On Increasing Trust Between Developers and Automated Refactoring Tools Through Visualization

In software development, maintaining good design is essential. The process of refactoring enables developers to improve this design during development without altering the program’s existing behavior. However, this process can be time-consuming, introduce semantic errors, and be difficult for developers inexperienced with refactoring or unfamiliar with a given code base. Automated refactoring tools can help not only by applying these changes, but by identifying opportunities for refactoring. Yet, developers have not been quick to adopt these tools due to a lack of trust between the developer and the tool. We propose an approach in the form of a visualization to aid developers in understanding these suggested operations and increasing familiarity with automated refactoring tools. We also provide a manual validation of this approach and identify options to continue experimentation

Increasing the Trust In Refactoring Through Visualization

In software development, maintaining good design is essential. The process of refactoring enables developers to improve this design during development without altering the program’s existing behavior. However, this process can be time-consuming, introduce semantic errors, and be difficult for developers inexperienced with refactoring or unfamiliar with a given code base. Automated refactoring tools can help not only by applying these changes, but by identifying opportunities for refactoring. Yet, developers have not been quick to adopt these tools due to a lack of trust between the developer and the tool. We propose an approach in the form of a visualization to aid developers in understanding these suggested operations and increasing familiarity with automated refactoring tools. We also provide a manual validation of this approach and identify options to continue experimentation

An empirical investigation into the impact of refactoring on regression testing

It is widely believed that refactoring improves software quality and developer’s productivity by making it easier to maintain and understand software systems. On the other hand, some believe that refactoring has the risk of functionality regression and increased testing cost. This paper investigates the impact of refactoring edits on regression tests using the version history of Java open source projects: (1) Are there adequate regression tests for refactoring in practice? (2) How many of existing regression tests are relevant to refactoring edits and thus need to be re-run for the new version? (3) What proportion of failure-inducing changes are relevant to refactorings? By using a refactoring reconstruction analysis and a change impact analysis in tandem, we investigate the relationship between the types and locations of refactoring edits identified by RefFinder and the affecting changes and affected tests identified by the FaultTracer change impact analysis. The results on three open source projects, JMeter, XMLSecurity, and ANT, show that only 22% of refactored methods and fields are tested by existing regression tests. While refactorings only constitutes 8% of atomic changes, 38% of affected tests are relevant to refactorings. Furthermore, refactorings are involved in almost a half of failed test cases. These results call for new automated regression test augmentation and selection techniques for validating refactoring edits.Electrical and Computer Engineerin

RePOR: Mimicking humans on refactoring tasks. Are we there yet?

Refactoring is a maintenance activity that aims to improve design quality while preserving the behavior of a system. Several (semi)automated approaches have been proposed to support developers in this maintenance activity, based on the correction of anti-patterns, which are `poor' solutions to recurring design problems. However, little quantitative evidence exists about the impact of automatically refactored code on program comprehension, and in which context automated refactoring can be as effective as manual refactoring. Leveraging RePOR, an automated refactoring approach based on partial order reduction techniques, we performed an empirical study to investigate whether automated refactoring code structure affects the understandability of systems during comprehension tasks. (1) We surveyed 80 developers, asking them to identify from a set of 20 refactoring changes if they were generated by developers or by a tool, and to rate the refactoring changes according to their design quality; (2) we asked 30 developers to complete code comprehension tasks on 10 systems that were refactored by either a freelancer or an automated refactoring tool. To make comparison fair, for a subset of refactoring actions that introduce new code entities, only synthetic identifiers were presented to practitioners. We measured developers' performance using the NASA task load index for their effort, the time that they spent performing the tasks, and their percentages of correct answers. Our findings, despite current technology limitations, show that it is reasonable to expect a refactoring tools to match developer code

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

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

Automating property-based testing of evolving web services

Web services are the most widely used service technology that drives the Service-Oriented Computing~(SOC) paradigm. As a result, effective testing of web services is getting increasingly important. In this paper, we present a framework and toolset for testing web services and for evolving test code in sync with the evolution of web services. Our approach to testing web services is based on the Erlang programming language and QuviQ QuickCheck, a property-based testing tool written in Erlang, and our support for test code evolution is added to Wrangler, the Erlang refactoring tool. The key components of our system include the automatic generation of initial test code, the inference of web service interface changes between versions, the provision of a number of domain specific refactorings and the automatic generation of refactoring scripts for evolving the test code. Our framework provides users with a powerful and expressive web service testing framework, while minimising users' effort in creating, maintaining and evolving the test model. The framework presented in this paper can be used by both web service providers and consumers, and can be used to test web services written in whatever language; the approach advocated here could also be adopted in other property-based testing frameworks and refactoring tools

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

On the Value of Quality Attributes for Refactoring Model Transformations Using a Multi-Objective Algorithm

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152454/1/QMOOD_for_ATL__Copy_.pd