Trustworthy Refactoring via Decomposition and Schemes: A Complex Case Study

Widely used complex code refactoring tools lack a solid reasoning about the correctness of the transformations they implement, whilst interest in proven correct refactoring is ever increasing as only formal verification can provide true confidence in applying tool-automated refactoring to industrial-scale code. By using our strategic rewriting based refactoring specification language, we present the decomposition of a complex transformation into smaller steps that can be expressed as instances of refactoring schemes, then we demonstrate the semi-automatic formal verification of the components based on a theoretical understanding of the semantics of the programming language. The extensible and verifiable refactoring definitions can be executed in our interpreter built on top of a static analyser framework.Comment: In Proceedings VPT 2017, arXiv:1708.0688

Renaming Global Variables in C Mechanically Proved Correct

Most integrated development environments are shipped with refactoring tools. However, their refactoring operations are often known to be unreliable. As a consequence, developers have to test their code after applying an automatic refactoring. In this article, we consider a refactoring operation (renaming of global variables in C), and we prove that its core implementation preserves the set of possible behaviors of transformed programs. That proof of correctness relies on the operational semantics of C provided by CompCert C in Coq.Comment: In Proceedings VPT 2016, arXiv:1607.0183

The effectiveness of refactoring, based on a compatibility testing taxonomy and a dependency graph

In this paper, we describe and then appraise a testing taxonomy proposed by van Deursen and Moonen (VD&M) based on the post-refactoring repeatability of tests. Four categories of refactoring are identified by VD&M ranging from semantic-preserving to incompatible, where, for the former, no new tests are required and for the latter, a completely new test set has to be developed. In our appraisal of the taxonomy, we heavily stress the need for the inter-dependence of the refactoring categories to be considered when making refactoring decisions and we base that need on a refactoring dependency graph developed as part of the research. We demonstrate that while incompatible refactorings may be harmful and time-consuming from a testing perspective, semantic-preserving refactorings can have equally unpleasant hidden ramifications despite their advantages. In fact, refactorings which fall into neither category have the most interesting properties. We support our results with empirical refactoring data drawn from seven Java open-source systems (OSS) and from the same analysis form a tentative categorization of code smells

A meta-analysis approach to refactoring and XP

The mechanics of seventy-two different Java refactorings are described fully in Fowler's text. In the same text, Fowler describes seven categories of refactoring, into which each of the seventy-two refactorings can be placed. A current research problem in the refactoring and XP community is assessing the likely time and testing effort for each refactoring, since any single refactoring may use any number of other refactorings as part of its mechanics and, in turn, can be used by many other refactorings. In this paper, we draw on a dependency analysis carried out as part of our research in which we identify the 'Use' and 'Used By' relationships of refactorings in all seven categories. We offer reasons why refactorings in the 'Dealing with Generalisation' category seem to embrace two distinct refactoring sub-categories and how refactorings in the 'Moving Features between Objects' category also exhibit specific characteristics. In a wider sense, our meta-analysis provides a developer with concrete guidelines on which refactorings, due to their explicit dependencies, will prove problematic from an effort and testing perspective

Improving Prolog Programs: Refactoring for Prolog

Refactoring is an established technique from the OO-community to restructure code: it aims at improving software readability, maintainability and extensibility. Although refactoring is not tied to the OO-paradigm in particular, its ideas have not been applied to Logic Programming until now. This paper applies the ideas of refactoring to Prolog programs. A catalogue is presented listing refactorings classified according to scope. Some of the refactorings have been adapted from the OO-paradigm, while others have been specifically designed for Prolog. Also the discrepancy between intended and operational semantics in Prolog is addressed by some of the refactorings. In addition, ViPReSS, a semi-automatic refactoring browser, is discussed and the experience with applying \vipress to a large Prolog legacy system is reported. Our main conclusion is that refactoring is not only a viable technique in Prolog but also a rather desirable one.Comment: To appear in ICLP 200

Refactoring, reengineering and evolution: paths to Geant4 uncertainty quantification and performance improvement

Ongoing investigations for the improvement of Geant4 accuracy and computational performance resulting by refactoring and reengineering parts of the code are discussed. Issues in refactoring that are specific to the domain of physics simulation are identified and their impact is elucidated. Preliminary quantitative results are reported.Comment: To be published in the Proc. CHEP (Computing in High Energy Physics) 201

A Case Study in Refactoring Functional Programs

Refactoring is the process of redesigning existing code without changing its functionality. Refactoring has recently come to prominence in the OO community. In this paper we explore the prospects for refactoring functional programs. Our paper centres on the case study of refactoring a 400 line Haskell program written by one of our students. The case study illustrates the type and variety of program manipulations involved in refactoring. Similarly to other program transformations, refactorings are based on program equivalences, and thus ultimately on language semantics. In the context of functional languages, refactorings can be based on existing theory and program analyses. However, the use of program transformations for program restructuring emphasises a different kind of transformation from the more traditional derivation or optimisation: characteristically, they often require wholesale changes to a collection of modules, and although they are best controlled by programmers, their application may require nontrivial semantic analyses. The paper also explores the background to refactoring, provides a taxonomy for describing refactorings and draws some conclusions about refactoring for functional programs

Dynamic Analysis can be Improved with Automatic Test Suite Refactoring

Context: Developers design test suites to automatically verify that software meets its expected behaviors. Many dynamic analysis techniques are performed on the exploitation of execution traces from test cases. However, in practice, there is only one trace that results from the execution of one manually-written test case. Objective: In this paper, we propose a new technique of test suite refactoring, called B-Refactoring. The idea behind B-Refactoring is to split a test case into small test fragments, which cover a simpler part of the control flow to provide better support for dynamic analysis. Method: For a given dynamic analysis technique, our test suite refactoring approach monitors the execution of test cases and identifies small test cases without loss of the test ability. We apply B-Refactoring to assist two existing analysis tasks: automatic repair of if-statements bugs and automatic analysis of exception contracts. Results: Experimental results show that test suite refactoring can effectively simplify the execution traces of the test suite. Three real-world bugs that could previously not be fixed with the original test suite are fixed after applying B-Refactoring; meanwhile, exception contracts are better verified via applying B-Refactoring to original test suites. Conclusions: We conclude that applying B-Refactoring can effectively improve the purity of test cases. Existing dynamic analysis tasks can be enhanced by test suite refactoring