Testing conformance of a deterministic implementation against a non-deterministic stream X-machine

Stream X-machines are a formalisation of extended finite state machines that have been used to specify systems. One of the great benefits of using stream X-machines, for the purpose of specification, is the associated test generation technique which produces a test that is guaranteed to determine correctness under certain design for test conditions. This test generation algorithm has recently been extended to the case where the specification is non-deterministic. However, the algorithms for testing from a non-deterministic stream X-machine currently have limitations: either they test for equivalence, rather than conformance or they restrict the source of non-determinism allowed in the specification. This paper introduces a new test generation algorithm that overcomes both of these limitations, for situations where the implementation is known to be deterministic

A search-based approach for automatic test generation from extended finite state machine (EFSM)

The extended finite state machine is a powerful model that can capture almost all the aspects of a system. However, testing from an EFSM is yet a challenging task due to two main problems: path feasibility and path test data generation. Although optimization algorithms are efficient, their applications to EFSM testing have received very little attention. The aim of this paper is to develop a novel approach that utilizes optimization algorithms to test from EFSM models

Generating feasible transition paths for testing from an extended finite state machine (EFSM)

The problem of testing from an extended finite state machine (EFSM) can be expressed in terms of finding suitable paths through the EFSM and then deriving test data to follow the paths. A chosen path may be infeasible and so it is desirable to have methods that can direct the search for appropriate paths through the EFSM towards those that are likely to be feasible. However, generating feasible transition paths (FTPs) for model based testing is a challenging task and is an open research problem. This paper introduces a novel fitness metric that analyzes data flow dependence among the actions and conditions of the transitions in order to estimate the feasibility of a transition path. The proposed fitness metric is evaluated by being used in a genetic algorithm to guide the search for FTPs

Testing Non-deterministic Stream X-machine Models and P systems

AbstractUnder certain well defined conditions, the stream X-machine testing method can produce a test set that is guaranteed to determine the correctness of an implementation. The testing method has originally assumed that an implementation of each processing function or relation is proven to be correct before the actual testing can take place. Such a limitation has been removed in a subsequent paper, but only for deterministic X-machines. This paper extends this result to non-deterministic stream X-machines and considers a conformance relationship between a specification and an implementation, rather than mere equivalence. Furthermore, it shows how this method can be applied to test a P system by building a suitable stream X-machine from the derivation tree associated with a partial computation

Testing a deterministic implementation against a non-controllable non-deterministic stream X-machine

A stream X-machine is a type of extended finite state machine with an associated development approach that consists of building a system from a set of trusted components. One of the great benefits of using stream X-machines for the purpose of specification is the existence of test generation techniques that produce test suites that are guaranteed to determine correctness as long as certain well-defined conditions hold. One of the conditions that is traditionally assumed to hold is controllability: this insists that all paths through the stream X-machine are feasible. This restrictive condition has recently been weakened for testing from a deterministic stream X-machine. This paper shows how controllability can be replaced by a weaker condition when testing a deterministic system against a non-deterministic stream X-machine. This paper therefore develops a new, more general, test generation algorithm for testing from a non-deterministic stream X-machine

Automatic generation of test sequences form EFSM models using evolutionary algorithms

Automated test data generation through evolutionary testing (ET) is a topic of interest to the software engineering community. While there are many ET-based techniques for automatically generating test data from code, the problem of generating test data from an extended finite state machine (EFSMs) is more complex and has received little attention. In this paper, we introduce a novel approach that addresses the problem of generating input test sequences that trigger given feasible paths in an EFSM model by employing an ET-based technique. The proposed approach expresses the problem as a search for input parameters to be applied to a set of functions to be called sequentially. In order to apply ET-based technique, a new fitness function is introduced to cope with the case when a test target involves calls to a set of transitions sequentially. We evaluate our approach empirically using five sets of randomly generated paths through two EFSM case studies: INRES and class 2 transport protocols. In the experiments, we apply two search techniques: a random and an ET-based which utilizes our new fitness function. Experimental results show that the proposed approach produces input test sequences that trigger all the feasible paths used with a success rate of 100%, however, the random technique failed in most cases with a success rate of 20.8%

An integrated search-based approach for automatic testing from extended finite state machine (EFSM) models

This is the post-print version of the Article - Copyright @ 2011 ElsevierThe extended finite state machine (EFSM) is a modelling approach that has been used to represent a wide range of systems. When testing from an EFSM, it is normal to use a test criterion such as transition coverage. Such test criteria are often expressed in terms of transition paths (TPs) through an EFSM. Despite the popularity of EFSMs, testing from an EFSM is difficult for two main reasons: path feasibility and path input sequence generation. The path feasibility problem concerns generating paths that are feasible whereas the path input sequence generation problem is to find an input sequence that can traverse a feasible path. While search-based approaches have been used in test automation, there has been relatively little work that uses them when testing from an EFSM. In this paper, we propose an integrated search-based approach to automate testing from an EFSM. The approach has two phases, the aim of the first phase being to produce a feasible TP (FTP) while the second phase searches for an input sequence to trigger this TP. The first phase uses a Genetic Algorithm whose fitness function is a TP feasibility metric based on dataflow dependence. The second phase uses a Genetic Algorithm whose fitness function is based on a combination of a branch distance function and approach level. Experimental results using five EFSMs found the first phase to be effective in generating FTPs with a success rate of approximately 96.6%. Furthermore, the proposed input sequence generator could trigger all the generated feasible TPs (success rate = 100%). The results derived from the experiment demonstrate that the proposed approach is effective in automating testing from an EFSM

A search-based technique for testing from extended finite state machine model

Extended finite state machines (EFSMs), and languages such as state-charts that are similar to EFSMs, are widely used to model state-based systems. When testing from an EFSM M it is common to aim to produce a set of test sequences (input sequences) that satisfies a test criterion that relates to the transition paths (TPs) of M that are executed by the test sequences. For example, we might require that the set of TPs triggered includes all of the transitions of M. One approach to generating such a set of test sequences is to split the problem into two stages: choosing a set of TPs that achieves the test criterion and then producing test sequences to trigger these TPs. However, the EFSM may contain infeasible TPs and the problem of generating a test sequence to trigger a given feasible TP (FTP) is generally uncomputable. In this paper we present a search-based approach that uses two techniques: (1) A TP fitness metric based on our previous work that estimates the feasibility of a given transition path; and (2) A fitness function to guide the search for a test sequence to trigger a given FTP. We evaluated our approach on five EFSMs: A simple in-flight safety system; a class II transport protocol; a lift system; an ATM; and the Inres initiator. In the experiments the proposed approach successfully tested approximately 96.75 % of the transitions and the proposed test sequence generation technique triggered all of the generated FTPs

Testing Conformance of a Deterministic Implementation against a Non-Deterministic Stream X-Machine

Stream X-machines are a formalisation of extended nite state machines that have been used to specify systems. One of the great bene ts of using stream X-machines, for the purpose of speci cation, is the associated test generation technique which produces a test that is guaranteed to determine correctness under certain design for test conditions. This test generation algorithm has recently been extended to the case where the speci cation is non-deterministic. However, the algorithms for testing from a non-deterministic stream X-machine currently have limitations: either they test for equivalence, rather than conformance or they restrict the source of non-determinism allowed in the speci cation. This paper introduces a new test generation algorithm that overcomes both of these limitations, for situations where the implementation is known to be deterministic

Software engineering: Testing real-time embedded systems using timed automata based approaches

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Real-time Embedded Systems (RTESs) have an increasing role in controlling society infrastructures that we use on a day-to-day basis. RTES behaviour is not based solely on the interactions it might have with its surrounding environment, but also on the timing requirements it induces. As a result, ensuring that an RTES behaves correctly is non-trivial, especially after adding time as a new dimension to the complexity of the testing process. This research addresses the problem of testing RTESs from Timed Automata (TA) specification by the following. First, a new Priority-based Approach (PA) for testing RTES modelled formally as UPPAAL timed automata (TA variant) is introduced. Test cases generated according to a proposed timed adequacy criterion (clock region coverage) are divided into three sets of priorities, namely boundary, out-boundary and in-boundary. The selection of which set is most appropriate for a System Under Test (SUT) can be decided by the tester according to the system type, time specified for the testing process and its budget. Second, PA is validated in comparison with four well-known timed testing approaches based on TA using Specification Mutation Analysis (SMA). To enable the validation, a set of timed and functional mutation operators based on TA is introduced. Three case studies are used to run SMA. The effectiveness of timed testing approaches are determined and contrasted according to the mutation score which shows that our PA achieves high mutation adequacy score compared with others. Third, to enhance the applicability of PA, a new testing tool (GeTeX) that deploys PA is introduced. In its current version, GeTeX supports Control Area Network (CAN) applications. GeTeX is validated by developing a prototype for that purpose. Using GeTeX, PA is also empirically validated in comparison with some TA testing approaches using a complete industrial-strength test bed. The assessment is based on fault coverage, structural coverage, the length of generated test cases and a proposed assessment factor. The assessment is based on fault coverage, structural coverage, the length of generated test cases and a proposed assessment factor. The assessment results confirmed the superiority of PA over the other test approaches. The overall assessment factor showed that structural and fault coverage scores of PA with respect to the length of its tests were better than the others proving the applicability of PA. Finally, an Analytical Hierarchy Process (AHP) decision-making framework for our PA is developed. The framework can provide testers with a systematic approach by which they can prioritise the available PA test sets that best fulfils their testing requirements. The AHP framework developed is based on the data collected heuristically from the test bed and data collected by interviewing testing experts. The framework is then validated using two testing scenarios. The decision outcomes of the AHP framework were significantly correlated to those of testing experts which demonstrated the soundness and validity of the framework.This study is funded by Damascus University, Syri