We provide an extensive overview of existing research in the field of software refactoring. This research is compared and discussed based on a number of different criteria: the refactoring activities that are supported, the specific techniques and formalisms that are used for supporting these activities, the types of software artifacts that are being refactored, the important issues that need to be taken into account when building refactoring tool support, and the effect of refactoring on the software process. A running example is used to explain and illustrate the main concepts.

/pdf/a-survey-of-software-refactoring-kgrdghit3u.pdf

A survey of software refactoring

Technical debt is a metaphor introduced by Cunningham to indicate “not quite right code which we postpone making it right”. One noticeable symptom of technical debt is represented by code smells, defined as symptoms of poor design and implementation choices. Previous studies showed the negative impact of code smells on the comprehensibility and maintainability of code. While the repercussions of smells on code quality have been empirically assessed, there is still only anecdotal evidence on when and why bad smells are introduced, what is their survivability , and how they are removed by developers. To empirically corroborate such anecdotal evidence, we conducted a large empirical study over the change history of 200 open source projects. This study required the development of a strategy to identify smell-introducing commits, the mining of over half a million of commits, and the manual analysis and classification of over 10K of them. Our findings mostly contradict common wisdom, showing that most of the smell instances are introduced when an artifact is created and not as a result of its evolution. At the same time, 80 percent of smells survive in the system. Also, among the 20 percent of removed instances, only 9 percent are removed as a direct consequence of refactoring operations.

When and Why Your Code Starts to Smell Bad (and Whether the Smells Go Away)

It is widely believed that refactoring improves software quality and developer productivity. However, few empirical studies quantitatively assess refactoring benefits or investigate developers' perception towards these benefits. This paper presents a field study of refactoring benefits and challenges at Microsoft through three complementary study methods: a survey, semi-structured interviews with professional software engineers, and quantitative analysis of version history data. Our survey finds that the refactoring definition in practice is not confined to a rigorous definition of semantics-preserving code transformations and that developers perceive that refactoring involves substantial cost and risks. We also report on interviews with a designated refactoring team that has led a multi-year, centralized effort on refactoring Windows. The quantitative analysis of Windows 7 version history finds that the binary modules refactored by this team experienced significant reduction in the number of inter-module dependencies and post-release defects, indicating a visible benefit of refactoring.

/pdf/a-field-study-of-refactoring-challenges-and-benefits-59mr3dripq.pdf

A field study of refactoring challenges and benefits

It is widely believed that refactoring improves software quality and developer productivity. However, few empirical studies quantitatively assess refactoring benefits or investigate developers’ perception towards these benefits. This paper presents a field study of refactoring benefits and challenges at Microsoft through three complementary study methods: a survey, semi-structured interviews with professional software engineers, and quantitative analysis of version history data. Our survey finds that the refactoring definition in practice is not confined to a rigorous definition of semantics-preserving code transformations and that developers perceive that refactoring involves substantial cost and risks. We also report on interviews with a designated refactoring team that has led a multi-year, centralized effort on refactoring Windows. The quantitative analysis of Windows 7 version history finds the top 5 percent of preferentially refactored modules experience higher reduction in the number of inter-module dependencies and several complexity measures but increase size more than the bottom 95 percent. This indicates that measuring the impact of refactoring requires multi-dimensional assessment.

/pdf/an-empirical-study-of-refactoringchallenges-and-benefits-at-2drp19tdfr.pdf

An Empirical Study of RefactoringChallenges and Benefits at Microsoft

An experimental investigation on the innate relationship between quality and refactoring

Program refactoring is a technique to enhance the maintainability of a program. Although the concept itself is considered to be effective, there are few quantitative evaluation of its impact to the software maintainability. It is sometimes difficult to judge whether the refactoring in question should be applied or not without knowing the effect accurately. We propose a quantitative evaluation method to measure the maintainability enhancement effect of program refactoring. We focused on the coupling metrics to evaluate the refactoring effect. By comparing the coupling before and after the refactoring, we could evaluate the degree of maintainability enhancement. We applied our method to a certain program and showed that our method was really effective to quantify the refactoring effect and helped us to choose appropriate refactorings.

https://www2.computer.org/portal/web/csdl/doi/10.1109/ICSM.2002.1167822

A quantitative evaluation of maintainability enhancement by refactoring

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A quantitative evaluation of maintainability enhancement by refactoring