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Improving the performance of OCL constraint solving with novel heuristics for logical operations: a search-based approach

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Abstract

A common practice to specify constraints on the Unified Modeling Language (UML) models is using the Object Constraint Language (OCL). Such constraints serve various purposes, ranging from simply providing precise meaning to the models to supporting complex verification and validation activities. In many applications, these constraints have to be solved to obtain values satisfying the constraints, for example, in the case of model-based testing (MBT) to generate test data for the purpose of generating executable test cases. In our previous work, we proposed novel heuristics for various OCL constructs to efficiently solve them using search algorithms. These heuristics are enhanced in this paper to further improve the performance of OCL constraint solving. We performed an empirical evaluation comprising of three case studies using three search algorithms: Alternating Variable Method (AVM), (1 + 1) Evolutionary Algorithm (EA), and a Genetic Algorithm (GA) and in addition Random Search (RS) was used as a comparison baseline. In the first case study, we evaluated each heuristics using carefully designed artificial problems. In the second case study, we evaluated the heuristics on various constraints of Cisco’s Video Conferencing Systems defined to support MBT. Finally, the third case study is about EU-Rent Car Rental specification and is obtained from the literature. The results of the empirical evaluation showed that (1 + 1) EA and AVM with the improved heuristics significantly outperform the rest of the algorithms.

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Acknowledgments

This paper is supported by the National Research Fund, Luxembourg (FNR/P10/03). Muhammad Zohaib Iqbal and Maham Khalid were also supported by National ICT R&D Fund, Pakistan (ICTRDF/MBTToolset/2013).

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Authors and Affiliations

  1. Simula Research Laboratory, Fornebu, Norway

    Shaukat Ali

  2. Quest Lab, National University of Computer & Emerging Sciences, Islamabad, Pakistan

    Muhammad Zohaib Iqbal & Maham Khalid

  3. SnT Centre, University of Luxembourg, Walferdange, Luxembourg

    Muhammad Zohaib Iqbal & Andrea Arcuri

  4. Scienta, Oslo, Norway

    Andrea Arcuri

Authors
  1. Shaukat Ali
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  2. Muhammad Zohaib Iqbal
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  3. Maham Khalid
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  4. Andrea Arcuri
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Corresponding author

Correspondence to Shaukat Ali.

Additional information

Communicated by: Marouane Kessentini and Günther Ruhe

Appendix A: artificial problems

Appendix A: artificial problems

Table 10 Artificial problems used in the experiment
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Table 11 Time measurements for each algorithm for IM
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Table 12 Time measurements for each algorithm for NIM
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Ali, S., Iqbal, M.Z., Khalid, M. et al. Improving the performance of OCL constraint solving with novel heuristics for logical operations: a search-based approach. Empir Software Eng 21, 2459–2502 (2016). https://doi.org/10.1007/s10664-015-9392-6

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