On Preserving the Behavior in Software Refactoring: A Systematic Mapping Study

Context: Refactoring is the art of modifying the design of a system without altering its behavior. The idea is to reorganize variables, classes and methods to facilitate their future adaptations and comprehension. As the concept of behavior preservation is fundamental for refactoring, several studies, using formal verification, language transformation and dynamic analysis, have been proposed to monitor the execution of refactoring operations and their impact on the program semantics. However, there is no existing study that examines the available behavior preservation strategies for each refactoring operation. Objective: This paper identifies behavior preservation approaches in the research literature. Method: We conduct, in this paper, a systematic mapping study, to capture all existing behavior preservation approaches that we classify based on several criteria including their methodology, applicability, and their degree of automation. Results: The results indicate that several behavior preservation approaches have been proposed in the literature. The approaches vary between using formalisms and techniques, developing automatic refactoring safety tools, and performing a manual analysis of the source code. Conclusion: Our taxonomy reveals that there exist some types of refactoring operations whose behavior preservation is under-researched. Our classification also indicates that several possible strategies can be combined to better detect any violation of the program semantics

30 Years of Software Refactoring Research: A Systematic Literature Review

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155872/4/30YRefactoring.pd

30 Years of Software Refactoring Research:A Systematic Literature Review

Due to the growing complexity of software systems, there has been a dramatic increase and industry demand for tools and techniques on software refactoring in the last ten years, defined traditionally as a set of program transformations intended to improve the system design while preserving the behavior. Refactoring studies are expanded beyond code-level restructuring to be applied at different levels (architecture, model, requirements, etc.), adopted in many domains beyond the object-oriented paradigm (cloud computing, mobile, web, etc.), used in industrial settings and considered objectives beyond improving the design to include other non-functional requirements (e.g., improve performance, security, etc.). Thus, challenges to be addressed by refactoring work are, nowadays, beyond code transformation to include, but not limited to, scheduling the opportune time to carry refactoring, recommendations of specific refactoring activities, detection of refactoring opportunities, and testing the correctness of applied refactorings. Therefore, the refactoring research efforts are fragmented over several research communities, various domains, and objectives. To structure the field and existing research results, this paper provides a systematic literature review and analyzes the results of 3183 research papers on refactoring covering the last three decades to offer the most scalable and comprehensive literature review of existing refactoring research studies. Based on this survey, we created a taxonomy to classify the existing research, identified research trends, and highlighted gaps in the literature and avenues for further research.Comment: 23 page

A survey on software testability

Context: Software testability is the degree to which a software system or a unit under test supports its own testing. To predict and improve software testability, a large number of techniques and metrics have been proposed by both practitioners and researchers in the last several decades. Reviewing and getting an overview of the entire state-of-the-art and state-of-the-practice in this area is often challenging for a practitioner or a new researcher. Objective: Our objective is to summarize the body of knowledge in this area and to benefit the readers (both practitioners and researchers) in preparing, measuring and improving software testability. Method: To address the above need, the authors conducted a survey in the form of a systematic literature mapping (classification) to find out what we as a community know about this topic. After compiling an initial pool of 303 papers, and applying a set of inclusion/exclusion criteria, our final pool included 208 papers. Results: The area of software testability has been comprehensively studied by researchers and practitioners. Approaches for measurement of testability and improvement of testability are the most-frequently addressed in the papers. The two most often mentioned factors affecting testability are observability and controllability. Common ways to improve testability are testability transformation, improving observability, adding assertions, and improving controllability. Conclusion: This paper serves for both researchers and practitioners as an "index" to the vast body of knowledge in the area of testability. The results could help practitioners measure and improve software testability in their projects

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

PROGRAM INSPECTION AND TESTING TECHNIQUES FOR CODE CLONES AND REFACTORINGS IN EVOLVING SOFTWARE

Developers often perform copy-and-paste activities. This practice causes the similar code fragment (aka code clones) to be scattered throughout a code base. Refactoring for clone removal is beneficial, preventing clones from having negative effects on software quality, such as hidden bug propagation and unintentional inconsistent changes. However, recent research has provided evidence that factoring out clones does not always reduce the risk of introducing defects, and it is often difficult or impossible to remove clones using standard refactoring techniques. To investigate which or how clones can be refactored, developers typically spend a significant amount of their time managing individual clone instances or clone groups scattered across a large code base. To address the problem, this research proposes two techniques to inspect and validate refactoring changes. First, we propose a technique for managing clone refactorings, Pattern-based clone Refactoring Inspection (PRI), using refactoring pattern templates. By matching the refactoring pattern templates against a code base, it summarizes refactoring changes of clones, and detects the clone instances not consistently factored out as potential anomalies. Second, we propose Refactoring Investigation and Testing technique, called RIT. RIT improves the testing efficiency for validating refactoring changes. RIT uses PRI to identify refactorings by analyzing original and edited versions of a program. It then uses the semantic impact of a set of identified refactoring changes to detect tests whose behavior may have been affected and modified by refactoring edits. Given each failed asserts, RIT helps developers focus their attention on logically related program statements by applying program slicing for minimizing each test. For debugging purposes, RIT determines specific failure-inducing refactoring edits, separating from other changes that only affect other asserts or tests

State of Refactoring Adoption: Towards Better Understanding Developer Perception of Refactoring

Context: Refactoring is the art of improving the structural design of a software system without altering its external behavior. Today, refactoring has become a well-established and disciplined software engineering practice that has attracted a significant amount of research presuming that refactoring is primarily motivated by the need to improve system structures. However, recent studies have shown that developers may incorporate refactoring strategies in other development-related activities that go beyond improving the design especially with the emerging challenges in contemporary software engineering. Unfortunately, these studies are limited to developer interviews and a reduced set of projects. Objective: We aim at exploring how developers document their refactoring activities during the software life cycle. We call such activity Self-Affirmed Refactoring (SAR), which is an indication of the developer-related refactoring events in the commit messages. After that, we propose an approach to identify whether a commit describes developer-related refactoring events, to classify them according to the refactoring common quality improvement categories. To complement this goal, we aim to reveal insights into how reviewers develop a decision about accepting or rejecting a submitted refactoring request, what makes such review challenging, and how to the efficiency of refactoring code review. Method: Our empirically driven study follows a mixture of qualitative and quantitative methods. We text mine refactoring-related documentation, then we develop a refactoring taxonomy, and automatically classify a large set of commits containing refactoring activities, and identify, among the various quality models presented in the literature, the ones that are more in-line with the developer\u27s vision of quality optimization, when they explicitly mention that they are refactoring to improve them to obtain an enhanced understanding of the motivation behind refactoring. After that, we performed an industrial case study with professional developers at Xerox to study the motivations, documentation practices, challenges, verification, and implications of refactoring activities during code review. Result: We introduced SAR taxonomy on how developers document their refactoring strategies in commit messages and proposed a SAR model to automate the detection of refactoring. Our survey with code reviewers has revealed several difficulties related to understanding the refactoring intent and implications on the functional and non-functional aspects of the software. Conclusion: Our SAR taxonomy and model, can work in conjunction with refactoring detectors, to report any early inconsistency between refactoring types and their documentation and can serve as a solid background for various empirical investigations. In light of our findings of the industrial case study, we recommended a procedure to properly document refactoring activities, as part of our survey feedback

From Monolith to Microservices: A Classification of Refactoring Approaches

While the recently emerged Microservices architectural style is widely discussed in literature, it is difficult to find clear guidance on the process of refactoring legacy applications. The importance of the topic is underpinned by high costs and effort of a refactoring process which has several other implications, e.g. overall processes (DevOps) and team structure. Software architects facing this challenge are in need of selecting an appropriate strategy and refactoring technique. One of the most discussed aspects in this context is finding the right service granularity to fully leverage the advantages of a Microservices architecture. This study first discusses the notion of architectural refactoring and subsequently compares 10 existing refactoring approaches recently proposed in academic literature. The approaches are classified by the underlying decomposition technique and visually presented in the form of a decision guide for quick reference. The review yielded a variety of strategies to break down a monolithic application into independent services. With one exception, most approaches are only applicable under certain conditions. Further concerns are the significant amount of input data some approaches require as well as limited or prototypical tool support.Comment: 13 pages, 4 tables, 2 figures, Software Engineering Aspects of Continuous Development and New Paradigms of Software Production and Deployment, First International Workshop, DEVOPS 2018, Chateau de Villebrumier, France, March 5-6, 2018, Revised Selected Paper