Converting Parallel Code from Low-Level Abstractions to Higher-Level Abstractions

Okur, Semih; Erdogan, Cansu; Dig, Danny

doi:10.1007/978-3-662-44202-9_21

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…The work most closely related to ours can be subdivided into two broad categories. Some work [Gallaba et al 2017] [Okur et al 2014a] [Lin et al 2015] [Lin et al 2014] is concerned with translating one asynchronous/concurrent programming paradigm to another, while others [Dig et al 2009a] [Wloka et al 2009] [Khatchadourian et al 2019] [Dig et al 2009b] [Okur et al 2014a] focus on introducing asynchrony or concurrency in synchronous code. To our knowledge, our work is the first technique in the latter category that is concerned with refactoring synchronous APIs into asynchronous equivalents, and that is concerned with JavaScript.…”

Section: Related Workmentioning

confidence: 99%

“…Other work on C# includes work by Okur et al [2014a] on two refactoring tools, Taskifier and Simplifier, for introducing Task abstractions and transforming them into higher-level design patterns. This is another example of a migration from one asynchronous paradigm to another (from low level Thread abstractions to higher level asynchronous design patterns).…”

Section: Related Workmentioning

confidence: 99%

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Automatic migration from synchronous to asynchronous JavaScript APIs

Gokhale

Turcotte

Tip

2021

Proc. ACM Program. Lang.

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The JavaScript ecosystem provides equivalent synchronous and asynchronous Application Programming Interfaces (APIs) for many commonly used I/O operations. Synchronous APIs involve straightforward sequential control flow that makes them easy to use and understand, but their "blocking" behavior may result in poor responsiveness or performance. Asynchronous APIs impose a higher syntactic burden that relies on callbacks, promises, and higher-order functions. On the other hand, their nonblocking behavior enables applications to scale better and remain responsive while I/O requests are being processed. While it is generally understood that asynchronous APIs have better performance characteristics, many applications still rely on synchronous APIs. In this paper, we present a refactoring technique for assisting programmers with the migration from synchronous to asynchronous APIs. The technique relies on static analysis to determine where calls to synchronous API functions can be replaced with their asynchronous counterparts, relying on JavaScript's async/await feature to minimize disruption to the source code. Since the static analysis is potentially unsound, the proposed refactorings are presented as suggestions that must be reviewed and confirmed by the programmer. The technique was implemented in a tool named Desynchronizer. In an empirical evaluation on 12 subject applications containing 316 synchronous API calls, Desynchronizer identified 256 of these as candidates for refactoring. Of these candidates, 244 were transformed successfully, and only 12 resulted in behavioral changes. Further inspection of these cases revealed that the majority of these issues can be attributed to unsoundness in the call graph.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Automatic migration from synchronous to asynchronous JavaScript APIs

Gokhale

Turcotte

Tip

2021

Proc. ACM Program. Lang.

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“…Lin et al [134] present a study to understand the use of AsyncTask in Android applications, and an accompanying tool to assist programmers in refactoring their applications to make use of it. Okur et al [172] convert concurrent code from low-level abstractions to higher-level equivalents. Other research loosely in this space includes work by Khatchadourian et al [124] on automatically parallelizing Java 8 streams, by Dig et al [71] to parallelize Java loops, by Wloka et al [236] on refactoring applications to be reentrant, by Dig et al [70] for leveraging concurrency APIs to transform sequential code.…”

Section: Refactoringmentioning

confidence: 99%

Optimizing asynchronous JavaScript applications

Turcotte

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Frank: thank you for your support and encouragement, for being an exemplary mentor, and for your guidance in navigating the research community. Looking forward to many more years of working together.Jan: thanks for sharing your enthusiasm for cool research and sound science, and for knowing what questions to ask and teaching me to ask the right questions. It was (and will continue to be!) a pleasure working with you.Committee: thanks to Jon for your enthusiastic support, Arjun for your zany energy, and Ali and Andreas for the interesting discussion (and getting up super early / working late to attend my proposal and defence!). Amber, Alexander, Phraea, Craig: thanks for all the late night dungeon delving. Remember, every adventure have skeleton.

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Understanding, Refactoring, and Fixing Concurrency in C#

Okur

2015

2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)

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Converting Parallel Code from Low-Level Abstractions to Higher-Level Abstractions

Cited by 3 publications

References 14 publications

Automatic migration from synchronous to asynchronous JavaScript APIs

Automatic migration from synchronous to asynchronous JavaScript APIs

Optimizing asynchronous JavaScript applications

Understanding, Refactoring, and Fixing Concurrency in C#

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