BEGIN:VCALENDAR VERSION:2.0 PRODID:-//https://techplay.jp//JP CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALDESC:スマートエスイーセミナー: ソフトウェア設計 の技術的負債とモデリングフレームワーク X-WR-CALNAME:スマートエスイーセミナー: ソフトウェア設計 の技術的負債とモデリングフレームワーク X-WR-TIMEZONE:Asia/Tokyo BEGIN:VTIMEZONE TZID:Asia/Tokyo BEGIN:STANDARD DTSTART:19700101T000000 TZOFFSETFROM:+0900 TZOFFSETTO:+0900 TZNAME:JST END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:936987@techplay.jp SUMMARY:スマートエスイーセミナー: ソフトウェア設計の 技術的負債とモデリングフレームワーク DTSTART;TZID=Asia/Tokyo:20240305T185000 DTEND;TZID=Asia/Tokyo:20240305T202000 DTSTAMP:20260429T191413Z CREATED:20240226T140625Z DESCRIPTION:イベント詳細はこちら\nhttps://techplay.jp/event/93698 7?utm_medium=referral&utm_source=ics&utm_campaign=ics\n\nスマートエ スイーセミナー: ソフトウェア設計の技術的負債とモ デリングフレームワーク\nSeminar on Design Technical Debt and M achine Learning System Modeling Framework\n設計のTechnical Debt、機 械学習システムのモデリングフレームワーク\n2024年3月 5日(火)18:50-20:20 March 5th Tue 6:50pm-8:20pm JST 早稲田大学西 早稲田キャンパス＆オンライン\nソフトウェアアーキ テクチャの設計手法ADDや評価手法ATAM\, SAAMなどを提案 され、書籍『実践ソフトウェアアーキテクチャ』や書 籍『Technical Debt in Practice: How to Find It and Fix It』の著者 として著名なソフトウェアアーキテクチャならびに技 術的負債の第一人者Rick Kazman教授（ハワイ大学、CMU/SEI 、IEEE Computer Society理事）ならびに技術的負債やアーキ テクチャ・ビッグデータ解析で著名なHong-Mei Chen教授（ ハワイ大学）が来日されることを記念し、複雑・不確 実な開発運用時代に重要性を増すソフトウェア設計と モデリングについてセミナーを開催します。具体的に はChen教授から技術的負債の概念を解説いただき、続い てKazman教授から設計における技術的負債のプロジェク トへの影響や特定ならびに修正のアプローチについて 解説いただきます。さらに、JST未来社会eAIプロジェク トにおける早稲田大学チーム（チーム代表: 鷲崎）に おける機械学習システムの設計を含むモデリングフレ ームワークの取り組みを解説します。なおすべて英語 による実施となります。ぜひご参加下さい。\nProf. Rick Kazman (University of Hawaii and CMU/SEI)\, the author of the books "Soft ware Architecture in Practice" and "Technical Debt in Practice: How to Fi nd It and Fix It" and a leading expert on software architecture\, and Pro f. Hong-Mei Chen (University of Hawaii)\, a well-known expert on technica l debt\, architecture and big data analysis\, will visit Japan to give a seminar on software design and modeling\, which are becoming increasingly important in the era of complex and uncertain development operations. Pr ofessor Chen will explain the concept of technical debt\, followed by Pro fessor Kazman's presentation on the impact of technical debt in design on projects and approaches to identify and correct it. In addition\, the Wa seda University ML framework team led by Prof. Washizaki will explain a m odeling framework that includes the design of machine learning systems. A ll sessions will be conducted in English. We look forward to seeing you t here.\n主催\n\nスマートエスイー\n\n協賛・協力\n\n早稲田 大学グローバルソフトウェアエンジニアリング研究所\ n\n概要\n\n日時: 2024年3月5日（火）18:50-20:20\n場所: 早稲 田大学西早稲田キャンパス 63号館 5階 0506会議室、なら びに、オンラインZoom\n参加申込: 本connpassページからお 申し込みください\n\nプログラム（個々の時間や内容は 変更の可能性があります）\n18:50-18:55 オープニング Open ing\n18:55-19:10 Introduction on Technical Debt（技術的負債とは ）\nProf. Hong-Mei Chen (University of Hawaii at Manoa)\n\nBiography: Ho ng-Mei Chen is a Professor of Information Technology Management at the Sh idler College of Business of the University of Hawaii at Manoa. She form erly served as Associate Dean for the College and was the Founder and Dir ector of the Advanced Information Management Solutions (AIMS) Lab. She h as won prestigious teaching excellence awards at the college\, community\ , and university levels. \nShe conducts cross-disciplinary empirical res earch on information systems design and development including technology adoption\, frequently working with many executives of Fortune 100 compani es. She has obtained multi-million-dollar grants and directed several la rge-scale\, multi-institution research projects. She directed and implem ented the image database system for the DARPA MISSION project utilizing N ASA experimental satellites. She was the director for the National Data C enter for the $34 million Electrical Vehicle development program. She ser ves on US NSF (National Science Foundation) review panels and a NSF large grant (>$25 million) management team. She has published in prestigious MIS and Software Engineering journals in areas such as social debt\, big data engineering and management\, software architecture\, innovation-driv en system design methods\, green information systems\, cybersecurity\, cr owd-sourced systems\, social CRM (customer relationship management)\, bus iness-IT alignment\, service engineering\, distributed database\, and AI. \n19:10-19:50 Finding and Fixing Design Debt（設計における技術 的負債の発見と修正）\nProf. Rick Kazman (University of Hawaii\, CMU/SEI)\nIn this talk I will discuss a common and pernicious form of te chnical debt--called design debt\, or architecture debt. I will briefly p resent the theoretical foundation behind this form of debt and present a broad set of evidence demonstrating its dramatic effects on project outco mes. That is the bad news. The good news is that we can automatically pin point the causes and scope of such debt. I will describe how we can autom atically locate it\, measure it\, and create the business case for removi ng it. Finally\, I will explain how we can remove--pay down--this debt vi a refactoring. I will also sketch some of my experiences doing all of thi s in real-world projects\, along with the outcomes.\n\nBiography: Rick Ka zman is the Danny and Elsa Lui Distinguished Professor of Information Tec hnology Management at the University of Hawaii and a Visiting Researcher at the Software Engineering Institute of Carnegie Mellon University. His primary research interests are software architecture\, design and analysi s tools\, software visualization\, and technical debt. Kazman has been in volved in the creation of several highly influential methods and tools fo r architecture analysis\, including the ATAM (Architecture Tradeoff Analy sis Method) and the Titan and DV8 tools. He is the author of over 250 pub lications\, co-author of three patents and eight books\, including Softwa re Architecture in Practice\, Technical Debt: How to Find It and Fix It\, Designing Software Architectures: A Practical Approach\, Evaluating Soft ware Architectures: Methods and Case Studies\, and Ultra-Large-Scale Syst ems: The Software Challenge of the Future. His research methods and tools have been adopted by many Fortune 1000 companies and has been cited over 29\,000 times\, according to Google Scholar. He is currently a member of the IEEE Computer Society’s Board of Governors\, an Associate Editor f or IEEE Transactions on Software Engineering\, and a member of the ICSE S teering Committee.\n19:50-20:10 Multi-view modeling framework for reliabl e machine learning systems（高信頼機械学習システムのため のマルチビュー・モデリングフレームワーク）\nJati H. Husen\, Jomphon Runpakprakun\, Hironori Washizaki (Waseda University)\nTo address the analysis between the experimental nature of machine learning and the deterministic side of traditional software engineering requires specific approaches. To address the challenge\, the eAI project's framewo rk team is developing a Multi-view Modeling Framework for ML Systems (M3S ) as a model-based framework that facilitates consistent and comprehensiv e analysis of ML systems. The analysis includes integrating the modeling environment and the ML pipelines to facilitate the highly experimental ch aracteristics of ML models\, in which a series of training and evaluation s are conducted with different solutions and configura\ntions to identify an ML model version that satisfies all requirements. These integrations are based on a cohesive metamodel to ensure analysis consistency. The und erlying approach of M3S supports a reliable and comprehensive analysis of the ML system while ensuring tight synchronization with the implementati on. This synchronization provides the base for a feedback loop between th e analysis and the implementation at both the ML model and the overall sy stem levels. \n20:10-20:20 議論とクロージング Closing LOCATION:早稲田大学西早稲田キャンパス 63号館 5階 0506会 議室 東京都新宿区大久保3-4-1 URL:https://techplay.jp/event/936987?utm_medium=referral&utm_source=ics&utm _campaign=ics END:VEVENT END:VCALENDAR