使用Tuscan做出数据驱动的移植决策

Kareem Khazem, Earl T. Barr, Petr Hosek
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引用次数: 1

摘要

软件通常比它最初为之编写的平台寿命更长。为了平稳过渡到新的工具和平台,程序应该尽可能少地依赖底层平台。然而,在实践中,软件构建过程对其构建平台非常敏感,特别是编译器和标准库的实现。这使得将现有的成熟软件移植到新兴平台(如WebAssembly等基于web的运行时,物联网设备的资源约束环境,或Fuchsia等创新的新操作系统)变得困难。我们提出了Tuscan,这是一个在构建系统上执行自动、确定、可重复测试的框架。Tuscan是第一个解决大规模跨平台可重复测试构建问题的框架。我们还编写了一个构建包装器Red,它劫持构建以容忍由平台依赖性引起的常见故障,从而允许测试工具在构建后期发现错误。创新平台的作者可以使用Tuscan和Red来测试软件生态系统中不可移植性的程度,并量化移植遗留软件所需的工作量。我们通过在四个平台上构建一个由2,699个red包装程序组成的操作系统发行版来评估Tuscan,得出了一个最常见的可移植性错误的“目录”。该目录为数据驱动的移植决策提供信息,并激励对程序、构建系统和语言标准的更改;系统地量化平台作者迄今为止仅在临时基础上发现的问题;并且形成了开发人员可以应用于其软件的可移植性修复的公共基础。
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Making data-driven porting decisions with Tuscan
Software typically outlives the platform that it was originally written for. To smooth the transition to new tools and platforms, programs should depend on the underlying platform as little as possible. In practice, however, software build processes are highly sensitive to their build platform, notably the implementation of the compiler and standard library. This makes it difficult to port existing, mature software to emerging platforms---web based runtimes like WebAssembly, resource-constrained environments for Internet-of-Things devices, or innovative new operating systems like Fuchsia. We present Tuscan, a framework for conducting automatic, deterministic, reproducible tests on build systems. Tuscan is the first framework to solve the problem of reproducibly testing builds cross-platform at massive scale. We also wrote a build wrapper, Red, which hijacks builds to tolerate common failures that arise from platform dependence, allowing the test harness to discover errors later in the build. Authors of innovative platforms can use Tuscan and Red to test the extent of unportability in the software ecosystem, and to quantify the effort necessary to port legacy software. We evaluated Tuscan by building an operating system distribution, consisting of 2,699 Red-wrapped programs, on four platforms, yielding a `catalog' of the most common portability errors. This catalog informs data-driven porting decisions and motivates changes to programs, build systems, and language standards; systematically quantifies problems that platform writers have hitherto discovered only on an ad-hoc basis; and forms the basis for a common substrate of portability fixes that developers can apply to their software.
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