NDLI: Application of genetic algorithm for flight system verification and validation

Content Provider	IEEE Xplore Digital Library
Author	Sacco, G.F. Barltrop, K.J. Cin-Young Lee Horvath, G.A. Terrile, R.J. Seungwon Lee
Copyright Year	2009
Description	Author affiliation: Jet Propulsion Laboratory and California Institute of Technology, 4800 Oak Grove Drive, Pasadena, 91109, USA (Sacco, G.F.; Barltrop, K.J.; Cin-Young Lee; Horvath, G.A.; Terrile, R.J.; Seungwon Lee)
Abstract	Most complex systems nowadays heavily rely on software, and spacecraft and satellite systems are no exception. Moreover as systems capabilities increase, the corresponding software required to integrate and address system tasks becomes more complex. Hence, in order to guarantee a system's success, testing of the software becomes imperative. Traditionally exhaustive testing of all possible behaviors was conducted. However, given the increased complexity and number of interacting behaviors of current systems, the time required for such thorough testing is prohibitive. As a result many have adopted random testing techniques to achieve sufficient coverage of the test space within a reasonable amount of time. In this paper we propose the use of genetic algorithms (GA) to greatly reduce the number of tests performed, while still maintaining the same level of confidence as current random testing approaches. We present a GA specifically tailored for the systems testing domain. In order to validate our algorithm we used the results from the Dawn test campaign. Preliminary results seem very encouraging, showing that our approach, when searching the worst test cases, outperforms random search , limiting the search to a mere 6 % of the full search domain.
Starting Page	1
Ending Page	7
File Size	263773
Page Count	7
File Format	PDF
ISBN	9781424426218
ISSN	1095323X
DOI	10.1109/AERO.2009.4839631
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genetic algorithms System testing Satellites Genetic mutations Encoding Propulsion Laboratories Space technology Space vehicles Software testing
Content Type	Text
Resource Type	Article
Subject	Aerospace Engineering Space and Planetary Science

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