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Model-based testing (part 1)

Model-based testing (part 1)

Rostislav Yavorsky, vice principal of Science and Technologies, Surgut State University

Video: https://youtu.be/b9KXyBLmt3w

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December 17, 2019


  1. Model Based Testing - 1 Rostislav Yavorskiy, PhD Head of

    Research, Exactpro Systems Kostroma, 17 December, 2019
  2. Plan 1. Formal methods 2. Types of models 3. Advantages

    and issues of model based testing 4. Examples 2
  3. Formal vs Informal methods Formal methods are a particular kind

    of mathematically based techniques for • specification • development • verification of software and hardware systems. 3
  4. Formal vs Informal methods Organizational (informal) methods • Waterfall and

    Feature-Driven Development • Agile, Scrum, Extreme Programming • Integrated Testing Process • Project Planning and Tracking • Visible Defect Tracking and Reporting 4
  5. Formal models are used to represent the behavior of a

    system under test (SUT): • Functional specification (input/output) • Time series (system dynamics/history) • State-transition system • Process algebra 5 Mathematical methods
  6. Model based testing 6 A model describing a SUT is

    usually an abstract, partial presentation of the SUT's desired behavior. Often the model is a finite state transition system. Test cases derived from such a model are functional tests on the same level of abstraction as the model.
  7. Model based testing 7 ① ② ③ ④

  8. • High level of Automation. Tests are automatically generated from

    a formal model with different algorithms and heuristics • Improved Test Coverage. Model states/transitions coverage • Change management. Small changes in the documentation are translated into new test scripts in few seconds Advantages of model based testing 8
  9. • Time. High initial start up cost with low measurable

    returns • Complexity. Require a high level of mathematical expertise and the analytical skills. A solution to this would be to develop tools and models that allow for these techniques to be implemented but hide the underlying mathematics • Flexibility. Not clear how to use formal specifications with "agile" development • Limited scope. MBT does not capture properties of interest for all stakeholders and not good for of specifying user interfaces. Issues of model based testing 9
  10. Example 10

  11. Example 11

  12. Example 12

  13. Finite Automata DFA is described by a tuple: (Q, Σ;

    q 0 , F). Q - a finite set of states Σ - a finite input alphabet (transitions) q 0 - the starting state F - the set of accepting (final) states 13
  14. Example 14