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2018年江苏省计算机软件专委会学术年会大会报告
发布日期:2018-05-04浏览次数:字号:[ ]

报告题目1软件分析与验证中的自动推理技术

报告摘要: 软件分析与验证是提高软件质量、保障软件可靠性和安全性的重要途径。自动推理是软件分析与验证中用到的主要支撑技术之一。本报告将介绍自动推理(特别是可满足性判定)的若干技术及工具。

报告人简介:张健,中国科学院软件研究所研究员、博士生导师。曾先后获得中创软件人才奖、国家杰出青年科学基金、国务院政府特殊津贴。主要研究兴趣包括:自动推理和约束求解,程序静态分析和软件测试。担任《计算机学报》、《中国科学:信息科学》、Journal of Computer Science and Technology、Frontiers of Computer ScienceIEEE Transactions on Reliability、《计算机科学与探索》编委。曾担任ICSEVSTTEIJCARCADESATCOMPSAC等重要国际会议程序委员会委员以及国际会议QRS 2015程序委员会主席。

 

 

报告题目2Object Orientation Meets Big DataPerformance Impact, Restoration, and Thoughts on Language Design

报告摘要: Object orientation (OO) is a powerful programming methodology that lays the foundation for most of today's large-scale software applications, including data-intensive systems such as Spark and Hadoop, which have increasingly large impact on our daily lives.  OO contains a set of abstractions that provide the benefit of modularity and simplicity in programming at the cost of a performance penalty at run time. While this penalty is arguably small for non-data-intensive applications, it can get significantly magnified in ``big data'' systems that create and manipulate billions of data objects, becoming too large to accept in production settings.

In this talk, I will first talk about several mismatches we have observed between widely-used OO abstractions and new behaviors exhibited by modern ``big data'' workloads. I will discuss a set of projects that my group has been working on to mitigate these mismatches. I will finally point out a number of directions for the future design of object-oriented languages that could potentially lead to huge performance wins for ``big data''/machine learning applications.

报告人简介: Harry Xu is an Associate Professor in the Computer Science Department of University of California, Irvine. Harry worked at Microsoft Research as a Visiting Researcher in 2017, where he created and led the development of a project that aims to build an optimizing compiler for multilingual data analytical pipelines, and in particular, Microsoft’s Scope/Cosmos. He worked at IBM T. J. Waston Research Center as a Co-op/intern from 2008 to 2011 where he led the development of a series of runtime bloat detection tools. His research ranges from software engineering, through programming languages and compilers, to runtime/operating/distributed systems and computer architecture. His recent interest is to develop cross-layer techniques that bridge the PL and systems communities – in particular, (1) how to use PL techniques to solve systems (especially Big Data systems) problems, and, conversely, (2) how to solve PL problems (e.g., program analysis scalability, SAT/Datalog solver parallelizability, memory energy efficiency, etc.) with systems and architectural support. Harry is the recipient of the AITO Dahl-Nygaard Prize (2018), a Distinguished Research Award from Ohio State University (2011), as well as a number of Distinguished Paper Award from ACM SIGPLAN and SIGSOFT.

 

报告时间:2018513日上午9:00-10:30

报告地点:二十四桥宾馆副楼三楼玫瑰厅

主办单位:科技处,信息工程学院

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