A survey of software refactoring

By Tom Mens, Tom Tourwé. IEEE Transactions on Software Engineering, 2004

1,349 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Software

View Paper: https://www.semanticscholar.org/paper/f26ebfb09c95753ed6f9dd44af3586031f51fe56

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Miltiadis Allamanis
2. Charles Sutton
3. Uri Alon
4. Premkumar T. Devanbu
5. Graham Neubig
6. Earl T. Barr
7. Omer Levy
8. Eran Yahav

In Information Systems

1. Charles Sutton
2. Miltiadis Allamanis
3. Uri Alon
4. Earl T. Barr
5. Premkumar T. Devanbu
6. Christian Bird
7. Eran Yahav
8. Michael Pradel

In Software

1. Charles Sutton
2. Miltiadis Allamanis
3. Earl T. Barr
4. Premkumar T. Devanbu
5. Uri Alon
6. Christian Bird
7. Graham Neubig
8. Thomas Zimmermann

Citations in the corpus

• Why we refactor? confessions of GitHub contributors (2016, background): “Refactoring is recognized as a fundamental practice to maintain a healthy code base [10, 4, 27, 19].”
• Enabling Flexibility in Process-Aware Information Systems (2012, methodology): “In the SE domain code smells are the most popular method for identifying refactoring opportunities [211].”
• Identification of Move Method Refactoring Opportunities (2009, background): “ACCORDING to several principles and laws of object-oriented design [18], [25], designers should always strive for low coupling and high cohesion.”
• Metamodel Adaptation and Model Co-adaptation (2007, background): “Nowadays, software refactoring [11] is a common practice.”
• CatchUp! Capturing and replaying refactorings to support API evolution (2005, background): “A recent survey by Mens and Tourwe covers refactoring research [7].”
• Learning Performance-Improving Code Edits (2023, methodology): “Machine learning has been applied to improve performance by refactoring code (Mens & Tourwé, 2004; Ag-nihotri & Chug, 2020), identify compiler transformations (Bacon et al., 1994; Talaashrafi, 2022; Mammadli et al., 2021), perform parameter search (Hamadi, 2013; Huang et al., 2019; Kaufman et al.,…”
• Mining Semantic Loop Idioms from Big Code (2016, background): “…on refactoring focuses on developing tools to automatically identify locations to refactor and/or perform refactorings (Binkley et al. 2005; Mens and Tourwé 2004; Dig 2011; Beyls and D’Hollander 2009; Kjolstad and Snir 2010) with tremendous impact: nearly all popular IDEs (e.g. Eclipse,…”
• Information needs for software development analytics (2012, background): “Often indicators related to architectural complexity and code clones are often cited as relevant to targeting refactoring effort [31].”