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 program builds cross-platform at massive scale. We also wrote a build wrapper, Red, which hijacks builds to automatically fix common failures that arise from platform dependence—allowing the test harness to ignore known errors and discover errors later in the build. On the platform on which the most programs failed to build, using Red rescued 48% of builds from failing, and allowed an additional 34% of builds to proceed further before failing. Authors of innovative new platforms can use Tuscan and Red to test the extent of platform dependence in the software ecosystem, and to quantify the porting effort necessary to build legacy software on new platforms.
We evaluated Tuscan by using it to build 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 a costly and ad-hoc basis; and forms the basis for a common substrate of portability fixes that developers and distributors can apply to their software.
Wed 18 Jul
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Comparing developer-provided to user-provided tests for fault localization and automated program repair
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Jiajun JiangPeking University, Yingfei XiongPeking University, Hongyu ZhangThe University of Newcastle, Qing GaoPeking University, Xiangqun ChenPeking UniversityPre-print
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