activity
20242026
collaborators

22 papers

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…