Natalia Kushik

On adaptive experiments for nondeterministic finite state machines

Adaptive experiments are well defined in the context of finite state machine (FSM) based analysis, in particular, in FSM based testing where homing and distinguishing experiments with FSMs are used for test derivation. In this paper, we define and propose algorithms for deriving adaptive homing and distinguishing experiments for non-initialized nondeterministic finite state machines (NFSMs). For NFSMs, the construction of adaptive experiments is rather complex as the partition over produced outputs does not define a partition over the set of states but a collection of intersecting subsets, and thus, the refinement of such set system is more difficult than the refinement of a partition. Given a complete non-initialized possibly non-observable NFSM, we establish necessary and sufficient conditions for having adaptive homing and distinguishing experiments and evaluate the height of these experiments.

On the length of homing sequences for nondeterministic finite state machines

Given a reduced deterministic finite state machine, there always exists a homing sequence of length polynomial with respect to the number of states of the machine. For nondeterministic reduced finite state machines, a homing sequence may not exist, and moreover, if it exists, its length can be exponential. We show that the problem of deriving a homing sequence cannot be reduced to deriving a synchronizing word for underlying automata and should be studied independently. We also propose a novel class of (n−1)-input finite state machines with n states whose shortest homing sequence is of length 2n−1−1.

Adaptive Homing and Distinguishing Experiments for Nondeterministic Finite State Machines

Adaptive experiments are well defined in the context of finite state machine (FSM) based analysis, in particular, in FSM based testing where homing and distinguishing experiments with FSMs are used in test derivation. In this paper, we define and propose algorithms for deriving adaptive homing and distinguishing experiments for non-initialized nondeterministic finite state machines (NFSM). For NFSMs, the construction of adaptive experiments is rather complex as the partition over produced outputs does not define a partition over the set of states but rather a collection of intersecting subsets, and thus, the refinement of such subsets is more difficult than the refinement of a partition. Given a complete non-initialized observable NFSM, we establish necessary and sufficient conditions for having adaptive homing and distinguishing experiments and evaluate the upper bound on the height of these experiments. Simple application examples demonstrating a proposed approach are provided.

On Testing against Partial Non-observable Specifications

As the complexity of communication systems increases, new techniques and strategies should be developed for testing and verification of the system components. In this paper, we focus on testing software components that implement communication protocols at various levels. Such implementations can be considered as reactive systems and we discuss how Finite State Machines (FSMs) might be used when deriving high quality tests and which properties can be held for corresponding FSMs when increasing/decreasing an abstraction level for the protocol specification. At the high abstraction level, the specification machine can be partial and non-observable, and we propose a test derivation strategy against such specifications. Furthermore, we turn to debugging techniques and discuss how an implementation bug can be located when the specification is partial and non-observable.

Evaluating Quality of Web Services: A Short Survey

This paper presents a short survey on the quality evaluation of web services. The most popular metrics for estimating such quality and user perception of web services are Quality of Service (QoS) and Quality of Experience (QoE), which represent objective and subjective assessments correspondingly. For different types of web services, the values of QoS and QoE are measured in different ways. In this paper, we consider various definitions of QoS based on web service parameters and describe several methods for evaluating QoS and QoE. We start with experimental evaluation of QoS based on network traffic analysis and further turn to model based methods for QoS estimating. Existing relationships between different kinds of service quality evaluation are also discussed.

Preset and adaptive homing experiments for nondeterministic finite state machines

In this paper, we present algorithms for preset and adaptive homing experiments for a given observable reduced nondeterministic finite state machine (NFSM). We show that the tight upper bound on a shortest preset homing sequence for a NFSM with n states and with two or more initial states is of order 2n2. The upper bound on a shortest adaptive homing sequence of a NFSM with m initial states, m ≤ n, states is of order Σj=2m Cnj and this upper bound is of order 2n when m tends to n.

Heuristics for Deriving Adaptive Homing and Distinguishing Sequences for Nondeterministic Finite State Machines

Distinguishing Sequences DS and Homing Sequences HS are used for state identification purposes in Finite State Machine FSM based testing. For deterministic FSMs, DS and HS related problems are well studied, for both preset and adaptive cases. There are also recent algorithms for checking the existence and constructing Adaptive DS and Adaptive HS for nondeterministic FSMs. However, most of the related problems are proven to be PSPACE-complete, while the worst case height of Adaptive DS and HS is known to be exponential. Therefore, novel heuristics and FSM classes where they can be applied need to be provided for effective derivation of such sequences. In this paper, we present a work in progress on the minimization of Adaptive DS and Adaptive HS for nondeterministic FSMs.

QoE Prediction for Multimedia Services: Comparing Fuzzy and Logic Network Approaches

This paper is devoted to the problem of evaluating the quality of experience (QoE) for a given multimedia service based on the values of service parameters such as QoS indicators. This paper proposes to compare two self learning approaches for predicting the QoE index, namely the approach based on logic circuit learning and the approach based on fuzzy logic expert systems. Experimental results for comparing these two approaches with respect to the prediction ability and the performance are provided.

QoE Evaluation Based on QoS and QoBiz Parameters Applied to an OTT Service

In this paper, we present a framework for evaluating the QoE of a service that includes functional and non-functional service requirements. Non-functional requirements are classified into objective, subjective, and business parameters that affect Quality of Service (QoS), Quality of Experience (QoE), and Quality of Business (QoBiz), correspondingly. As those metrics have a strong dependency between each other, we discuss how the QoE of a web-based Over-The-Top service (OTT) can be evaluated taking into account subjective, objective and business parameters. The functional service behavior is described by an Extended Finite State Machine (EFSM) in which non-functional objective, subjective and business-related parameters are tracked using context variables and corresponding updating functions. These parameters are used to evaluate the QoE of the service. We show that the corresponding model allows to keep a track of a user-service interaction. Moreover, the model of the service integrates subjective, objective and business parameters, and thus, can be applied to the QoE evaluation of any OTT service.

Describing Homing and Distinguishing Sequences for Nondeterministic Finite State Machines via Synchronizing Automata

There is a long standing problem of the study of homing and distinguishing sequences for deterministic and nondeterministic Finite State Machines (FSMs) which are widely used in many applications. A homing sequence allows establishing the state of the given FSM after applying the sequence while a distinguishing sequence allows learning the state of the given FSM before the sequence is applied. On the other hand, other sequences, namely, synchronizing sequences, have been thoroughly studied for finite automata. For a synchronizing automaton, there is a state such that a synchronizing sequence takes the automaton from any state to this state. There are many papers reported on such automata as well as on the complexity of synchronizing sequences. In this paper, given a complete nondeterministic FSM, we propose a method for deriving a corresponding finite automaton such that the set of all homing (or distinguishing) sequences coincides with the set of all synchronizing sequences of the derived automaton.