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Xiran Liang

dblp:272/5258 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%
Software engineering, system software, and programming languages
1 paper
Software maintenance and evolution · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › document retrieval › domain-specific retrieval
code search
0.412020
OCoR: An Overlapping-Aware Code Retriever · ASE 2020
Information retrieval › document retrieval › domain-specific retrieval › code search
neural code search
0.412020
OCoR: An Overlapping-Aware Code Retriever · ASE 2020
Software maintenance and evolution
code reuse
0.112020
OCoR: An Overlapping-Aware Code Retriever · ASE 2020

Methods — techniques the papers use, named apart from their topics

overlap-aware embedding · 0.9neural network · 0.9
YearPublicationVenuePosition
2020 OCoR: An Overlapping-Aware Code Retriever
abstract
Code retrieval helps developers reuse code snippets in the open-source projects. Given a natural language description, code retrieval aims to search for the most relevant code relevant among a set of code snippets. Existing state-of-the-art approaches apply neural networks to code retrieval. However, these approaches still fail to capture an important feature: overlaps. The overlaps between different names used by different people indicate that two different names may be potentially related (e.g., "message" and "msg"), and the overlaps between identifiers in code and words in natural language descriptions indicate that the code snippet and the description may potentially be related.
Qihao Zhu, Zeyu Sun 0004, Xiran Liang, Yingfei Xiong 0001, Lu Zhang 0023
ASE3