Mutation Operators for Code Annotations

Pinheiro, Pedro; Viana, José Carlos Posada; Fernandes, Leonardo; Ribeiro, Márcio; Ferrari, Fabiano Cutigi; Fonseca, Baldoíno; Gheyi, Rohit

doi:10.1145/3266003.3266006

Cited by 5 publications

(1 citation statement)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To address these three problems, we propose CodeHunter, which uses both code and code annotation information to represent the code. Code annotation [10][11][12][13] can be treated as an irreplaceable part of the software, it is also a core component of APIs and frameworks for enterprise development. It plays a very important role in helping communicate key program capabilities in software development.…”

Section: Introductionmentioning

confidence: 99%

Boosting Code Search with Structural Code Annotation

Kong

Chen

et al. 2022

Electronics

View full text Add to dashboard Cite

Code search is a process that takes a given query as input and retrieves relevant code snippets from a code base. The relationship between query and code is commonly built on code annotation, which is extracted from code comments or other documents. The current code search studies approximately treat code annotation as a common natural language, regardless of its hidden structural information. To address the information loss, this work proposes a code annotation model to extract features from five perspectives, and further conduct a code search engine, i.e., CodeHunter. CodeHunter is evaluated on a dataset of 7 million code snippets and query descriptions. The experimental results show that CodeHunter obtains more effective results than Lucene and DeepCS. And we also prove that the effectiveness comes from the rich features and search models, CodeHunter can work well with different sizes of query descriptions.

show abstract

Section: Introductionmentioning

confidence: 99%