Testing Monte Carlo Algorithmic Systems

[article]
Member Submitted
Summary:
This article covers the unique challenge in defining testing scope and expected results when testing systems with non-deterministic outputs whose accuracy improves over repeated iterations of the same inputs. A thorough understanding of the algorithms under test and excellent communication between development and testing are essential in test scenario definition and predicting anticipated outcomes. Defining tests and expected behaviors prior to the start of testing is especially crucial in these types of conditions.

About the author

Frank Erdman's picture Frank Erdman

Frank Erdman is a Software QA Engineer in Austin, Texas. His background includes testing mobile workforce management systems which use stochastic algorithms for mobile resource planning, forecasting, and scheduling. Unit test and automation tools he has worked with include JUnit, XMLUnit, CPPUnit, and Borland SilkTest. He is COMPTIA A+ and Network+ certified, and was a website consultant for Calliope, LLC, a talent agency in San Antonio. You can reach Frank via e-mail at FrankErdman2000@yahoo.com or his blog http://blogkinnetic.blogspot.com.

AgileConnection is one of the growing communities of the TechWell network.

Featuring fresh, insightful stories, TechWell.com is the place to go for what is happening in software development and delivery.  Join the conversation now!

Upcoming Events

Nov 09
Nov 09
Apr 13
May 03