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Dániel Horváth 0001

dblp:83/7257-1 · DBLP profile ↗
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3ranked-venue papers
1as first author
3since 2021 · last 2025
0000-0001-8855-921XORCID · conflict

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

Software engineering, systems software and programming languages · 2 · 2 since 2021Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 first-author · 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.

Software engineering, system software, and programming languages
1 paper
Debugging and program repair · 100%

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

TopicWeightPapersLastEvidence papers
Debugging and program repair
automated program repair
0.912025
GenProgJS: A Baseline System for Test-Based Automated Repair of JavaScript Programs · IEEE Trans. Software Eng. 2025
Debugging and program repair › automated program repair
generate-and-validate repair
0.912025
GenProgJS: A Baseline System for Test-Based Automated Repair of JavaScript Programs · IEEE Trans. Software Eng. 2025
Debugging and program repair › automated program repair
test-based program repair
0.312025
GenProgJS: A Baseline System for Test-Based Automated Repair of JavaScript Programs · IEEE Trans. Software Eng. 2025

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

mutation operators · 0.9genetic programming · 0.9
YearPublicationVenuePosition
2025 GenProgJS: A Baseline System for Test-Based Automated Repair of JavaScript Programs
abstract
Originally, GenProg was created to repair buggy programs written in the C programming language, launching a new discipline in Generate-and-Validate approach of Automated Program Repair (APR). Since then, a number of other tools has been published using a variety of repair approaches. Some of these still operate on programs written in C/C++, others on Java or even Python programs. In this work, a tool named GenProgJS is presented, which generates candidate patches for faulty JavaScript programs. The algorithm it uses is very similar to the genetic algorithm used in the original GenProg, hence the name. In addition to the traditional approach, solutions used in some more recent works were also incorporated, and JavaScript language-specific approaches were also taken into account when the tool was designed. To the best of our knowledge, the tool presented here is the first to apply GenProg's general generate-and-validate approach to JavaScript programs. We evaluate the method on the BugsJS bug database, where it successfully fixed 31 bugs in 6 open source Node.js projects. These bugs belong to 14 different categories showing the generic nature of the method. During the experiments, code transformations applied on the original source code are all traced, and an in-depth analysis of mutation operators and fine-grained changes are also presented. We share our findings with the APR research community and describe the difficulties and differences we faced while designed this JavaScript repair tool. The source code of GenProgJS is publicly available on Github, with a pre-configured Docker environment where it can easily be launched.
Viktor Csuvik, Dániel Horváth 0001, Márk Lajkó, László Vidács
IEEE Trans. Software Eng.2
2024 Yet Another Miner Utility Unveiling a Dataset: CodeGrain
Dániel Horváth 0001, László Vidács
DATA1
2024 Feature Extraction, Learning and Selection in Support of Patch Correctness Assessment
Viktor Csuvik, Dániel Horváth 0001, László Vidács
ICSOFT2