Argus: Automated Software Bug Discovery and Assessment
Navy SBIR FY2018.1


Sol No.: Navy SBIR FY2018.1
Topic No.: N181-068
Topic Title: Argus: Automated Software Bug Discovery and Assessment
Proposal No.: N181-068-0452
Firm: ATC - NY
P.O. Box 422
Trumansburg, New York 14886
Contact: Matthew Donovan
Phone: (607) 257-1975
Web Site: http://www.atcorp.com
Abstract: Software bugs are a significant risk to mission success and human safety. Software testing and analysis, which is used to combat bugs, is difficult, and thus time-consuming and expensive. It is particularly difficult to find latent bugsƒ?"bugs that do not have obvious, observable effects on the system. This results in undiscovered and unfixed bugs in the system. New approaches to automated software testing offer the opportunity to catch bugs with less time and cost than manual approaches. To achieve this, ATC-NY will develop Argus, an automated software testing tool that finds latent errors in a program by analyzing large amounts of testing output. Argus uses big-data machine learning techniques to autonomously analyze records of program behavior to find and prioritize anomalous behavior that may indicate an undiscovered software bug.
Benefits: Argus provides an innovative new technique for automated software bug detection. This technique operates in parallel with existing software testing approaches and requires minimal additional time, but promises to discover bugs that are not found by the existing testing. In particular, Argus promises to discover latent bugs that, because they do not have observable effects on the system, are very hard to detect with current testing approaches. The result is that a larger number of software bugs will be discovered, and thus fixed, prior to software deployment. This will improve the reliability of the software and reduce the risk to mission success and human safety.

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