报告题目：Automating Software Quality Assurance: Approaches and Perspectives
报告人：Artur Andrzejak
单位：Heidelberg University
报告时间：2015年11月18日（周三）上午10:15-11:15
地点：软件学院第二多媒体教室（合肥工业大学翡翠湖校区图书馆一楼）
报告摘要：
The number of software developers worldwide is likely to increase by 40% in the next four years, from 18.2 million in 2014 to est. 26.4 million by 2019 (source: IDC and Evans Data Corp.). This demonstrates the growing demand for software, and points to some challenges: How to support young software engineers in creating high-quality, reliable software in face of increasingly complex and interdependent systems? How to reduce the overall cost of software development and maintenance, in particular of quality assurance?
In this talk we illustrate on case studies taken from software testing and debugging how automation can address these challenges. We first discuss how scalable machine learning could help in recognizing spurious test results in a very large software project at SAP AG. Next we present techniques for detecting and isolating certain types of latent software defects which typically manifest in a deployment scenario. Consequently, such defects are expensive and difficult to locate. Finally, we look at a method for automated debugging of errors in configuration settings of complex applications. Configuration errors are responsible for a significant share of system downtime in production scenarios, and are usually attributed to operator mistakes.
报告人简介：
Artur Andrzejak is a computer science professor at Ruprecht-Karls-University of Heidelberg and a head of the group Parallel and Distributed Systems (since 2010). He has received a PhD degree in computer science from ETH Zurich in 2000 and a habilitation degree from FU Berlin in 2009. He was a postdoctoral researcher at the HP Labs Palo Alto from 2001 to 2002 and a researcher at ZIB Berlin from 2003 to 2009. He was leading the CoreGRID Institute on System Architecture (2004 to 2006) and acted as a Deputy Head of Data Mining Department at I2R Singapore in 2010. Artur Andrzejak has published over 50 papers in international conferences and journals and received multiple best paper awards. His research topics cover scalable data analysis (in particular end-user programming), and debugging/testing of complex software systems. Driven by practical applicability of scientific results, his group is conducting projects in collaboration with industry and industrial research centers, including I2R (Singapore), SAP AG (Germany), NEC Labs (Japan), and McKinsey & Company (Germany).
软件学院 老人福祉实验室
