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Search-based performance evaluation with MARMOT

: Mayer, N.; Groß, H.-G.; Bunse, C.

Bruel, J.-M.:
QoS in CBSE 2003. Proceedings of the 1st International Workshop on Quality of Service in Component-Based Software Engineering : Workshop at Ada-Europe 2003
Toulouse: Cépaduès-Editions, 2003
ISBN: 2-85428-617-0
S.133-148 : Ill., Lit.
International Workshop on Quality of Service in Component-Based Software Engineering <1, 2003, Toulouse>
International Conference on Reliable Software Technologies, Ada-Europe <8, 2003, Toulouse>
Fraunhofer IESE ()
built-in testing; component-based development; dynamic execution-time analysis; methodology; real-time system

Performance analysis and evaluation are essential constructive and validative activities during embedded system development. These activities can be performed either statically, or dynamically through search-based techniques such as random or evolutionary testing. Search or optimisation algorithms have already been successfully used for a number of software engineering activities such as execution-time analysis and validation under the traditional procedural development paradigm. This paper describes how Marmot, a new method for real-time embedded system development and testing, applies search-based analysis/testing techniques under the more recent object-oriented and component-based software development paradigms. Here, their application is more difficult compared with the traditional procedural development approaches because object and component-based architectures are inherently encapsulated, they often represent state machines, and they are fundamentally based upon software reuse technology rather than "one-of'' developments. Marmot proposes a solution that makes search techniques applicable in object-oriented and component-based embedded real-time system development.
This solution is based on built testing artifacts and on the adaptation of search-based testing strategies to object and component technologies. We demonstrate the applicability of the Marmot performance evaluation strategy in a development project for an autonomous vehicle.