Up to *Research, Theory group at Nada, KTH*.

# Learning-based Software Testing

Learning-based testing (LBT) is a new paradigm for black-box specification-based testing of software systems. This approach combines model-based testing methods (using model checkers) with machine learning algorithms to produce efficient search heuristics for testing.
We have designed, implemented and benchmarked a number of LBT algorithms. This research is an ongoing project involving PhD and Masters level students, as well as international collaborators and projects.

## Researcher Leader

Karl Meinke
## Post Docs

## Graduate students

Mateus de Oliveira Oliveira,

Niu Fei,

Mudassar Sindhu

## Publications

K. Meinke and M. Sindhu: *An n log n algorithm for Deterministic Kripke Structure Minimization*, submitted for journal publication, 2012.

K. Meinke and F. Niu: *An Incremental Learning Algorithm for Extended Mealy Automata*, to appear in B. Steffen and T. Margharia (eds) Proc. 2012 Int. ISoLA workshop on Machine Learning for Software Construction, LNCS, Springer Verlag, 2012.

K. Meinke, F. Niu and M. Sindhu: *Learning-Based Software Testing: a Tutorial*, invited paper to appear in B. Steffen and R. Haehnle (eds) Proc. Int. ISoLA workshop on Machine Learning for Software Construction, CCIS, Springer Verlag, 2011.

F. Niu: *Learning-based Software Testing using Symbolic Constraint Solving Methods,* Licentiate Thesis,
School of Computer Science and Communication,
Royal Institute of Technology, Stockholm, Sweden, 2011, ISBN 978-91-7501-117-2.

K. Meinke and M. Sindhu: *Correctness and Performance of an Incremental Learning Algorithm for Finite Automata*, accepted for poster presentation at Third Asian Conference on Machine Learning (ACML 2011), 13-15 November 2011, Taiwan.

K. Meinke and F. Niu, *Learning-Based Testing for Reactive Systems using Term Rewriting Technology*, pp 97-114 in
B. Wolff and F Zaidi (eds) Proc. 23rd IFIP Int. Conf. on Testing Software and Systems (ICTSS 2011), LNCS 7019, Springer Verlag, 2011.

M. Sindhu, *Incremental Learning and Testing of Reactive Systems* Licentiate Thesis,
School of Computer Science and Communication,
Royal Institute of Technology, Stockholm, Sweden, 2011, ISBN 978-91-7501-062-5.

K. Meinke and M. Sindhu, *Incremental Learning-Based testing for Reactive Systems*, pp 134-151 in: Proc. Int. Conf. on Tests and Proofs TAP 2011, LNCS 6706, Springer Verlag, 2011.

K. Meinke and F. Niu, *A Learning-Based Approach to Unit Testing of Numerical Software*, pp 221-235 in A. Petrenko et al. (eds) Proc. 22nd IFIP Int. Conf. on Testing Software and Systems (ICTSS 2010), LNCS 6435, Springer Verlag, 2010.

K. Meinke, *CGE: a Sequential Learning Algorithm for Mealy Automata*, pp 148-162 in J.M. Sempere and P. Garcia (eds), Proc. 10th Int. Colloquium on Grammatical Inference, (ICGI 2010), LNCS 6339, Springer Verlag, 2010.

Here is my original paper on
*learning-based testing*.
This paper appeared as:
K. Meinke, Automated Black-Box Testing of Functional Correctness using Function Approximation, pp 143-153 in: G. Rothermel (ed) Proc. ACM SIGSOFT Int. Symp. on Software Testing and Analysis, ISSTA 2004, Software Engineering Notes 29 (4), ACM Press, 2004.