%0 Conference Proceedings
%T Multiple Mutation Testing from Finite State Machines with Symbolic Inputs
%+ Centre de Recherche Informatique de Montréal = Computer Research Institute of Montréal (CRIM)
%+ General Motors [Warren]
%A Nguena Timo, Omer
%A Petrenko, Alexandre
%A Ramesh, S.
%Z Part 2: Test Derivation Methods
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 29th IFIP International Conference on Testing Software and Systems (ICTSS)
%C St. Petersburg, Russia
%Y Nina Yevtushenko
%Y Ana Rosa Cavalli
%Y Hüsnü Yenigün
%I Springer International Publishing
%3 Testing Software and Systems
%V LNCS-10533
%P 108-125
%8 2017-10-09
%D 2017
%R 10.1007/978-3-319-67549-7_7
%K Extended FSM
%K Symbolic inputs
%K Conformance testing
%K Mutation testing fault modelling
%K Fault model-based test generation
%K Constraint solving
%Z Computer Science [cs]
%Z Computer Science [cs]/Networking and Internet Architecture [cs.NI]Conference papers
%X Recently, we proposed a mutation-testing approach from a classical finite state machine (FSM) for detecting nonconforming mutants in a given fault domain specified with a so-called mutation machine. In this paper, we lift this approach to a particular type of extended finite state machines called symbolic input finite state machine (SIFSM), where transitions are labeled with symbolic inputs, which are predicates on input variables possibly having infinite domains. We define a well-formed mutation SIFSM for describing various types of faults. Given a mutation SIFSM, we develop a method for evaluating the adequacy of a test suite and a method for generating tests detecting all nonconforming mutants. Experimental results with the prototype tool we have developed indicate that the approach is applicable to industrial-like systems.
%G English
%Z TC 6
%Z WG 6.1
%2 https://inria.hal.science/hal-01678962/document
%2 https://inria.hal.science/hal-01678962/file/449632_1_En_7_Chapter.pdf
%L hal-01678962
%U https://inria.hal.science/hal-01678962
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC6
%~ IFIP-WG6-1
%~ IFIP-ICTSS
%~ IFIP-LNCS-10533