Conference Program

                             Conference Agenda (TBD)

Wednesday, Oct. 19, 2016

9:00 – 18:00

Conference Registration


9:00 – 18:00

Workshops:

CRESCI-PHM Tutorial, organized by   Prof. Rui Kang, Beihang University

IEEE Reliability Tutorial, organized   by Prof. Eric Wong, University of Texas, Dallas

Thursday, Oct. 20, 2016

9:00 – 18:00

Conference Registration

9:00 – 12:00

Opening Ceremony

Keynote Speeches

12:00 – 13:30

Lunch

13:30 – 18:10

Keynote Speeches

Parallel Technical Sessions


19:00 – 21:00

Conference Banquet

Friday, Oct. 21, 2016

9:00 – 18:00

Conference Registration

9:00 – 18:00

Workshop:

CRESCI-PHM Tutorial, organized by   Prof. Rui Kang, Beihang University

8:30 – 12:10

Parallel Technical Sessions

12:10 – 13:30

Lunch

13:30 –18:10

Parallel Technical Sessions


IEEE Reliability Tutorial


Combinatorial Testing and Its Applications

10/19, Wednesday, 8:30 − 9:30 am

W. Eric Wong

Professor & Director
Advanced Research Center for Software Testing & Quality Assurance
Department of Computer Science
University of Texas at Dallas

Abstract

Studies have shown that combinatorial testing can help programs detect hard-to-find software bugs that may not be revealed by test cases generated using other testing techniques. The first part of this talk focuses on traditional black-box requirements-based combinatorial testing. In particular, I will discuss results and lessons learned from two real-life industry applications: a control panel of a rail-road system and a Linux system. The second part extends the concept of combinatorial testing to a white-box structure-based setting. I will present an advanced coverage criterion, Combinatorial Decision Coverage, in conjunction with symbolic execution to achieve high coverage cost-effectively without suffering from potential space exploration. Finally, I will explain how combinatorial testing can be applied to a graph-based methodology for testing IoT (Internet of Things).

Bio

W. Eric Wong received his M.S. and Ph.D. in Computer Science from Purdue University, West Lafayette, Indiana, USA. He is a Full Professor, the Director of International Outreach, and the Founding Director of Advanced Research Center for Software Testing and Quality Assurance (http://paris.utdallas.edu/stqa) in Computer Science at the University of Texas at Dallas (UTD). He also has an appointment as a guest researcher at the National Institute of Standards and Technology, an agency of the U.S. Department of Commerce. Prior to joining UTD, he was with Telcordia Technologies (formerly Bellcore) as a senior research scientist and the project manager in charge of Dependable Telecom Software Development.

Dr. Wong is the recipient of the 2014 IEEE Reliability Society Engineer of the Year. He is also the Edit-in-Chief of the IEEE Transactions on Reliability. His research focuses on helping practitioners improve software quality while reducing production cost. In particular, he is working on software testing, program debugging, risk analysis, safety, and reliability. Dr. Wong has published more than 180 papers and edited 2 books.

Dr. Wong is also the Founding Steering Committee Chair of the IEEE International Conference on Software Security and Reliability (SERE) and the IEEE International Workshop on Program Debugging. In 2015, the SERE conference and the QSIC conference (International Conference on Quality Software) merged into one large conference, QRS, with Q representing Quality, R for Reliability, and S for Security. Dr. Wong continues to be the Steering Committee Chair of this new conference (http://paris.utdallas.edu/qrs).

Software/System Reliability

10/19, Wednesday, 9:30 m − 12:30 pm

Pete Rotella

Cisco Systems, Inc.

Abstract

This tutorial begins by describing the use of three types of software metrics:  In-process, customer experience, and customer sentiment. Each metric type characterizes an important part of the software lifecycle, and the sequence circumscribes much of what concerns us in software engineering and reliability. For example, an important use of in-process metrics is to construct and use mathematical models that predict software reliability and other key quality attributes. The tutorial session will describe the process of collecting, scrubbing, and transforming in-process data to build models and simulations that predict customer experience and sentiment.

Models are needed to enable software practitioners to identify deficient (and superior) development and test practices.  Even in environments having standard practices and metrics, software  teams often vary substantially in practice adoption and effectiveness.  Therefore, one challenge is to develop and implement generalized models that adequately characterize the health of individual practices (such as code review, unit test, function testing), to enable process and quality assurance groups in assisting engineering teams in repairing broken practices or replacing them with more effective and efficient ones. 

In this tutorial session, we will describe our experience with model building and implementation, and attempt to describe the domains within which certain types of models perform well. We will also address how to balance model generalizability and specificity in order to integrate the findings into the everyday engineering workflow.

Also, we will describe how to in practice use the models and other analyses we create – how to implement the changes and then track progress over time and over subsequent software releases and new products. Developing analyses and models is only the first step in an often arduous journey to full acceptance and use.

Bio

Pete Rotella has a degree in Physics from Duke University in North Carolina. For the past 15 years at the corporate level in Cisco Systems, he has been investigating ways to improve software quality, including work in software reliability and availability, security, and customer perception. He also leads the corporate implementation of a number of improved development and test practices. Much of this work involves analytics, including mathematical modeling, statistics, metrics creation and implementation, and the trending and goaling of corporate, business unit, product, and release metrics. Mr. Rotella at many software engineering conferences including ISSRE, ICSE, MSR, and FSE.

Mechanical Reliability

10/19, Wednesday, 1:30 pm − 5:30 pm

​Richard Doyle

Abstract

Mechanical Reliability analysis is a technique for predicting the expected life and reliability of a mechanical system based on the reliability of the individual mechanical components. Mechanical designs are often one of a kind; therefore historical data from “similar” equipment is not always readily available for predicting performance reliability of the new equipment or its new application. The intent of this tutorial is to guide one through the basic steps of performing a mechanical reliability analysis. However, it is left up to the reliability analyst to select the most applicable techniques to use and which probability function best fits the mechanical equipment that is under evaluation. These techniques may be used to determine reliability improvements based on design changes if the design is not meeting the reliability goals. The most current mechanical reliability model selection guides will be provided. Also, small systems and Micro-mechanical reliability applications will be discussed.

Bio

Richard Doyle is a Registered Electrical and Civil Engineer in California and has a B.S. in Mechanical Engineering from Oregon State University and a M.S. in Engineering from the University of California, Irvine. Mr. Doyle has more than 30 years of experience in the theoretical analysis and design of electrical and mechanical systems, including consulting for the past 20 years in Aerospace, Commercial Electronics, and Nuclear Power Industries. He performed thermal/reliability analysis using computer simulations for different electrical systems such as Digital TV set top boxes, numerous power supplies, and Pentium, DSP, and ASIC ICs. He also taught Thermal Analysis of Electronics to graduate engineers working for the US Navy (Civil Service). He has also presented this tutorial many times at different locations. Mr. Doyle is a former president of the IEEE Reliability Society.

 

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