A. T. Acree, On Mutation, 1980.

R. Agrawal, T. Imielinski, and A. Swami, Mining association rules between sets of items in large databases, Proc. 1993 ACM-SIGMOD int. conf. management of data (SIGMOD93), pp.207-216, 1993.

K. M. Borgwardt and H. P. Kriegel, Shortest-Path Kernels on Graphs, Fifth IEEE International Conference on Data Mining (ICDM'05), pp.74-81, 2005.
DOI : 10.1109/ICDM.2005.132

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.411.7965

H. Bunke and K. Riesen, Improving vector space embedding of graphs through feature selection algorithms, Pattern Recognition, vol.44, issue.9, pp.1928-1940, 2011.
DOI : 10.1016/j.patcog.2010.05.016

H. Bunke and K. Riesen, Recent advances in graph-based pattern recognition with applications in document analysis, Pattern Recognition, vol.44, issue.5, pp.1057-1067, 2011.
DOI : 10.1016/j.patcog.2010.11.015

T. A. Budd, Mutation Analysis of Program Test Data, 1980.

M. Chein, M. L. Mugnier, and G. Simonet, Nested Graphs: A Graph-based Knowledge Representation Model with FOL Semantics, Proceedings of the 6th International Conference " Principles of Knowledge Representation and Reasoning " (KR'98), pp.524-534, 1998.

C. Ji, Z. Chen, B. Xu, and Z. Zhao, A Novel Method of Mutation Clustering Based on Domain Analysis, Proceedings of the 21st International Conference on Software Engineering and Knowledge Engineering (SEKE09): Knowledge Systems Institute Graduate School, pp.1-3, 2009.

P. Chevalley, Applying mutation analysis for object-oriented programs using a reflective approach, Proceedings Eighth Asia-Pacific Software Engineering Conference, p.267, 2001.
DOI : 10.1109/APSEC.2001.991487

P. Chevalley and P. Thevenod-fosse, A mutation analysis tool for Java programs, International Journal on Software Tools for Technology Transfer, vol.7, issue.1, p.90103, 2002.
DOI : 10.1007/s10009-002-0099-9

M. Collins and N. Duffy, New ranking algorithms for parsing and tagging, Proceedings of the 40th Annual Meeting on Association for Computational Linguistics , ACL '02, 2002.
DOI : 10.3115/1073083.1073128

R. A. Demillo, R. J. Lipton, and F. G. Sayward, Hints on Test Data Selection: Help for the Practicing Programmer, Computer, vol.11, issue.4, p.3441, 1978.
DOI : 10.1109/C-M.1978.218136

T. Gartner, A survey of kernels for structured data, ACM SIGKDD Explorations Newsletter, vol.5, issue.1, p.4958, 2003.
DOI : 10.1145/959242.959248

T. Gartner, Kernels for structured data, Series in Machine Perception and Artificial Intelligence, 2003.

J. Han, J. Pei, Y. Yin, and R. Mao, Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach, Data Mining and Knowledge Discovery, vol.8, issue.1, pp.53-87, 2004.
DOI : 10.1023/B:DAMI.0000005258.31418.83

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.3.2424

D. Haussler, Convolutional kernels on discrete structures, 1999.

S. Hussain, Mutation Clustering, 2008.

A. Inokuchi, T. Washio, and H. Motoda, An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data, Principles of Data Mining and Knowledge Discovery, 4th European Conference, pp.87-92, 2000.

Y. Jia and M. Harman, An Analysis and Survey of the Development of Mutation Testing, IEEE Transactions on Software Engineering, vol.37, issue.5, pp.649-678, 2011.
DOI : 10.1109/TSE.2010.62

H. Kashima and K. Tsuda, Akihiro Inokuchi, Marginalized Kernels Between Labeled Graphs, ICML, vol.2003, pp.321-328

S. Kim, J. A. Clark, and J. A. Mcdermid, Assessing Test Set Adequacy for Object Oriented Programs Using Class Mutation, Proceedings of the 3rd Symposium on Software Technology (SoST99), pp.8-9, 1999.

S. Kim, J. A. Clark, and J. A. Mcdermid, The Rigorous Generation of Java Mutation Operators Using HAZOP, Proceedings of the 12th International Cofference Software and Systems Engineering and their Applications (ICSSEA 99), 1999.

S. Kim, J. A. Clark, and J. A. Mcdermid, Class Mutation: Mutation Testing for Object-oriented Programs, Proceedings of the Net.ObjectDays Conference on Object-Oriented Software Systems, 2000.

S. Kim, J. A. Clark, and J. A. Mcdermid, Investigating the effectiveness of objectoriented testing strategies using the mutation method published in book form, as Mutation Testing for the New Century, Proceedings of the 1st Workshop on Mutation Analysis (MUTATION00), pp.6-7, 2001.

K. N. King and A. J. Offutt, A Fortran Language System for Mutation-Based Software Testing, Software:Practice and Experience, p.685718, 1991.

M. Liwicki, H. Bunke, J. A. Pittman, and S. Knerr, Combining diverse systems for handwritten text line recognition, Machine Vision and Applications, vol.23, issue.4, pp.39-51, 2011.
DOI : 10.1007/s00138-009-0208-9

M. Liwicki, A. Schlapbach, and H. Bunke, Automatic gender detection using on-line and off-line information, Pattern Analysis and Applications, vol.18, issue.3, pp.87-92, 2011.
DOI : 10.1007/s10044-010-0178-6

A. Preller, M. L. , and M. Chein, Logic for Nested Graphs, Computational Intelligence, vol.14, issue.3, pp.335-357, 1998.
DOI : 10.1111/0824-7935.00066

Y. Ma, J. Offutt, and Y. R. Kwon, MuJava, Proceeding of the 28th international conference on Software engineering , ICSE '06, pp.827-830, 2006.
DOI : 10.1145/1134285.1134425

A. P. Mathur, Performance, effectiveness, and reliability issues in software testing, [1991] Proceedings The Fifteenth Annual International Computer Software & Applications Conference, pp.11-13, 1991.
DOI : 10.1109/CMPSAC.1991.170248

A. P. Mathur and W. E. Wong, An empirical comparison of data flow and mutation-based test adequacy criteria, Software Testing, Verification and Reliability, vol.16, issue.1, 1993.
DOI : 10.1002/stvr.4370040104

A. J. Offutt, G. Rothermel, and C. Zapf, An experimental evaluation of selective mutation, Proceedings of 1993 15th International Conference on Software Engineering, p.100107, 1993.
DOI : 10.1109/ICSE.1993.346062

J. Richiardi, D. Van-de-ville, K. Riesen, and H. Bunke, Vector Space Embedding of Undirected Graphs with Fixed-cardinality Vertex Sequences for Classification, 2010 20th International Conference on Pattern Recognition, pp.902-905
DOI : 10.1109/ICPR.2010.227

K. Riesen and H. Bunke, Cluster Ensembles Based on Vector Space Embeddings of Graphs, MCS, vol.66, issue.336, pp.211-221
DOI : 10.1002/0471660264

K. Riesen and H. Bunke, Dissimilarity Based Vector Space Embedding of Graphs Using Prototype Reduction Schemes, MLDM, vol.21, issue.6, pp.617-631
DOI : 10.1142/5832

K. Riesen and H. Bunke, Reducing the dimensionality of dissimilarity space embedding graph kernels, Engineering Applications of Artificial Intelligence, vol.22, issue.1, pp.48-56, 2009.
DOI : 10.1016/j.engappai.2008.04.006

G. Rozenberg, Handbook of Graph Grammars and Computing by Graph, Transformations, vol.1, 1997.

G. Rozenberg, Handbook of Graph Grammars and Computing by Graph, Applications, Languages and Tools, 1999.

J. Shawe-taylor and N. Cristianini, Kernel Methods for Pattern Analysis, pp.1-462, 2004.
DOI : 10.1017/CBO9780511809682

B. Schlkopf and A. J. , Smola: A Short Introduction to Learning with Kernels, Machine Learning Summer School, pp.41-64, 2002.

B. Schlkopf and A. J. , Smola: Learning with kernels, 2002.

B. Strug, Using Kernels on Hierarchical Graphs in Automatic Classification of Designs, LNCS, vol.6658, pp.335-344, 2011.
DOI : 10.1007/978-3-642-20844-7_34

K. Tsuda, T. Kin, and K. Asai, Marginalized kernels for biological sequences, Bioinformatics, vol.18, issue.Suppl 1, pp.268-275
DOI : 10.1093/bioinformatics/18.suppl_1.S268

URL : http://bioinformatics.oxfordjournals.org/cgi/content/short/18/suppl_1/S268

S. V. Vishwanathan, K. M. Borgwardt, and N. Nicol, Schraudolph: Fast Computation of Graph Kernels, NIPS, vol.2006, pp.1449-1456

W. E. Wong, On Mutation and Data Flow, 1993.

X. Yan, P. S. Yu, and J. Han, Substructure similarity search in graph databases, Proceedings of the 2005 ACM SIGMOD international conference on Management of data , SIGMOD '05
DOI : 10.1145/1066157.1066244

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.133.5680

X. Yan, P. S. Yu, and J. Han, Graph indexing, Proceedings of the 2004 ACM SIGMOD international conference on Management of data , SIGMOD '04, 2004.
DOI : 10.1145/1007568.1007607