Biography: Prof. Dr. Hironori Washizaki is a Professor and the Associate Dean of the Research Promotion Division at Waseda University in Tokyo, and a Visiting Professor at the National Institute of Informatics. He also works in industry as Outside Directors of SYSTEM INFORMATION and eXmotion. Hironori currently serves as IEEE Computer Society 1st Vice President 2023. He was awarded Golden Core Member and Distinguished Contributor from IEEE CS. He is leading professional and educational activities, including development of the Guide to the Software Engineering Body of Knowledge (SWEBOK), educational courses, and certification programs. He has published more than 200 research papers in refereed international journals and conferences, including IEEE Computer, IEEE IoT-J, TETC, EMSE, SCICO, ICSE, and ASE. He has led many academia-industry joint research and large-funded projects in software design, reuse, traceability, and quality assurance. He is leading a professional IoT/AI education project called SmartSE. Since 2015, he has been the Convenor of ISO/IEC/JTC1/SC7/WG20 to standardize bodies of knowledge and certifications, and leading adoptions of IEEE CS products SWEBOK and Software Engineering Competency Model (SWECOM) into standards. He is currently running for IEEE Computer Society President-Elect 2024. The election will close on 11 September, 2023.
Title of Speech: SWEBOK Guide Evolution and Its Emerging Areas including Integrated Platform for Multi-View Modeling and Machine Learning Pipelines
Abstract: The Guide to the Software Engineering Body of Knowledge (SWEBOK Guide) published by IEEE Computer Society spells out components of the software engineering discipline, promoting a consistent view of SE worldwide. Hironori has led its evolution project to release its newest version 4, which mainly reflects recent developments in SE practice (such as Agile and DevOps) and the growth of BOK, resulting in new knowledge areas (including software architecture, security, and operations) as well as connections to related areas such as AI. This talk firstly overviews the SWEBOK guide and its latest updates, including new knowledge areas and emerging topic areas, including AI SE. Furthermore, as a part of AI SE, the talk explains how recommended SE practices for modeling and DevOps can be incorporated into machine learning (ML)-based application development and operation. The probabilistic nature of ML leads to a more experimentative development approach, which often results in a disparity between the quality of ML models and other aspects such as business, safety, and the overall system architecture. Herein, Hironori introduces a multi-view modeling framework for ML systems as a solution to this problem. An integrated metamodel supports it to ensure the connection and consistency between different models. The framework provides an integrated platform between the modeling environment and the ML training, performance monitoring, and repair pipelines to facilitate the experimentative nature of ML training and monitoring.