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Ishikawa Lab
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A lab that supports software reliability with AI and formal methods.
AboutAbout the lab
Assuring smart systems in a smart way.
The Ishikawa Lab studies technologies for making software trustworthy, and the relationship between AI and software engineering.
With the vision of "smart systems and smart dependability assurance," the lab operates as a research group that spans multiple organizations.
Prof. Ishikawa belongs to the National Institute of Informatics (NII), and the lab also accepts graduate students from SOKENDAI (The Graduate University for Advanced Studies) and The University of Electro-Communications.
Most of the students accepted at The University of Electro-Communications are working professionals in the doctoral program.
Key terms
- Formal methods
- Methods for writing the specifications and designs of software rigorously using mathematical descriptions, and for verifying them
- Safety case
- A method of laying out, step by step and with supporting evidence, the reasons why a system can be said to be safe
- Fault localization
- The task of narrowing down where in a program the cause of a bug lies
ResearchResearch themes
With the vision of "smart systems and smart dependability assurance," the lab studies software engineering for building trustworthy systems. It also works on research that uses AI in software engineering, and on software engineering research that targets AI systems.
*Illustrative imageTechnologies for trustworthy software
Within software engineering, the lab works on technologies that support dependability and trust. Its subjects are formal methods (such as Event-B and Alloy), testing (such as search-based testing), requirements analysis, and safety cases.
Using AI in software engineering
This research applies AI to software engineering. Topics include automated test generation, automated repair of models and programs, optimization of designs and services, bug analysis and fault localization, and the use of large language models (LLMs) and generative AI.
*Illustrative imageSoftware engineering for AI
This area is known as AI engineering or machine learning engineering. The lab applies automated test generation, design optimization, bug analysis and fault localization, and safety cases to deep learning models, autonomous driving systems, large language model and generative AI systems, service-oriented and cloud systems, games, and more.
MembersFaculty
The Ishikawa Lab's members include a Project Associate Professor, project researchers, external researchers, visiting faculty, graduate students, research students, and interns from overseas universities.As of 2026
- ProfessorFuyuki Ishikawa
- Project Associate ProfessorPaolo Arcaini
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Bridge Global developers' bay, Apr 2019” Arunvrparavur / CC BY-SA 4.0 (cropped)
- Technologies for trustworthy software: “SeL4 design” Tiir IIR / CC BY-SA 4.0 (cropped)
- Software engineering for AI: “ISEAUTO, the Lab for Self-Driving Vehicles in TalTech” Lauri Veerde / CC BY 4.0 (cropped)
- Related lab (田原 康之 研究室): “Fujikura optic fiber at Science Museum” Syced / CC0 (cropped)
- Related lab (織田 健 研究室): “TestingCup-Polish-Championship-in-Software-Testing-Katowice-2016” Radosław Smilgin / CC BY-SA 3.0 (cropped)
- Related lab (加納 龍一
研究室): “Simplified neural network example” Mikael Häggström, M.D. Author info - Reusing images- Conflicts of interest: None Mikael Häggström, M.D. / CC0 (cropped) - Related lab (藤田 秀之 研究室): “Data Visualization of Street Trees” Intel Free Press / CC BY-SA 2.0 (cropped)
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