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Byeongguk Kwak

dblp:394/9471 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none

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

Software engineering, systems software and programming languages · 1 · 1 since 2021

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
Program synthesis and code generation · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › query formulation
query synthesis
0.912025
Synthesizing Document Database Queries Using Collection Abstractions · ICSE 2025
Program synthesis and code generation
programming by example
0.312025
Synthesizing Document Database Queries Using Collection Abstractions · ICSE 2025

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

domain-specific language · 1.7collection abstraction · 1.7
YearPublicationVenuePosition
2025 Synthesizing Document Database Queries Using Collection Abstractions
abstract
Document databases are increasingly popular in various applications, but their queries are challenging to write due to the flexible and complex data model underlying document databases. This paper presents a synthesis technique that aims to generate document database queries from input-output examples automatically. A new domain-specific language is designed to express a representative set of document database queries in an algebraic style. Furthermore, the synthesis technique leverages a novel abstraction of collections for deduction to efficiently prune the search space and quickly generate the target query. An evaluation of 110 benchmarks from various sources shows that the proposed technique can synthesize 108 benchmarks successfully. On average, the synthesizer can generate document database queries from a small number of input-output examples within tens of seconds.
Qikang Liu, Yanwen Cai, Byeongguk Kwak, Yuepeng Wang 0001
ICSE4