activity
20232026
most citedExploring the Effect of Multiple Natural Languages on Code Suggestion Using GitHub Copilot

1 citations · 1 across the 20 of their papers we have counts for

collaborators

24 papers

cs.SE2026

Rethinking SZZ Search Strategies: Lessons from Claude Code

Inase Kondo, Masanari Kondo, Daniel M. German +3

Identifying bug-inducing commits (BICs) is important for studying software bugs and maintaining software, yet the accuracy of existing SZZ methods remains limited. Although various…

cs.SE2026

PreMaQ: Predicting Maintainability-Related Quality of LLM-Generated Code Before Generation

Taiki Wakamatsu, Yuta Ishimoto, Masanari Kondo +1

As large language models (LLMs) become increasingly capable of code generation, adopting generated code in software development requires assessing not only its functional correctne…

cs.SE2026

Multi-SWT-Bench: A Multilingual Benchmark for Reproduction Test Generation

Kazuki Kusama, Sota Nakashima, Haruka Tokumasu +3

Reproduction test generation translates a natural-language issue description into executable tests that fail on the original code and pass after the issue is resolved, providing ex…

cs.SE2026

A Study on the Impact of Natural Language Differences in Prompts on Automatic Code Generation Using LLMs

Haruka Tokumasu, Masanari Kondo, Alexander Serebrenik +5

Large Language Models (LLMs) have demonstrated remarkable performance in automatic code generation tasks, thereby encouraging new research in this area. Although numerous studies h…

cs.SE2026

Exploring the Potential of Program Flowcharts on Code Generation Using Multimodal LLMs

Yuki Toi, Tao Xiao, Kazushi Tomoto +2

In recent years, Large Language Models (LLMs) have made significant strides, leading to the emergence of multimodal LLMs capable of processing diverse inputs such as images and aud…

cs.SE2026

ThinkLog: Leveraging Reasoning for Log Statement Generation

Kazuki Kusama, Honglin Shu, Masanari Kondo +2

Runtime logs are an important source of information that supports software maintenance. To obtain useful logs, developers spend significant effort identifying appropriate log locat…

cs.SE2026

How Well Do LLMs Generate Taxonomies in the SE Domain? A Multi-perspective Evaluation Framework

Sota Nakashima, Yuta Ishimoto, Masanari Kondo +2

Taxonomies provide a shared conceptual framework for organizing heterogeneous observations in software engineering (SE) research. Manually constructing such taxonomies is labor-int…

cs.SE2026

Directed Symbolic Execution for Vulnerability Discovery: An LLM-Guided Approach in KLEE

Lingfeng Chen, Tao Xiao, Masanari Kondo +1

Symbolic execution effectively discovers security violations but suffers from path explosion. Engines like KLEE therefore use path prioritization heuristics to order state explorat…

cs.SE2026

RepTran: Search-Based Repair of Transformer Models

Yuta Ishimoto, Paolo Arcaini, Fuyuki Ishikawa +3

To ensure the overall quality of AI-enabled software, not only traditional software components but also AI components need to be tested and repaired. Among AI components, Transform…

cs.SE2026

Leveraging Language Models for Log Statement Generation in Multilingual Scenarios: How Far Are We?

Kazuki Kusama, Honglin Shu, Masanari Kondo +1

Log statements capture critical information for software maintenance activities such as testing, debugging, and failure analysis. Because of this importance, developers must carefu…

cs.SE2026

"Refactoring Runaway": Understanding and Mitigating Tangled Refactorings in Coding Agents for Issue Resolution

Zhao Tian, Zifan Zhang, Tao Xiao +4

Recent advances in coding agents have shown remarkable progress in software issue resolution. In practice, real-world issues are typically bug fixes or feature requests in which hu…

cs.SE2026

Toward Linking Declined Proposals and Source Code: An Exploratory Study on the Go Repository

Sota Nakashima, Masanari Kondo, Mahmoud Alfadel +4

Traceability links are key information sources for software developers, connecting software artifacts. Such links play an important role, particularly between contribution artifact…

cs.SE2026

Why Agentic-PRs Get Rejected: A Comparative Study of Coding Agents

Sota Nakashima, Yuta Ishimoto, Masanari Kondo +2

Agentic coding -- software development workflows in which autonomous coding agents plan, implement, and submit code changes with minimal human involvement -- is rapidly gaining tra…

cs.SE2026

Leveraging Mutation Analysis for LLM-based Repair of Quantum Programs

Chihiro Yoshida, Yuta Ishimoto, Olivier Nourry +4

In recent years, Automated Program Repair (APR) techniques specifically designed for quantum programs have been proposed. However, existing approaches often suffer from low repair…

cs.SE2025

AILINKPREVIEWER: Enhancing Code Reviews with LLM-Powered Link Previews

Panya Trakoolgerntong, Tao Xiao, Masanari Kondo +4

Code review is a key practice in software engineering, where developers evaluate code changes to ensure quality and maintainability. Links to issues and external resources are ofte…

cs.SE2025

An empirical study on declined proposals: why are these proposals declined?

Masanari Kondo, Mahmoud Alfadel, Shane McIntosh +2

Design-level decisions in open-source software (OSS) projects are often made through structured mechanisms such as proposals, which require substantial community discussion and rev…

cs.SE2025

How Small is Enough? Empirical Evidence of Quantized Small Language Models for Automated Program Repair

Kazuki Kusama, Honglin Shu, Masanari Kondo +1

Background: Large language models (LLMs) have greatly improved the accuracy of automated program repair (APR) methods. However, LLMs are constrained by high computational resource…

cs.SE2025

How Far Have LLMs Come Toward Automated SATD Taxonomy Construction?

Sota Nakashima, Yuta Ishimoto, Masanari Kondo +2

Technical debt refers to suboptimal code that degrades software quality. When developers intentionally introduce such debt, it is called self-admitted technical debt (SATD). Since…

cs.SE2025

Evaluating Mutation-based Fault Localization for Quantum Programs

Yuta Ishimoto, Masanari Kondo, Naoyasu Ubayashi +4

Quantum computers leverage the principles of quantum mechanics to execute operations. They require quantum programs that define operations on quantum bits (qubits), the fundamental…

cs.SE2024

Myth: The loss of core developers is a critical issue for OSS communities

Olivier Nourry, Masanari Kondo, Shinobu Saito +3

Throughout their lifetime, open-source software systems will naturally attract new contributors and lose existing contributors. Not all OSS contributors are equal, however, as some…

cs.SE2024

An Empirical Study of Token-based Micro Commits

Masanari Kondo, Daniel M. German, Yasutaka Kamei +2

In software development, developers frequently apply maintenance activities to the source code that change a few lines by a single commit. A good understanding of the characteristi…

cs.SE2024

OSS Myths and Facts

Yukako Iimura, Masanari Kondo, Kazushi Tomoto +3

We have selected six myths about the OSS community and have tested whether they are true or not. The purpose of this report is to identify the lessons that can be learned from the…

cs.SE2024★ 1 cited

Exploring the Effect of Multiple Natural Languages on Code Suggestion Using GitHub Copilot

Kei Koyanagi, Dong Wang, Kotaro Noguchi +4

GitHub Copilot is an AI-enabled tool that automates program synthesis. It has gained significant attention since its launch in 2021. Recent studies have extensively examined Copilo…

cs.SE2023

When Conversations Turn Into Work: A Taxonomy of Converted Discussions and Issues in GitHub

Dong Wang, Masanari Kondo, Yasutaka Kamei +2

Popular and large contemporary open-source projects now embrace a diverse set of documentation for communication channels. Examples include contribution guidelines (i.e., commit me…