16,787 research outputs found
K-branching UIO sequences for partially specified observable non-deterministic FSMs
In black-box testing, test sequences may be constructed from systems modelled as deterministic finite-state machines (DFSMs) or, more generally, observable non-deterministic finite state machines (ONFSMs). Test sequences usually contain state identification sequences, with unique input output sequences (UIOs) often being used with DFSMs. This paper extends the notion of UIOs to ONFSMs. One challenge is that, as a result of non-determinism, the application of an input sequence can lead to exponentially many expected output sequences. To address this scalability problem, we introduce K-UIOs: K-UIOs that lead to at most K output sequences from states of M. We show that checking K-UIO existence is PSPACE-Complete if the problem is suitably bounded; otherwise it is in EXPSPACE and PSPACE-Hard. We provide a massively parallel algorithm for constructing K-UIOs and the results of experiments on randomly generated and real FSM specifications. The proposed algorithm was able to construct UIOs in cases where the existing UIO generation algorithm could not and was able to construct UIOs from FSMs with 38K states and 400K transitions
Canonical finite state machines for distributed systems
There has been much interest in testing from finite state machines (FSMs) as a result of their suitability for modelling or specifying state-based systems. Where there are multiple ports/interfaces a multi-port FSM is used and in testing, a tester is placed at each port. If the testers cannot communicate with one another directly and there is no global clock then we are testing in the distributed test architecture. It is known that the use of the distributed test architecture can affect the power of testing and recent work has characterised this in terms of local s-equivalence: in the distributed test architecture we can distinguish two FSMs, such as an implementation and a specification, if and only if they are not locally s-equivalent. However, there may be many FSMs that are locally s-equivalent to a given FSM and the nature of these FSMs has not been explored. This paper examines the set of FSMs that are locally s-equivalent to a given FSM M. It shows that there is a unique smallest FSM Ļmin(M) and a unique largest FSM Ļmax(M) that are locally s-equivalent to M. Here smallest and largest refer to the set of traces defined by an FSM and thus to its semantics. We also show that for a given FSM M the set of FSMs that are locally s-equivalent to M defines a bounded lattice. Finally, we define an FSM that, amongst all FSMs locally s-equivalent to M, has fewest states. We thus give three alternative canonical FSMs that are locally s-equivalent to an FSM M: one that defines the smallest set of traces, one that defines the largest set of traces, and one with fewest states. All three provide valuable information and the first two can be produced in time that is polynomial in terms of the number of states of M. We prove that the problem of finding an s-equivalent FSM with fewest states is NP-hard in general but can be solved in polynomial time for the special case where there are two ports
Testing Identifiable Kernel P Systems Using an X-machine Approach
This paper presents a testing approach for kernel P systems (kP systems),
based on the X-machine testing framework and the concept of cover automaton. The
testing methodology ensures that the implementation conforms the speci cations, under
certain conditions, such as the identi ably concept in the context of kernel P systems
Learning Moore Machines from Input-Output Traces
The problem of learning automata from example traces (but no equivalence or
membership queries) is fundamental in automata learning theory and practice. In
this paper we study this problem for finite state machines with inputs and
outputs, and in particular for Moore machines. We develop three algorithms for
solving this problem: (1) the PTAP algorithm, which transforms a set of
input-output traces into an incomplete Moore machine and then completes the
machine with self-loops; (2) the PRPNI algorithm, which uses the well-known
RPNI algorithm for automata learning to learn a product of automata encoding a
Moore machine; and (3) the MooreMI algorithm, which directly learns a Moore
machine using PTAP extended with state merging. We prove that MooreMI has the
fundamental identification in the limit property. We also compare the
algorithms experimentally in terms of the size of the learned machine and
several notions of accuracy, introduced in this paper. Finally, we compare with
OSTIA, an algorithm that learns a more general class of transducers, and find
that OSTIA generally does not learn a Moore machine, even when fed with a
characteristic sample
Constraint-Based Heuristic On-line Test Generation from Non-deterministic I/O EFSMs
We are investigating on-line model-based test generation from
non-deterministic output-observable Input/Output Extended Finite State Machine
(I/O EFSM) models of Systems Under Test (SUTs). We propose a novel
constraint-based heuristic approach (Heuristic Reactive Planning Tester (xRPT))
for on-line conformance testing non-deterministic SUTs. An indicative feature
of xRPT is the capability of making reasonable decisions for achieving the test
goals in the on-line testing process by using the results of off-line bounded
static reachability analysis based on the SUT model and test goal
specification. We present xRPT in detail and make performance comparison with
other existing search strategies and approaches on examples with varying
complexity.Comment: In Proceedings MBT 2012, arXiv:1202.582
Amorphous slicing of extended finite state machines
Slicing is useful for many Software Engineering applications and has been widely studied for three decades, but there has been comparatively little work on slicing Extended Finite State Machines (EFSMs). This paper introduces a set of dependency based EFSM slicing algorithms and an accompanying tool. We demonstrate that our algorithms are suitable for dependence based slicing. We use our tool to conduct experiments on ten EFSMs, including benchmarks and industrial EFSMs. Ours is the first empirical study of dependence based program slicing for EFSMs. Compared to the only previously published dependence based algorithm, our average slice is smaller 40% of the time and larger only 10% of the time, with an average slice size of 35% for termination insensitive slicing
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Using formal methods to support testing
Formal methods and testing are two important approaches that assist in the development of high quality software. While traditionally these approaches have been seen as rivals, in recent
years a new consensus has developed in which they are seen as complementary. This article reviews the state of the art regarding ways in which the presence of a formal specification can be used to assist testing
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