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Seminar by Dr. Audris Mockus (University of Tennessee)

July 15, 2015
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Speaker: Dr. Audris Mockus
                University of Tennessee

Title: Toward Evidence Engineering

Date: Wednesday, July 15th, 2015

Time: 2:00-3:00 PM

Place: EV2.184

ABSTRACT

The focus of software engineering over the last half century has shifted from squeezing the most from every (then very expensive) compute cycle, to improving developer productivity, and, as of late, to engineering user behaviors.  The software systems now collect massive amounts of operational data related to users' individual and social activities and rely on it to create experiences that achieve desired outcomes, e.g., increase sales revenue or the quality of software (if the user is a software developer). Novel approaches to design, implement, test, and operate such systems are needed to transform this vast operational data into accurate and actionable information (evidence) either automatically of with social support. With operation and measurement becoming an integral part of software development, the separation between the software tools and end-user software are increasingly blurred. The software construction, development, build, delivery, and operation are both tools to build software systems and, at the same time, an integral part of these systems. The core software engineering questions need, therefore, to address the engineering principles needed for these systems not simply to store or push this massive data around, but also to reliably produce compelling evidence for users and developers alike: to refocus on evidence engineering.

BIO

Audris Mockus received the BS and MS degrees in applied mathematics from the Moscow Institute of Physics and Technology in 1988, the MS degree in 1991 and the PhD degree in statistics from Carnegie Mellon University in 1994. He studies software developers' culture and behavior through the recovery, documentation, and analysis of digital remains. These digital traces reflect projections of collective and individual activity. He reconstructs the reality from these projections by designing data mining methods to summarize and augment these digital traces, interactive visualization techniques to inspect, present, and control the behavior of teams and individuals, and statistical models and optimization techniques to understand the nature of individual and collective behavior. He is Ericsson-Harlan D Mills Chair Professor in the Department of Electrical Engineering and Computer Science of the
University of Tennessee. He also continues to work part-time at Avaya Labs Research. Previously he worked in the Software Production Research Department at Bell Labs. He is a member of the IEEE and ACM.




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