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...ch techniques have been used, e.g., to create models of environment constraints with respect to which a component should be verified, for regression testing to create a specification and a test suite =-=[6, 7]-=-, to perform model checking without access to code or to formal models [8, 9], for program analysis [10], and for formal specification and verification [11]. For finite-state reactive systems, the reg...

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...g e#ort. All this could be dramatically improved if it were possible to generate and then maintain appropriate reference models steering the testing e#ort and helping to evaluate the test results. In =-=[6]-=- it has been proposed to generate the models from previous system versions, by using learning techniques, and incorporating further knowledge in various ways. We call this general approach moderated r...

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... class field. Ammons et al. [1] develop a tool to infer likely protocol specifications from C method call traces by using an off-the-shelf probabilistic finite state automaton learner. Hagerer et al. =-=[19]-=- present the regular extrapolation technique to discover protocol specifications from execution traces of reactive systems. Henkel and Diwan [21] develop a tool to derive a large number of terms for a...

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...omata learning) techniques [4–10]). This class of techniques has recently started to get attention in the testing and verification community, e.g., for regression testing of telecommunication systems =-=[11, 12]-=-, and for combining conformance testing and model checking [13, 14]. They describe how to construct a finite-state machine (or a regular language) from the answers to a finite sequence of membership q...

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...ly outperforms the classic L∗ algorithm, even when exploiting optimal data abstraction and symmetry reduction. 1 Introduction The model-based approach to development, verification, and testing of software systems (e.g., [7, 5, 11]) is a key path towards efficient development of reliable software systems. However, its application is hampered by the current lack of adequate specifications for most actual systems. The use of component libraries with very partial specifications, and the problem of maintaining specifications of evolving systems aggravate the situation. Automata learning techniques [9] have been proposed to overcome this, by allowing to construct and later update behavioral models automatically. This has been illustrated in a number of case studies like, e.g., the concrete setting of Computer Telephony Integrated (CTI) systems [9], and in protocol specification [18], analysis [22], and testing [24]. Black-box techniques for learning component models broadly fall into two classes. One class generates finite-state models of control skeletons, modeling the sequences of interactions of a component [9, 12, 2, 22], or automata learning techniques (e.g., [3, 19]). Another class ge...

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...ay be replaced, and UnitsTesting and Integration Testing are iterated.s7. The process terminates after domain expertssapprove the results.sThis incremental approach is similar to the onespresented in =-=[3]-=-. In this paper, we concentrate on thesuse of such an approach for component integration, andsdevelop the necessary extensions to the learningsalgorithm.sThe rest of the paper is organized as follows....

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... one can send sequences of actions to the system and -- the system signals whether it could execute the sequence. This approach has been used in projects for test sequence generation by Ste#en et al. =-=[HHNS02]-=-, and by Peled et al. for developing techniques for conformance testing of finite automata [GPY02]. The number of reported e#orts to use Angluin 's algorithm (or some related algorithm) for generating...