A software architecture orientation framework

Timo Kehrer, Ingo Arnold, Arif Chughtai, Oliver Vogel
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引用次数: 1

Abstract

Summary form only given. Software development at Google is big and fast. The code base receives 20+ code changes per minute and 50% of the files change every month! Each product is developed and released from head relying on automated tests verifying the product behavior. Release frequency varies from multiple times per day to once every few weeks, depending on the product team. With such a huge, fast-moving codebase, it is possible for teams to get stuck spending a lot of time just keeping their build green. A continuous integration system should help by providing the exact change at which a test started failing, instead of a range of suspect changes or doing a lengthy binary-search for the offending change. We have built a system that uses dependency analysis to determine all the tests a change transitively affects and then runs only those tests for every change. The system is built on top of Googles cloud computing infrastructure enabling many builds to be executed concurrently, allowing the system to run affected tests as soon as a change is submitted. The use of smart tools and cloud computing infrastructure in the continuous integration system enables quick, effective feedback to development teams.
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面向软件体系结构的框架
只提供摘要形式。谷歌的软件开发规模大、速度快。代码库每分钟收到20多个代码更改,每个月有50%的文件更改!每个产品的开发和发布都依赖于验证产品行为的自动化测试。根据产品团队的不同,发布频率从每天多次到每几周一次不等。面对如此庞大且快速移动的代码库,团队可能会花费大量时间来保持构建绿色。持续集成系统应该通过提供测试开始失败的确切更改来提供帮助,而不是一系列可疑的更改或对违规更改进行冗长的二进制搜索。我们已经建立了一个系统,它使用依赖分析来确定变更传递影响的所有测试,然后只对每个变更运行这些测试。该系统建立在google的云计算基础设施之上,可以同时执行多个构建,允许系统在提交更改后立即运行受影响的测试。在持续集成系统中使用智能工具和云计算基础设施,可以向开发团队提供快速、有效的反馈。
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