Quickchecking refactoring tools

Drienyovszky, Dániel; Horpácsi, Dániel; Thompson, Simon

doi:10.1145/1863509.1863521

Cited by 9 publications

(7 citation statements)

References 12 publications

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“…Quviq QuickCheck [24] extends the original version with libraries tailored for testing industrial software, such as the state machine library used here. It has been used to test many large systems, including telecoms products [4], a messaging gateway [25], refactoring tools [26], [27], and quadcopters [28]. Probably the largest application so far was to test AUTOSAR basic software (C code which runs in cars), in which a million lines of C was tested against 3,000 pages of the AUTOSAR standard, using 20,000 lines of QuickCheck code [29].…”

Section: Related Workmentioning

confidence: 99%

Mysteries of DropBox: Property-Based Testing of a Distributed Synchronization Service

Hughes

Pierce

Arts

et al. 2016

2016 IEEE International Conference on Software Testing, Verification and Validation (ICST)

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File synchronization services such as Dropbox are used by hundreds of millions of people to replicate vital data. Yet rigorous models of their behavior are lacking. We present the first formal-and testable-model of the core behavior of a modern file synchronizer, and we use it to discover surprising behavior in two widely deployed synchronizers. Our model is based on a technique for testing nondeterministic systems that avoids requiring that the system's internal choices be made visible to the testing framework.

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Section: Related Workmentioning

confidence: 99%

Mysteries of DropBox: Property-Based Testing of a Distributed Synchronization Service

Hughes

Pierce

Arts

et al. 2016

2016 IEEE International Conference on Software Testing, Verification and Validation (ICST)

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“…The experiment was successful to the extent that it identified bugs in Wrangler. More details are reported in Drienyovszky et al (2010).…”

Section: Testing Refactoring Toolsmentioning

confidence: 99%

“…On the other hand, it is possible to identify the (potential) presence of such conversions statically, and to issue appropriate warnings. 4 Work in this direction is reported inDrienyovszky et al (2010). 5 This topic is also discussed at the end of Section 14.…”

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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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“…Wrangler, a refactoring tool for Erlang has also been tested using random program generation [7]. A rich program generator has been created, which is capable of generating full modules.…”

Section: Related Workmentioning

confidence: 99%

“…This approach is problematic for two reasons. Firstly, because collecting a large number of suitable programs is difficult and such programs rarely cover all interesting cases of code [7,10]. Secondly, because the compiler is tested against the same set of programs over and over again, which means that if a bug is not triggered by any of them, then it will never be found.…”

Section: Introductionmentioning

confidence: 99%

Testing an optimising compiler by generating random lambda terms

Pałka

Claessen

Russo

et al. 2011

Proceedings of the 6th International Workshop on Automation of Software Test

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This paper considers random testing of a compiler, using randomly generated programs as inputs, and comparing their behaviour with and without optimisation. Since the generated programs must compile, then we need to take into account syntax, scope rules, and type checking during our random generation. Doing so, while attaining a good distribution of test data, proves surprisingly subtle; the main contribution of this paper is a workable solution to this problem. We used it to generate typed functions on lists, which we compiled using the Glasgow Haskell compiler, a mature production quality Haskell compiler. After around 20,000 tests we triggered an optimiser failure, and automatically simplified it to a program with just a few constructs.

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Quickchecking refactoring tools

Cited by 9 publications

References 12 publications

Mysteries of DropBox: Property-Based Testing of a Distributed Synchronization Service

Mysteries of DropBox: Property-Based Testing of a Distributed Synchronization Service

Refactoring tools for functional languages

Testing an optimising compiler by generating random lambda terms

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