RENAS: Prioritizing Co-Renaming Opportunities of Identifiers
August 19, 2024 Β· Declared Dead Β· π IEEE International Conference on Software Maintenance and Evolution
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Naoki Doi, Yuki Osumi, Shinpei Hayashi
arXiv ID
2408.09716
Category
cs.SE: Software Engineering
Citations
1
Venue
IEEE International Conference on Software Maintenance and Evolution
Last Checked
5 months ago
Abstract
Renaming identifiers in source code is a common refactoring task in software development. When renaming an identifier, other identifiers containing words with the same naming intention related to the renaming should be renamed simultaneously. However, identifying these related identifiers can be challenging. This study introduces a technique called RENAS, which identifies and recommends related identifiers that should be renamed simultaneously in Java applications. RENAS determines priority scores for renaming candidates based on the relationships and similarities among identifiers. Since identifiers that have a relationship and/or have similar vocabulary in the source code are often renamed together, their priority scores are determined based on these factors. Identifiers with higher priority are recommended to be renamed together. Through an evaluation involving real renaming instances extracted from change histories and validated manually, RENAS demonstrated an improvement in the F1-measure by more than 0.11 compared with existing renaming recommendation approaches.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted