Automatic refactoring of Erlang programs

Sagonas, Konstantinos; Avgerinos, Thanassis

doi:10.1145/1599410.1599414

Cited by 13 publications

(12 citation statements)

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“…Because refactoring involves the transformation of source code, it is typically performed using machine support in a refactoring tool. There are a number of tools that support refactoring in Erlang: in the RELEASE project we have chosen to extend Wrangler 10 [56]; other tools include Tidier [68] and RefactorErl [44].…”

Section: Refactoring For Scalabilitymentioning

confidence: 99%

Scaling Reliably

Trinder

Chechina

Papaspyrou

et al. 2017

ACM Trans. Program. Lang. Syst.

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Distributed actor languages are an effective means of constructing scalable reliable systems, and the Erlang programming language has a well-established and influential model. While the Erlang model conceptually provides reliable scalability, it has some inherent scalability limits and these force developers to depart from the model at scale. This article establishes the scalability limits of Erlang systems, and reports the work of the EU RELEASE project to improve the scalability and understandability of the Erlang reliable distributed actor model.We systematically study the scalability limits of Erlang, and then address the issues at the virtual machine, language and tool levels. More specifically: (1) We have evolved the Erlang virtual machine so that it can work effectively in large scale single-host multicore and NUMA architectures. We have made important changes and architectural improvements to the widely used Erlang/OTP release. (2) We have designed and implemented Scalable Distributed (SD) Erlang libraries to address language-level scalability issues, and provided and validated a set of semantics for the new language constructs. (3) To make large Erlang systems easier to deploy, monitor, and debug we have developed and made open source releases of five complementary tools, some specific to SD Erlang.Throughout the article we use two case studies to investigate the capabilities of our new technologies and tools: a distributed hash table based Orbit calculation and Ant Colony Optimisation (ACO). Chaos Monkey experiments show that two versions of ACO survive random process failure and hence that SD Erlang preserves the Erlang reliability model. While we report measurements on a range of NUMA and cluster architectures, the key scalability experiments are conducted on the Athos cluster with 256 hosts (6144 cores). Even for programs with no global recovery data to maintain, SD Erlang partitions the network to reduce network traffic and hence improves performance of the Orbit and ACO benchmarks above 80 hosts. ACO measurements show that maintaining global recovery data dramatically limits scalability; however scalability is recovered by partitioning the recovery data. We exceed the established scalability limits of distributed Erlang, and do not reach the limits of SD Erlang for these benchmarks at this scale (256 hosts, 6144 cores).

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Section: Refactoring For Scalabilitymentioning

confidence: 99%

Scaling Reliably

Trinder

Chechina

Papaspyrou

et al. 2017

ACM Trans. Program. Lang. Syst.

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“…The tools Tidier (Sagonas & Avgerinos, 2009) for Erlang and HLint (Mitchell, 2011) for Haskell implement expression-level refactorings: Tidier implements a set of chosen transformations, fully automatically, whereas HLint serves to point out bad smells that can be eliminated by the user. Feedback from HLint takes the form of advice on the smell and how it can be removed: and examples of the application of Tidier can be found in Sagonas & Avgerinos (2009).…”

Section: Functional Refactoringsmentioning

confidence: 99%

“…Feedback from HLint takes the form of advice on the smell and how it can be removed: and examples of the application of Tidier can be found in Sagonas & Avgerinos (2009). In the HLint manual Mitchell ( 2011) discusses the reasons for not applying the transformations automatically, not least of which is the fact that it is difficult to use the existing Haskell front-end toolset to reformat code so that it looks similar to the untransformed code.…”

Section: Functional Refactoringsmentioning

confidence: 99%

Refactoring tools for functional languages

Thompson¹,

Li²

2013

J. Funct. Prog.

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Refactoring is the process of changing the design of a program without changing what it does. Typical refactorings, such as function extraction and generalisation, are intended to make a program more amenable to extension, more comprehensible and so on. Refactorings differ from other sorts of program transformation in being applied to source code, rather than to a 'core' language within a compiler, and also in having an effect across a code base, rather than to a single function definition, say. Because of this, there is a need to give automated support to the process. This paper reflects on our experience of building tools to refactor functional programs written in Haskell (HaRe) and Erlang (Wrangler). We begin by discussing what refactoring means for functional programming languages, first in theory, and then in the context of a larger example. Next, we address system design and details of system implementation as well as contrasting the style of refactoring and tooling for Haskell and Erlang. Building both tools led to reflections about what particular refactorings mean, as well as requiring analyses of various kinds, and we discuss both of these. We also discuss various extensions to the core tools, including integrating the tools with test frameworks; facilities for detecting and eliminating code clones; and facilities to make the systems extensible by users. We then reflect on our work by drawing some general conclusions, some of which apply particularly to functional languages, while many others are of general value.

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“…Refactoring tools/engines help to automate the routine aspects of certain code transformations. For Erlang there are three refactoring tools available: Wrangler [3] from the University of Kent, RefactorErl [2] from Eötvös Loránd University and last but not least, Tidier [6,18], a completely automatic code cleaning tool from the National Technical University of Athens.…”

Section: Introductionmentioning

confidence: 99%