发人员进行问卷调查,共66个问题。大多数问题采用11分制。我们还进行了一项后续调查,在激励因素改善的情况下,对激励因素的改善进行了调查。结果:预测分析——调查不同的激励因素如何影响高激励的概率——提供了有价值的见解。不同激励因素之间的相关性较低,表明其独立性。所有11个激励因素的高值预示着高激励的可能性增加。此外,改进分析表明,大多数激励因素的增加预示着一般动机的增加。结论:所有11个激励因素确实支持激励,但只是适度支持。没有单一的激励因素足以预测高动机或动机改善,每个激励因素都阐明了动机的不同方面。基于多个激励因素的模型预测动机改善的准确率高达94%,优于任何单一激励因素。编者注:开放科学材料由系统与软件开放科学委员会杂志验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A large scale survey of motivation in software development

Context:

Motivation is known to improve performance. In software development, in particular, there has been considerable interest in the motivation of contributors to open-source.

Objective:

We would like to predict motivation, in various settings. We identify 11 motivators from the literature (enjoying programming, ownership of code, learning, self-use, etc.), and evaluate their relative effect on motivation using supervised learning.

Method:

We conducted a survey with 66 questions on motivation which was completed by 521 developers. Most of the questions used an 11-point scale. We also conducted a follow-up survey, enabling investigation of motivation improvement given improvement in motivators.

Results:

Predictive analysis — investigating how diverse motivators influence the probability of high motivation — provided valuable insights. The correlations between the different motivators are low, implying their independence. High values in all 11 motivators predict an increased probability of high motivation. In addition, improvement analysis shows that an increase in most motivators predicts an increase in general motivation.

Conclusions:

All 11 motivators indeed support motivation, but only moderately. No single motivator suffices to predict high motivation or motivation improvement, and each motivator sheds light on a different aspect of motivation. Models based on multiple motivators predict motivation improvement with up to 94% accuracy, better than any single motivator.
Editor’s note: Open Science material was validated by the Journal of Systems and Software Open Science Board.
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来源期刊
Journal of Systems and Software
Journal of Systems and Software 工程技术-计算机:理论方法
CiteScore
8.60
自引率
5.70%
发文量
193
审稿时长
16 weeks
期刊介绍: The Journal of Systems and Software publishes papers covering all aspects of software engineering and related hardware-software-systems issues. All articles should include a validation of the idea presented, e.g. through case studies, experiments, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited to: •Methods and tools for, and empirical studies on, software requirements, design, architecture, verification and validation, maintenance and evolution •Agile, model-driven, service-oriented, open source and global software development •Approaches for mobile, multiprocessing, real-time, distributed, cloud-based, dependable and virtualized systems •Human factors and management concerns of software development •Data management and big data issues of software systems •Metrics and evaluation, data mining of software development resources •Business and economic aspects of software development processes The journal welcomes state-of-the-art surveys and reports of practical experience for all of these topics.
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