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A model-driven framework for guided design space exploration

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Abstract

Design space exploration (DSE) aims at searching through various models representing different design candidates to support activities like configuration design of critical systems or automated maintenance of IT systems. In model-driven engineering, DSE is applied to find instance models that are (i) reachable from an initial model with a sequence of transformation rules and (ii) satisfy a set of structural and numerical constraints. Since exhaustive exploration of the design space is infeasible for large models, the traversal is often guided by hints, derived by system analysis, to prioritize the next states to traverse (selection criteria) and to avoid searching unpromising states (cut-off criteria). In this paper, we define an exploration approach where selection and cut-off criteria are defined using dependency analysis and algebraic abstraction of transformation rules. Additionally, we apply different state encoding techniques to identify recurring states and reduce the number of visited states. Finally, we illustrate our approach on a cloud infrastructure configuration problem and provide detailed evaluation on both synthetic and real applications. This evaluation includes (i) the comparison of several exploration techniques, (ii) performance measurements on multiple state encoding techniques and (iii) comparing two implementation architectures of our design space exploration framework.

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Notes

  1. http://www.ibm.com/software/integration/optimization/cplex-optimizer/

  2. http://roots.iai.uni-bonn.de/research/condor/

  3. For measurements we used a computer with Intel Centrino Duo 1.66 GHz, 1.5 GB memory (Java heap size), Windows 7 Professional 32 bit, Eclipse 3.6.1, Viatra2 3.2

  4. All measurements were carried out on a computer with Intel Core i5 2.3 GHz processor, 2.5 GB DDR3 memory (Java heap space), Windows 8 Professional 64 bit, Eclipse 3.8, BPMN 1.2, Viatra2 3.3

  5. All measurements were carried out on a computer with Intel Core i7 3.4 Ghz processor, 2.5 GB DDR3 memory (Java heap size), Windows 7 Professional 64 bit, Eclipse 4.2

  6. All measurements were carried out on a computer with Intel Core i5 2.5 GHz processor, 2.5 GB DDR3 memory (Java heap size), Windows 7 Professional 64 bit, Eclipse 4.2

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Acknowledgments

The authors would like to thank their students Miklós Földényi and Tamás Szabó, who helped in the evaluation of state encoding techniques and comparing the Viatra2 and EMF-based DSE framework implementations and the anonymous reviewers for their excellent comments and suggestions. This work was partially supported by the CERTIMOT (ERC_HU-09-01-2010-0003) Project, the TÁMOP (4.2.2.B-10/1–2010-0009, 4.2.2.C-11/1/KONV-2012-0001) Grants and the János Bolyai Scholarship.

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  1. Department of Measurement and Information Systems, Budapest University of Technology and Economics, Magyar tudósok krt. 2., Budapest, 1117, Hungary

    Ábel Hegedüs, Ákos Horváth & Dániel Varró

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  1. Ábel Hegedüs
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Correspondence to Ábel Hegedüs.

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Hegedüs, Á., Horváth, Á. & Varró, D. A model-driven framework for guided design space exploration. Autom Softw Eng 22, 399–436 (2015). https://doi.org/10.1007/s10515-014-0163-1

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