Feature location in source code: a taxonomy and survey
By Bogdan Dit, Meghan Revelle, Malcom Gethers, Denys Poshyvanyk. J. Softw. Evol. Process., 2013
630 citations recorded by the source corpus.
Subfields: Information Systems, Software
View Paper: https://www.semanticscholar.org/paper/ad302689fbc6841d7960d97774cccd0869145156
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems
- Charles Sutton
- Miltiadis Allamanis
- Jaroslav M. Fowkes
- Denys Poshyvanyk
- Nicholas A. Kraft
- Kostadin Damevski
- Christopher S. Corley
- Massimiliano Di Penta
In Software
- Charles Sutton
- Miltiadis Allamanis
- Jaroslav M. Fowkes
- Denys Poshyvanyk
- Nicholas A. Kraft
- Massimiliano Di Penta
- Rocco Oliveto
- Andrea De Lucia
Citations in the corpus
- Improving bug localization using structured information retrieval (2013, background): “, moreBugs [30]) and perform function/method level bug localization [9].”
- Autofolding for Source Code Summarization (2014, background): “, variable names) are information-rich and have been shown to be important for tasks such as feature location [30], [31].”
- Software development in startup companies: A systematic mapping study (2014, background): “…there exist reviews that studied software engineering topics pertinent to specific contexts or environments (as opposed to reviews that investigated individual software engineering technologies, e.g. feature location [40] or search-based software testing [41]) that we consider as related work.”
- Why we refactor? confessions of GitHub contributors (2016, methodology): “This could be achieved by leveraging the recent advancements in feature location [8] and requirements tracing to automatically locate the code associated with a feature or bug fix request, or a requirement change, and recommend suitable refactorings that will make easier the completion of the mainte”
- How to effectively use topic models for software engineering tasks? An approach based on Genetic Algorithms (2013, background): “For more information about the datasets refer to [4].”
- Exploring the use of deep learning for feature location (2015, background): “Due to the difficulty and importance of this task, researchers have proposed a number of approaches to improve developers’ effectiveness in locating features, largely based upon applying natural language analysis or text retrieval techniques to source code [1].”
- IssueExec: A Test-Driven Approach for Localizing Software Engineering Issues (2026, unknown): “Related research in Feature Location [16] and dynamic analysis has demonstrated that execution scenarios and traces can provide direct evidence of functional behavior [17, 41].”