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Adaptation non-anticipée de comportement : application au déverminage de programmes en cours d'exécution

Abstract : Some programs must run continuously and cannot be interrupted in the event of a malfunction.This is, for example, the case of drones, satellites and some internet-of-things applications. For such applications, the challenge is to identify and fix problems while the program is still running. Moreover, in the context of object-oriented Systems, it may be necessary to observe and instrument the behavior of very specifie objects.In this thesis, we propose a method to adapt object behavior in a running program. This solution is presented as a pattern applicable to dynamically typed object-oriented languages. This pattern makes it possible to implement, in a minimal and generic way, additional debugging capabilities at the level of objects. An implementation of this pattern for a particular programming language makes it possible to dynamically instrument a program, by collecting specifie objects and adapting their behavior during run-time. We experiment this pattern in Pharo and Python implementations with dedicated debuggers for each language.These tools are evaluated on typical debugging case studies: a simulation of drones, connected applications deployed on remote cyber-physical Systems, an online discussion server and a debugging session to fix a defect in a production software.
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  • HAL Id : tel-02082447, version 1

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Steven Costiou. Adaptation non-anticipée de comportement : application au déverminage de programmes en cours d'exécution. Autre [cs.OH]. Université de Bretagne occidentale - Brest, 2018. Français. ⟨NNT : 2018BRES0069⟩. ⟨tel-02082447⟩

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