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

Improving fault coverage and minimising the cost of fault identification when testing from finite state machines

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Software needs to be adequately tested in order to increase the confidence that the system being developed is reliable. However, testing is a complicated and expensive process. Formal specification based models such as finite state machines have been widely used in system modelling and testing. In this PhD thesis, we primarily investigate fault detection and identification when testing from finite state machines. The research in this thesis is mainly comprised of three topics - construction of multiple Unique Input/Output (UIO) sequences using Metaheuristic Optimisation Techniques (MOTs), the improved fault coverage by using robust Unique Input/Output Circuit (UIOC) sequences, and fault diagnosis when testing from finite state machines. In the studies of the construction of UIOs, a model is proposed where a fitness function is defined to guide the search for input sequences that are potentially UIOs. In the studies of the improved fault coverage, a new type of UIOCs is defined. Based upon the Rural Chinese Postman Algorithm (RCPA), a new approach is proposed for the construction of more robust test sequences. In the studies of fault diagnosis, heuristics are defined that attempt to lead to failures being observed in some shorter test sequences, which helps to reduce the cost of fault isolation and identification. The proposed approaches and techniques were evaluated with regard to a set of case studies, which provides experimental evidence for their efficacy.Brunel Research Initiative and Enterprise Fund (BRIEF) Award from Brunel University and Departmental bursary from Department of Information Systems and Computing, Brunel Universit

Estimating the feasibility of transition paths in extended finite state machines

There has been significant interest in automating testing on the basis of an extended finite state machine (EFSM) model of the required behaviour of the implementation under test (IUT). Many test criteria require that certain parts of the EFSM are executed. For example, we may want to execute every transition of the EFSM. In order to find a test suite (set of input sequences) that achieves this we might first derive a set of paths through the EFSM that satisfy the criterion using, for example, algorithms from graph theory. We then attempt to produce input sequences that trigger these paths. Unfortunately, however, the EFSM might have infeasible paths and the problem of determining whether a path is feasible is generally undecidable. This paper describes an approach in which a fitness function is used to estimate how easy it is to find an input sequence to trigger a given path through an EFSM. Such a fitness function could be used in a search-based approach in which we search for a path with good fitness that achieves a test objective, such as executing a particular transition, and then search for an input sequence that triggers the path. If this second search fails then we search for another path with good fitness and repeat the process. We give a computationally inexpensive approach (fitness function) that estimates the feasibility of a path. In order to evaluate this fitness function we compared the fitness of a path with the ease with which an input sequence can be produced using search to trigger the path and we used random sampling in order to estimate this. The empirical evidence suggests that a reasonably good correlation (0.72 and 0.62) exists between the fitness of a path, produced using the proposed fitness function, and an estimate of the ease with which we can randomly generate an input sequence to trigger the path

Automated test sequence generation for finite state machines using genetic algorithms

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Testing software implementations, formally specified using finite state automata (FSA) has been of interest. Such systems include communication protocols and control sections of safety critical systems. There is extensive literature regarding how to formally validate an FSM based specification, but testing that an implementation conforms to the specification is still an open problem. Two aspects of FSA based testing, both NP-hard problems, are discussed in this thesis and then combined. These are the generation of state verification sequences (UIOs) and the generation of sequences of conditional transitions that are easy to trigger. In order to facilitate test sequence generation a novel representation of the transition conditions and a number of fitness function algorithms are defined. An empirical study of the effectiveness on real FSA based systems and example FSAs provides some interesting positive results. The use of genetic algorithms (GAs) makes these problems scalable for large FSAs. The experiments used a software tool that was developed in Java

Distinguishing sequences for partially specified FSMs

Distinguishing Sequences (DSs) are used inmany Finite State Machine (FSM) based test techniques. Although Partially Specified FSMs (PSFSMs) generalise FSMs, the computational complexity of constructing Adaptive and Preset DSs (ADSs/PDSs) for PSFSMs has not been addressed. This paper shows that it is possible to check the existence of an ADS in polynomial time but the corresponding problem for PDSs is PSPACE-complete. We also report on the results of experiments with benchmarks and over 8 * 106 PSFSMs. © 2014 Springer International Publishing

Testing in context: Efficiency and executability

Testing each software component in isolation is not always feasible. We consider testing a deterministic Implementation Under Test (IUT) together with some other correctly implemented components as its context. One of the essential issues of testing in context is test executability problem, i.e., tests generated solely from the specification of the IUT may not be executable due to the uncontrollable interaction between the IUT and its context. On the other hand, generating a test sequence from the abstract specifications of a stateful IUT and its context often suffers from the well-known state explosion problem. In this dissertation, we solve the problem of generating a minimal-length test sequence from a given specification of a stateful IUT and its embedded context. By adopting model checking techniques, we avoid the state explosion problem during test generation and avoid the test executability problem during testing in context

Test Sequences for Web Service Composition using CPN model

Web service composition is most mature and effective way to realize the rapidly changing requirements of business in service-oriented solutions. Testing the compositions of web services is complex, due to their distributed nature and asynchronous behaviour. Colored Petri Nets (CPNs) provide a framework for the design, specification, validation and verification of systems. In this paper the CPN model used for composition design verification is reused for test design purpose. We propose an on-the-fly algorithm that generates a test suite that covers all possible paths without redundancy.  The prioritization of test sequences, test suite size and redundancy reduction are also focused. The proposed technique was applied to air line reservation system and the generated test sequences were evaluated against three coverage criteria; Decision Coverage, Input Output Coverage and Transition Coverage. Keywords— CPN, MBT, web service composition testing, test case generatio

Improving fault coverage and minimising the cost of fault identification when testing from finite state machines

Software needs to be adequately tested in order to increase the confidence that the system being developed is reliable. However, testing is a complicated and expensive process. Formal specification based models such as finite state machines have been widely used in system modelling and testing. In this PhD thesis, we primarily investigate fault detection and identification when testing from finite state machines. The research in this thesis is mainly comprised of three topics - construction of multiple Unique Input/Output (UIO) sequences using Metaheuristic Optimisation Techniques (MOTs), the improved fault coverage by using robust Unique Input/Output Circuit (UIOC) sequences, and fault diagnosis when testing from finite state machines. In the studies of the construction of UIOs, a model is proposed where a fitness function is defined to guide the search for input sequences that are potentially UIOs. In the studies of the improved fault coverage, a new type of UIOCs is defined. Based upon the Rural Chinese Postman Algorithm (RCPA), a new approach is proposed for the construction of more robust test sequences. In the studies of fault diagnosis, heuristics are defined that attempt to lead to failures being observed in some shorter test sequences, which helps to reduce the cost of fault isolation and identification. The proposed approaches and techniques were evaluated with regard to a set of case studies, which provides experimental evidence for their efficacy.EThOS - Electronic Theses Online ServiceGBUnited Kingdo