32 research outputs found

    Search Based Software Engineering in Membrane Computing

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    This paper presents a testing approach for kernel P Systems (kP systems), based on test data generation for a given scenario. This method uses Genetic Algorithms to generate the input sets needed to trigger the given computation steps

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

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    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

    Search-based software engineering: A search-based approach for testing from extended finite state machine (EFSM) models

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    This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The extended finite state machine (EFSM) is a powerful modelling approach that has been applied to represent a wide range of systems. Despite its popularity, testing from an EFSM is a substantial problem for two main reasons: path feasibility and path test case generation. The path feasibility problem concerns generating transition paths through an EFSM that are feasible and satisfy a given test criterion. In an EFSM, guards and assignments in a path‟s transitions may cause some selected paths to be infeasible. The problem of path test case generation is to find a sequence of inputs that can exercise the transitions in a given feasible path. However, the transitions‟ guards and assignments in a given path can impose difficulties when producing such data making the range of acceptable inputs narrowed down to a possibly tiny range. While search-based approaches have proven efficient in automating aspects of testing, these have received little attention when testing from EFSMs. This thesis proposes an integrated search-based approach to automatically test from an EFSM. The proposed approach generates paths through an EFSM that are potentially feasible and satisfy a test criterion. Then, it generates test cases that can exercise the generated feasible paths. The approach is evaluated by being used to test from five EFSM cases studies. The achieved experimental results demonstrate the value of the proposed approach.Aleppo University, Syri

    Multi-objective construction of an entire adequate test suite for an EFSM

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    In this paper we propose a method and a tool to generate test suites from extended finite state machines, accounting for multiple (potentially conflicting) objectives. We aim at maximizing coverage and feasibility of a test suite while minimizing similarity between its test cases and minimizing overall cost. Therefore, we define a multi-objective genetic algorithm that searches for optimal test suites based on four objective functions. In doing so, we create an entire test suite at once as opposed to test cases one at a time. Our approach is evaluated on two different case studies, showing interesting initial results

    Validation and Verification of Safety-Critical Systems in Avionics

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    This research addresses the issues of safety-critical systems verification and validation. Safety-critical systems such as avionics systems are complex embedded systems. They are composed of several hardware and software components whose integration requires verification and testing in compliance with the Radio Technical Commission for Aeronautics standards and their supplements (RTCA DO-178C). Avionics software requires certification before its deployment into an aircraft system, and testing is mandatory for certification. Until now, the avionics industry has relied on expensive manual testing. The industry is searching for better (quicker and less costly) solutions. This research investigates formal verification and automatic test case generation approaches to enhance the quality of avionics software systems, ensure their conformity to the standard, and to provide artifacts that support their certification. The contributions of this thesis are in model-based automatic test case generations approaches that satisfy MC/DC criterion, and bidirectional requirement traceability between low-level requirements (LLRs) and test cases. In the first contribution, we integrate model-based verification of properties and automatic test case generation in a single framework. The system is modeled as an extended finite state machine model (EFSM) that supports both the verification of properties and automatic test case generation. The EFSM models the control and dataflow aspects of the system. For verification, we model the system and some properties and ensure that properties are correctly propagated to the implementation via mandatory testing. For testing, we extended an existing test case generation approach with MC/DC criterion to satisfy RTCA DO-178C requirements. Both local test cases for each component and global test cases for their integration are generated. The second contribution is a model checking-based approach for automatic test case generation. In the third contribution, we developed an EFSM-based approach that uses constraints solving to handle test case feasibility and addresses bidirectional requirements traceability between LLRs and test cases. Traceability elements are determined at a low-level of granularity, and then identified, linked to their source artifact, created, stored, and retrieved for several purposes. Requirements’ traceability has been extensively studied but not at the proposed low-level of granularity

    Search-based software engineering : a search-based approach for testing from extended finite state machine (EFSM) models

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    The extended finite state machine (EFSM) is a powerful modelling approach that has been applied to represent a wide range of systems. Despite its popularity, testing from an EFSM is a substantial problem for two main reasons: path feasibility and path test case generation. The path feasibility problem concerns generating transition paths through an EFSM that are feasible and satisfy a given test criterion. In an EFSM, guards and assignments in a path‟s transitions may cause some selected paths to be infeasible. The problem of path test case generation is to find a sequence of inputs that can exercise the transitions in a given feasible path. However, the transitions‟ guards and assignments in a given path can impose difficulties when producing such data making the range of acceptable inputs narrowed down to a possibly tiny range. While search-based approaches have proven efficient in automating aspects of testing, these have received little attention when testing from EFSMs. This thesis proposes an integrated search-based approach to automatically test from an EFSM. The proposed approach generates paths through an EFSM that are potentially feasible and satisfy a test criterion. Then, it generates test cases that can exercise the generated feasible paths. The approach is evaluated by being used to test from five EFSM cases studies. The achieved experimental results demonstrate the value of the proposed approach.EThOS - Electronic Theses Online ServiceAleppo University, SyriaGBUnited Kingdo

    Aplicaciones de la teoría de la información y la inteligencia artificial al testing de software

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    Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Ingeniería de Sistemas lnformáticos y de Computación, leída el 4-05-2022Software Testing is a critical field for the software industry, as it has the main tools used to ensure the reliability of the produced software. Currently, mor then 50% of the time and resources for creating a software product are diverted to testing tasks, from unit testing to system testing. Moreover, there is a huge interest into automatising this field, as software gets bigger and the amount of required testing increases. however, software Testing is not only an industry oriented field; it is also a really interesting field with a noble goal (improving the reliability of software systems) that at the same tieme is full of problems to solve....Es Testing Software es un campo crítico para la industria del software, ya que éste contienen las principales herramientas que se usan para asegurar la fiabilidad del software producido. Hoy en día, más del 50% del tiempo y recursos necesarios para crear un producto software son dirigidos a tareas de testing, desde el testing unitario al testing a nivel de sistema. Más aún, hay un gran interés en automatizar este campo, ya que el software cada vez es más grande y la cantidad de testing requerido crece. Sin embargo, el Testing de Software no es solo un campo orientado a la industria; también es un campo muy interesante con un objetivo noble (mejorar la fiabilidad de los sistemas software) que al mismo tiempo está lleno de problemas por resolver...Fac. de InformáticaTRUEunpu

    Fail-Safe Test Generation of Safety Critical Systems

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    This dissertation introduces a technique for testing proper failure mitigation in safety critical systems. Unlike other approaches which integrate behavioral and failure models, and then generate tests from the integrated model, we build safety mitigation tests from an existing behavioral test suite, using an explicit mitigation model for which we generate mitigation paths which are then woven at selected failure points into the original test suite to create failure-mitigation tests (safety mitigation test)

    Reverse Engineering Systems to Identify Flaws and Understand Behaviour

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    Accurate system models are applicable to many software engineering tasks. Despite their utility, models are often neglected during development. It is therefore desirable to reverse engineer them from existing systems. One way to do this is to record traces of the system and infer a model by generalising from this behaviour. Unfortunately, the models inferred by current techniques often cannot represent how the data values associated with each action affect system behaviour. This raises the following questions. What kind of model do we need in order to show the interplay between behaviour and data? How can we infer such models from system traces? How can we infer functions to relate input data with subsequent outputs? How can we use our models once they have been inferred? To answer these questions, the first contribution of this thesis is a new model definition designed to show the relationship between data and behaviour. Secondly, I present a technique to infer such models from system traces, and define a preprocessing step to infer functions that relate system inputs and outputs. I then empirically evaluate the models produced by my technique and compare them to those produced by a state-of-the-art tool. Finally, I show how the inferred models can be used to analyse properties of the systems they represent. The results show that my technique infers models which are more accurate and intuitive than the current state of the art. My tool can also handle circumstances where the output of a system depends on data values not present in the traces, and can identify situations where the result of particular actions depends on specific data values. The models inferred by my tool can be used by existing verification tools to prove and refute properties of the underlying systems
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