A Temporal Logic Based Theory of Test Coverage and Generation

Hong, Henry; Lee, Insup; Sokolsky, Oleg; Ural, Hasan

doi:10.1007/3-540-46002-0_23

Cited by 101 publications

(75 citation statements)

References 24 publications

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“…While checking correctness, the model checker reports counterexample(s) that violate a correctness criterion. While generating test inputs, the model checker generates paths that are witnesses to a testing criterion encoded as a safety property (see, e.g., [30,36]). For a reported counterexample, the model checker also reports the input heap configuration, the path condition for the primitive input fields, and the thread scheduling, which can be used to reproduce the error.…”

Section: Checking Safety Properties and Generating Test Inputsmentioning

confidence: 99%

A survey of new trends in symbolic execution for software testing and analysis

Păsăreanu

Visser

2009

Int J Softw Tools Technol Transfer

183

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Symbolic execution is a well-known program analysis technique which represents program inputs with symbolic values instead of concrete, initialized, data and executes the program by manipulating program expressions involving the symbolic values. Symbolic execution has been proposed over three decades ago but recently it has found renewed interest in the research community, due in part to the progress in decision procedures, availability of powerful computers and new algorithmic developments. We provide here a survey of some of the new research trends in symbolic execution, with particular emphasis on applications to test generation and program analysis. We first describe an approach that handles complex programming constructs such as input recursive data structures, arrays, as well as multithreading. Furthermore, we describe recent hybrid techniques that combine concrete and symbolic execution to overcome some of the inherent limitations of symbolic execution, such as handling native code or availability of decision procedures for the application domain. We follow with a discussion of techniques that can be used to limit the (possibly infinite) number of symbolic configurations that need to be analyzed for the symbolic execution of looping programs. Finally, we give a short survey of interesting new applications, such as predictive testing, invariant inference,

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Section: Checking Safety Properties and Generating Test Inputsmentioning

confidence: 99%

A survey of new trends in symbolic execution for software testing and analysis

Păsăreanu

Visser

2009

Int J Softw Tools Technol Transfer

183

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“…Test case generation with regard to coverage of data flow graphs is considered in [33,58]. A flow graph G is defined as a tuple G = (V, v s , v f , A), where V is a finite set of vertices, v s ∈ V is the start vertex, v f ∈ V is the final vertex, and A is a finite set of arcs.…”

Section: Control and Data Flow Coverage Criteriamentioning

confidence: 99%

“…Hong et al [58] assume the existence of a special predicate exit, which is true in any exit state (e.g., in the final vertex of a data flow graph). It is also suggested that the initial state can be used as an exit state, such that test cases can be seamlessly executed.…”

Section: Fault Visibilitymentioning

confidence: 99%

Testing with model checkers: a survey

Fraser

Wotawa

Ammann

2008

Software Testing Verif & Rel

146

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Abstract.About a decade after the initial proposal to use model checkers for the generation of test cases we take a look at the achievements in this field of research. Model checkers are formal verification tools, capable of providing counterexamples to violated properties. Normally, these counterexamples are meant to guide an analyst when searching for the root cause of a property violation. They are, however, also very useful as test cases. Many different approaches have been presented, many problems have been solved, yet many issues remain. This survey paper reviews the state of the art in testing with model checkers.

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“…Blom et al [12] and Hong et al [13] extend this idea by formalizing standard coverage criteria (all-definitions, all-uses, etc.) using observers (or temporal logic).…”

Section: Comparison To Related Workmentioning

confidence: 99%

Integrating formal verification and conformance testing for reactive systems

Constant

Jéron

Marchand

et al. 2007

IIEEE Trans. Software Eng.

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Abstract-In this paper, we describe a methodology integrating verification and conformance testing. A specification of a systeman extended input-output automaton, which may be infinite-state-and a set of safety properties ("nothing bad ever happens") and possibility properties ("something good may happen") are assumed. The properties are first tentatively verified on the specification using automatic techniques based on approximated state-space exploration, which are sound, but, as a price to pay for automation, are not complete for the given class of properties. Because of this incompleteness and of state-space explosion, the verification may not succeed in proving or disproving the properties. However, even if verification did not succeed, the testing phase can proceed and provide useful information about the implementation. Test cases are automatically and symbolically generated from the specification and the properties and are executed on a black-box implementation of the system. The test execution may detect violations of conformance between implementation and specification; in addition, it may detect violation/satisfaction of the properties by the implementation and by the specification. In this sense, testing completes verification. The approach is illustrated on simple examples and on a Bounded Retransmission Protocol.

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A Temporal Logic Based Theory of Test Coverage and Generation

Cited by 101 publications

References 24 publications

A survey of new trends in symbolic execution for software testing and analysis

A survey of new trends in symbolic execution for software testing and analysis

Testing with model checkers: a survey

Integrating formal verification and conformance testing for reactive systems

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