第58回先端ソフトウェア科学･工学に関するGRACEセミナー
今回のGRACEセミナーは2件の講演からなります．まず，Rutgers 大学の
Chung-chieh Shan 博士が確率的プログラムの最適化について講演します。
次に，NIIの胡振江教授が「双方向モデル変換によるソフトウェア進化」に関する
NIIグランドチャンレンジ研究プロジェクトの最新の研究成果を分かりやすく
説明します。
日時：2012年4月10日（火）15:00-17:00
場所：国立情報学研究所(NII)（地図）
20階 ミーティングルーム1・2（2009・2010）
参加費：無料
お問い合わせ：田辺良則(seminar-steering_AT_grace-center.jp)_AT_を＠に書き換えてください。
参加ご希望の方は，下記よりご登録をお願いいたします:
http://form1.fc2.com/form/?id=489702
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Speaker 1: Chung-chieh Shan (Rutgers University)
Title: Lifted inference: normalizing loops by evaluation
Many loops in probabilistic inference map almost every individual in
their domain to the same result. Running such loops symbolically takes
time sublinear in the domain size. Using normalization by evaluation
with first-class delimited continuations, we _lift_ inference procedures
to reap this speed-up without interpretive overhead. To express
nested loops, we use multiple control delimiters for metacircular
interpretation. To express loops over a powerset domain, we convert
nested loops over a subset to unnested loops.
Bio:
Chung-chieh Shan received his PhD in computer science from Harvard
University in 2005. He then joined the faculty of Rutgers University
in the department of computer science and the center of cognitive
science. Since 2011, he has been visiting the department of linguistics
at Cornell University and the department of computer science at the
University of Tsukuba.
Speaker 2: Zhenjiang Hu (National Institute of Informatics)
Title: Bidirectional Model Transformation for High-Confidence Software
Evolution
Model transformations are a key element in the OMG’s Model Driven
Development agenda, providing a standard way to represent and
transform software artifacts such as requirements, design models,
program code, tests, configuration files, and documentation in
software development. However, after a transformation is applied, the
source and the target models usually co-exist and evolve
independently. How to propagate modifications correctly across models
in different formats and guarantee system consistency remains as a big
challenge. In this talk, I will show that well-behaved bidirectional
model transformations play an important role in making software
evolution be more robust and trusty, and demonstrate how the
bidirectional transformation system GRoundTram can be effectively used
for development of evolutionary software with high confidence.
Bio:
Zhenjiang Hu is Professor of National Institute of Informatics (NII).
He received his BS and MS from Shanghai Jiao Tong University
in 1988 and 1991 respectively, and PhD degree from University of Tokyo
in 1996. He was a lecturer (1997-1999) and an associate professor
(2000-2007) in University of Tokyo, before joining NII as a full
professor in 2008. His main interest is in programming languages and
software engineering in general, and functional programming, parallel
programming and bidirectional model-driven software development in
particular.
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