Chaining Test Cases for Reactive System Testing (extended version)

Testing of synchronous reactive systems is challenging because long input sequences are often needed to drive them into a state at which a desired feature can be tested. This is particularly problematic in on-target testing, where a system is tested in its real-life application environment and the time required for resetting is high. This paper presents an approach to discovering a test case chain---a single software execution that covers a group of test goals and minimises overall test execution time. Our technique targets the scenario in which test goals for the requirements are given as safety properties. We give conditions for the existence and minimality of a single test case chain and minimise the number of test chains if a single test chain is infeasible. We report experimental results with a prototype tool for C code generated from Simulink models and compare it to state-of-the-art test suite generators.Comment: extended version of paper published at ICTSS'1

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

Towards automatic generation of parameterized test cases from abstractions

Model-based tools for automatic test generation usually can handle systems of a rather limited size. Therefore, they cannot be applied directly to systems of real industrial size. Here, we propose an approach to test generation combining enumerative data abstraction, test generation methods and constraint solving. The approach allows applying enumerative test generation tools like TGV to large and infinite systems. Given such a system, abstractions allow to derive a finite abstract system suitable for automatic test generation with enumerative tools. Abstract test cases need to be parameterized with actual test data, in order to execute them. For data selection, we make use of constraint solving techniques. Test case execution will later be done by TTCN-

Metamodel Instance Generation: A systematic literature review

Modelling and thus metamodelling have become increasingly important in Software Engineering through the use of Model Driven Engineering. In this paper we present a systematic literature review of instance generation techniques for metamodels, i.e. the process of automatically generating models from a given metamodel. We start by presenting a set of research questions that our review is intended to answer. We then identify the main topics that are related to metamodel instance generation techniques, and use these to initiate our literature search. This search resulted in the identification of 34 key papers in the area, and each of these is reviewed here and discussed in detail. The outcome is that we are able to identify a knowledge gap in this field, and we offer suggestions as to some potential directions for future research.Comment: 25 page

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

A recommender system for process discovery

Over the last decade, several algorithms for process discovery and process conformance have been proposed. Still, it is well-accepted that there is no dominant algorithm in any of these two disciplines, and then it is often difficult to apply them successfully. Most of these algorithms need a close-to expert knowledge in order to be applied satisfactorily. In this paper, we present a recommender system that uses portfolio-based algorithm selection strategies to face the following problems: to find the best discovery algorithm for the data at hand, and to allow bridging the gap between general users and process mining algorithms. Experiments performed with the developed tool witness the usefulness of the approach for a variety of instances.Peer ReviewedPostprint (author’s final draft

Addressing performance requirements in the FDT-based design of distributed systems

The development of distributed systems is generally regarded as a complex and costly task, and for this reason formal description techniques such as LOTOS and ESTELLE (both standardized by the ISO) are increasingly used in this process. Our experience is that LOTOS can be exploited at many stages on the design trajectory, from requirements specification to implementation, but that the language elements do not allow direct formalization of performance requirements. To avoid duplication of effort by using two formalisms with distinct approaches, we propose a design method that incorporates performance constraints in an heuristic but effective manner

Meta-model Pruning

Large and complex meta-models such as those of Uml and its profiles are growing due to modelling and inter-operability needs of numerous\ud stakeholders. The complexity of such meta-models has led to coining\ud of the term meta-muddle. Individual users often exercise only a small\ud view of a meta-muddle for tasks ranging from model creation to construction\ud of model transformations. What is the effective meta-model that represents\ud this view? We present a flexible meta-model pruning algorithm and\ud tool to extract effective meta-models from a meta-muddle. We use\ud the notion of model typing for meta-models to verify that the algorithm\ud generates a super-type of the large meta-model representing the meta-muddle.\ud This implies that all programs written using the effective meta-model\ud will work for the meta-muddle hence preserving backward compatibility.\ud All instances of the effective meta-model are also instances of the\ud meta-muddle. We illustrate how pruning the original Uml metamodel\ud produces different effective meta-models