SHF: Small: Collaborative Research: Discerning and Recommending Context-Specific Best Practices in DevOps-Oriented Software Development

SHF：小型：协作研究：在面向 DevOps 的软件开发中识别和推荐特定于环境的最佳实践

• 批准号: 1717415
• 负责人: Bogdan Vasilescu
• 金额: $ 31万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1717415&HistoricalAwards=false
• 关键词: SHF; Small; Collaborative; Research; Discerning

This project is a scientific study of modern software development practices, which has become known as DevOps. The DevOps culture seeks to bring changes into software production as quickly as possible without compromising software quality, primarily by automating the processes of building, testing, and deploying software. In practice, DevOps engineers can choose between a multitude of tools, including configuration management, cloud-based continuous integration, and automated deployment. Often individual tools are used without much guidance on how they fit in the big picture, and questions about best practices abound in online forums. However, existing answers are typically generic rules of thumb or dated advice, mostly based on third-party experiences, often non-applicable to the specific context. In fact, current empirical evidence on the effectiveness of DevOps practices is much fragmented and incomplete. State-of-the-art decision-making support, based on hard data and informed advice, can help DevOps engineers discern the best choices and practices for their tasks. The proposed research is grounded in contingency theory, where the emphasis is on task context when reasoning about the effectiveness of practices. The goal of this project is to learn and convey structured, context-dependent analytics on best practices in DevOps environments, by mining and analyzing data from the collaborative coding platform GitHub. Using established and novel qualitative and quantitative techniques, this research will: (1) identify clusters of software projects that share similar context variables; and (2) within a context of interest, discern the conditions under which DevOps practices such as continuous integration are most (and least) effective. This will result in actionable knowledge and tool support for DevOps teams, to customize efficient project practices to their environment, as well as advance the theory and practice of software engineering, especially as it relates to distributed, fast paced, automation-heavy environments.

该项目是对现代软件开发实践的科学研究，已被称为DevOps。DevOps文化寻求在不影响软件质量的情况下尽快将更改引入软件生产，主要是通过自动化构建，测试和部署软件的过程。在实践中，DevOps工程师可以在多种工具之间进行选择，包括配置管理、基于云的持续集成和自动化部署。通常，单独的工具在使用时没有太多关于它们如何适应全局的指导，在线论坛中充斥着关于最佳实践的问题。然而，现有的答案通常是通用的经验法则或过时的建议，大多基于第三方的经验，往往不适用于具体情况。事实上，目前关于DevOps实践有效性的经验证据非常分散和不完整。最先进的决策支持，基于硬数据和明智的建议，可以帮助DevOps工程师识别最佳选择和实践，为他们的任务。拟议的研究是基于权变理论，其中的重点是在推理实践的有效性时的任务上下文。该项目的目标是通过挖掘和分析来自协作编码平台GitHub的数据，学习和传达DevOps环境中最佳实践的结构化，上下文相关的分析。使用已建立的和新的定性和定量技术，本研究将：（1）识别共享相似上下文变量的软件项目集群;（2）在感兴趣的上下文中，识别DevOps实践（如持续集成）最有效（和最不有效）的条件。这将为DevOps团队提供可操作的知识和工具支持，为他们的环境定制高效的项目实践，并推进软件工程的理论和实践，特别是当它涉及到分布式，快节奏，自动化程度高的环境时。

项目成果

A conceptual replication of continuous integration pain points in the context of Travis CI

• DOI: 10.1145/3338906.3338922
• 发表时间: 2019-08
• 期刊: Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering
• 作者: D. Widder;Michael C Hilton;Christian Kästner;Bogdan Vasilescu

Tool Choice Matters: JavaScript Quality Assurance Tools and Usage Outcomes in GitHub Projects

• DOI: 10.1109/icse.2019.00060
• 发表时间: 2019-05
• 期刊: 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)
• 作者: David Kavaler;Asher Trockman;Bogdan Vasilescu;V. Filkov

Capture the Feature Flag: Detecting Feature Flags in Open-Source

捕获功能标志：检测开源中的功能标志

• DOI: 10.1145/3379597.3387463
• 发表时间: 2020
• 期刊: International Conference on Mining Software Repositories
• 作者: Meinicke, J;Hoyos, J;Vasilescu, B;Kästner, C.
• 通讯作者: Kästner, C.

The impact of continuous integration on other software development practices: A large-scale empirical study

• DOI: 10.1109/ase.2017.8115619
• 发表时间: 2017-10
• 期刊: 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)
• 作者: Yangyang Zhao;Alexander Serebrenik;Yuming Zhou;V. Filkov;Bogdan Vasilescu

I'm Leaving You, Travis: A Continuous Integration Breakup Story

• DOI: 10.1145/3196398.3196422
• 发表时间: 2018-05
• 期刊: 2018 IEEE/ACM 15th International Conference on Mining Software Repositories (MSR)
• 作者: D. Widder;Michael C Hilton;Christian Kästner;Bogdan Vasilescu