Enabling Real-Time Feedback in Software Engineering

Enrique Larios Vargas, J. Hejderup, M. Kechagia, M. Bruntink, Georgios Gousios
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引用次数: 15

Abstract

Modern software projects consist of more than just code: teams follow development processes, the code runs on servers or mobile phones and produces run time logs and users talk about the software in forums like StackOverflow and Twitter and rate it on app stores. Insights stemming from the real-time analysis of combined software engineering data can help software practitioners to conduct faster decision-making. With the development of CodeFeedr, a Real-time Software Analytics Platform, we aim to make software analytics a core feedback loop for software engineering projects. CodeFeedr's vision entails: (1) The ability to unify archival and current software analytics data under a single query language, and (2) The feasibility to apply new techniques and methods for high-level aggregation and summarization of near real-time information on software development. In this paper, we outline three use cases where our platform is expected to have a significant impact on the quality and speed of decision making; dependency management, productivity analytics, and run-time error feedback.
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在软件工程中实现实时反馈
现代软件项目不仅仅由代码组成:团队遵循开发流程,代码在服务器或手机上运行并产生运行时日志,用户在像StackOverflow和Twitter这样的论坛上讨论软件并在应用程序商店中对其进行评分。来自实时分析组合软件工程数据的洞察力可以帮助软件从业者进行更快的决策。随着实时软件分析平台CodeFeedr的开发,我们的目标是使软件分析成为软件工程项目的核心反馈回路。CodeFeedr的愿景需要:(1)在单一查询语言下统一存档和当前软件分析数据的能力,以及(2)应用新技术和方法的可行性,以便对软件开发中的近实时信息进行高级聚合和总结。在本文中,我们概述了三个用例,我们的平台有望对决策的质量和速度产生重大影响;依赖管理、生产力分析和运行时错误反馈。
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