Email: sindhu[at]nada dot kth dot se or you can use
sindhu[at]csc dot kth dot se

**Past
Activity**

The current focus of my research is on optimizing the tool which we have developed on the basis of our earlier research for automatic test case generation (ATCG) for testing of safety critical embedded software systems. The tool was developed on the idea of using incremental learning of system under test (SUT), which can be modeled as Moore Automata initially. To begin with an off the shelf algorithm available in literature was used to materialize this idea. But initial research led us to the conclusion that this algorithm was too limited therefore a new algorithm in which SUT can be modeled as a deterministic Kripke structure with multi bit output was devised and implemented with two variants (with and without prefix closure). Promising results on this learning frame work led us to integrate the *Incremental Kripke Learner* with the NuSMV model checker which provides counter examples when a specific requirment/specification formula is violated, this counterexample can be used as an interesting test case for SUT. An initial version of the (ATCG) tool is now ready and has been put to test on a few reactive systems like the cruise controller and an elevator system for multiple floors. The results indicate the usefulness of incremental learning over complete learning for ATCG by detecting the bug/error much earlier than the systems which try to learn the system completely. In the next stage we want to optimize this tool and scale it to systems with even larger state space.

Algorithms and Tools for Learning-based Testing of Reactive Systems, Doctoral Thesis, School of Computer Science and Communication, Royal Institute of Technology, Stockholm, Sweden, 2013, ISBN 978-91-7501-674-0. : link

LBTest: A Learning-based Testing Tool for Reactive Systems. [Karl Mienke, Muddassar Sindhu]

*In proc. IEEE ICST 2013 Tools Track.*Testing Abstract Behavioural Specifications [P. Wong, R. Bubel, F. De Boer, M. Gomez-Zamalloa, S. De Gouw, R. HĂ¤hnle, Karl Mienke, Muddassar Sindhu]

*Submitted for publication, 2012.*An n log n Algorithm for Deterministic Kripke Structure Minimization [Karl Mienke, Muddassar Sindhu] arxiv.org download

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. : link bibtex

Learning-Based Software Testing: a Tutorial [Karl Mienke, Fei Niu, Muddassar Sindhu]

*In Proc. Int. ISoLA workshop on Machine Learning, CCIS, Springer Verlag, 2011.*IDS: An Incremental Learning Algorithm for Finite Automata.[Karl Mienke, Muddassar Sindhu]. arxiv.org download

Incremental Learning-Based Testing for Reactive Systems.[Karl Mienke, Muddassar Sindhu]

*pp 134-151 in: Proc, TAP 2011, LNCS 6706, Springer Verlag, 2011.*bibtex

Correctness and Performance of IID Learning Algorithm for Finite Automata.[Karl Mienke, Muddassar Sindhu]

*Technical Report, also accepted for poster presentation in 3rd ACML 2011, Taiwan.*bibtex

I worked as a Lecturer in Computer Science Department of Quaid i Azam University Islamabad, Pakistan prior to joining CSC as a PhD Student. I taught CS-301 Computer Sytems , CS-353 Database Design and CS-482 Web Engineering there along with superivising final projects of MSc students relevant to Databases, Web, DLD and Software Engineering.

**Education**

Licentiate in Engineering from Royal Institute of Technology, Stockholm, Sweden.

MSc in Computer Science from Punjab University, Lahore, Pakistan.

In Semantic and Logic Interest Group at CSC, KTH.

About Angluin's ID Algorithm (April 29, 2009)

About IID Algorithm (May 13, 2009)

In HATS Project Meeting at CWI, Amsterdam, Netherlands.

Model Mining at KTH (May 12, 2010) pdf

In proceedings of 5th International Conference on Tests and Proofs TAP 2011 at ETH, Zurich, Switzerland.

Incremental Learning-based Testing for Reactive Systems. pdf