NDLI: Swarm testing

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Swarm testing

Content Provider	ACM Digital Library
Author	Groce, Alex Zhang, Chaoqiang Regehr, John Eide, Eric Chen, Yang
Abstract	Swarm testing is a novel and inexpensive way to improve the diversity of test cases generated during random testing. Increased diversity leads to improved coverage and fault detection. In swarm testing, the usual practice of potentially including all features in every test case is abandoned. Rather, a large “swarm” of randomly generated configurations, each of which omits some features, is used, with configurations receiving equal resources. We have identified two mechanisms by which feature omission leads to better exploration of a system’s state space. First, some features actively prevent the system from executing interesting behaviors; e.g., “pop” calls may prevent a stack data structure from executing a bug in its overflow detection logic. Second, even when there is no active suppression of behaviors, test features compete for space in each test, limiting the depth to which logic driven by features can be explored. Experimental results show that swarm testing increases coverage and can improve fault detection dramatically; for example, in a week of testing it found 42% more distinct ways to crash a collection of C compilers than did the heavily hand-tuned default configuration of a random tester. .
Starting Page	78
Ending Page	88
Page Count	11
File Format	PDF
ISBN	9781450314541
DOI	10.1145/2338965.2336763
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-07-15
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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