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Inase Kondo

dblp:437/8644 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2026
0009-0003-2907-9592ORCID · corroborated

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

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

Software engineering, system software, and programming languages
1 paper
Debugging and program repair · 87% Empirical software engineering · 13%

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

TopicWeightPapersLastEvidence papers
Debugging and program repair
fault localization
1.012026
MV-SZZ: An Empirical Study of a Majority Voting-Based SZZ Method · IEEE Trans. Software Eng. 2026
Debugging and program repair › regression debugging › failure-inducing change identification
SZZ algorithm
1.012026
MV-SZZ: An Empirical Study of a Majority Voting-Based SZZ Method · IEEE Trans. Software Eng. 2026
Empirical software engineering
mining software repositories
0.312026
MV-SZZ: An Empirical Study of a Majority Voting-Based SZZ Method · IEEE Trans. Software Eng. 2026

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

majority voting · 1.0
YearPublicationVenuePosition
2026 Why Are Agentic Pull Requests Merged or Rejected? An Empirical Study
Sien Reeve Ordonez Peralta, Fumika Hoshi, Hironori Washizaki, Naoyasu Ubayashi, Inase Kondo, Yoshiki Higo, Hiroki Mukai, Norihiro Yoshida, Kazuki Kusama, Hidetake Tanaka, Youmei Fan
MSR5
2026 MV-SZZ: An Empirical Study of a Majority Voting-Based SZZ Method
Inase Kondo, Masanari Kondo, Daniel M. Germán, Yasutaka Kamei, Yoshiki Higo
IEEE Trans. Software Eng.1