To prospective students

The Reliable Software Engineering, Washizaki Laboratory welcomes applications for admissions from highly motivated and qualified, especially students with MEXT scholarships, having knowledge about (or being interested in) software engineering and related areas, such as the following but not limited to:

  • Machine learning software engineering: Software engineering approaches for machine learning systems and software development, such as a modeling framework for supporting the development of machine learning systems (MLS)(e.g., MODELSWARD’23), safety risk assessment of MLS, MLOps workflow pipeline integration, documenting and detecting machine learning design patterns (e.g., Computer’22), IoT design patterns (e.g., IoT-J’20), empirical study on change and defects in MLS as well as developers’ practices (e.g., SQJ’24)
  • Software engineering with machine learning and natural language processing (NLP): Application of NLP and ML to reliable and efficient software systems development and operation, such as detecting object-oriented design patterns by machine learning, software development documentation and other applications of natural language processing and machine learning, data-driven persona and requirements engineering (e.g., IJSEKE’21), security knowledge and document tracing and structuring (e.g., Applied Sciences’22IRI’22), bug reports and related issue reports and tickets  analysis (e.g., EASE’23Frontiers’23Applied Sciences’22), agile development and process analysis (e.g., EASE’23Agile’12)
  • Software quality engineering: Advanced engineering approaches for software quality assurance often involving the application of NLP/ML, such as automatic program modification and empirical research, visualization of program repair (e.g., SEKE’23), software reliability evaluation and prediction (e.g., Mathematics’21), program quality measurement, evaluation and improvement (e.g., ICSE’19ENASE’20), combinatorial testing and reuse (e.g., PeerJ’21)
  • Program analysis: Program code static and dynamic analysis as well as its application in education, such as code-clone analysis (e.g., IWSC’20), programming learning and teaching supports (e.g., SIGCSE’18)
  • Programming and STEM education: Approaches for K-12 and other STEM education, such as a framework for programming education, ICT, and introductory programming education supports (e.g., Education Sciences’22)

Send a copy of the following documents (in English or Japanese) to Prof. Washizaki by e-mail with the subject of “Application to [Master | Doctor] Course ( YOUR NAME HERE ).”

  • Curriculum vitae including your name, address, education qualification, research and working experiences, and list of publications. Suppose you are a doctor course applicant and have a number of papers (especially first-author ones) in international journals and international conferences. In that case, the list of papers is encouraged to submit.
  • Research proposal (or what do you want to study in the laboratory) related to the above-mentioned topics
  • School academic record (undergraduate and/or masters course), including your cumulative GPA (grade point average) on a 4.0 scale (A = 4, B = 3, C = 2, D = 1). 3.0 or higher is required.
  • Certificate of your bachelor’s (and master’s) degree(s).
  • Recommendation letter from your supervisor
  • Your photograph (if this is not included in your CV)
  • Other supportive documents if you have, such as the GRE as well as language test scores