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  <div class="vevent h-event"> <h1 class="summary p-name">(Galois Tech Talk) New Directions in Random Testing: from Mars Rovers to JavaScript Engines</h1> <div class='date'><time class="dtstart dt-start" title="2013-09-12T10:30:00" datetime="2013-09-12T10:30:00">Thursday, September 12, 2013 from 10:30</time>–<time class="dtend dt-end" title="2013-09-12T11:30:00" datetime="2013-09-12T11:30:00">11:30am</time></div> <div class="location vcard p-location h-card"> <a class="url" href='http://calagator.org/venues/202390439'><span class='fn org p-name'>Galois, Inc</span></a> <div class="adr p-adr h-adr"> <div class="street-address p-street-address">421 SW 6th Ave. Suite 300</div> <span class="locality p-locality">Portland</span> , <span class="region p-region">OR</span> <span class="postal-code p-postal-code">97204</span> <div class="country-name p-country-name">US</div> (<a href='https://maps.google.com/maps?q=421%20SW%206th%20Ave.%20Suite%20300,%20Portland%20OR%2097204%20US'>map</a>) </div> </div> <div class="description p-description"> <p>Presented by Alex Groce.</p> <p>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.</p> </div> <h3>Links</h3> <ul> <li><a class="url u-url" href="http://corp.galois.com/blog/2013/9/9/tech-talk-new-directions-in-random-testing-from-mars-rovers.html">Website</a></li> </ul> </div>