(Tech Talk) New Directions in Random Testing, From Mars Rovers to JavaScript Engines

  • Date  Time
  • Speaker
  • Location

Galois is pleased to host the following tech talk.
These talks are open to the interested public–please join us!
(There is no need to pre-register for the talk.)

This talk is on Thursday.

title: New Directions in Random Testing:
from Mars Rovers to JavaScript Engines
speaker: Alex Groce
time: Thursday, 12 September 2013, 10:30am
location: Galois Inc.
421 SW 6th Ave. Suite 300,
Portland, OR, USA
(3rd floor of the Commonwealth building)

One of the most effective ways to test complex language
implementations, file systems, and other critical systems software is random
test generation. This talk will cover a number of recent results that show
how—despite the importance of hand-tooled random test generators for complex
testing targets— there are methods that can be easily applied in almost any
setting to greatly improve the effectiveness of random testing. Surprisingly,
giving up on potentially finding any bug with every test makes it
possible to find more bugs over all. The practical problem of finding distinct
bugs in a large set of randomly generated tests, where the frequency of some
bugs may be orders of magnitude higher than other bugs, is also open to non
ad-hoc methods.

Alex Groce received his PhD in Computer Science from Carnegie Mellon University
in 2005, and B.S. degrees in Computer Science and Multidisciplinary Studies
(with a focus on English literature) from North Carolina State University in
1999. Before joining the Oregon State University faculty in 2009, he was a core
member of the Laboratory for Reliable Software at NASA’s Jet Propulsion
Laboratory, and taught classes on Software Testing at the California Institute
of Technology. His activities at JPL included a role as lead developer and
designer for test automation for the Mars Science Laboratory Curiosity
mission’s internal flight software test team, and lead roles in testing file
systems for space missions. His research interests are in software
engineering, particularly testing, model checking, code analysis, debugging,
and error explanation and fault localization.