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  • 1.
    Hatvani, Leo
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Formal Verification of Adaptive Real-Time Systems by Extending Task Automata2014Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Recently, we have seen an increase in the deployment of safety critical embedded systems in rapidly changing environments, as well as requirement for on-site customizations and rapid adaptation. To address the extended range of requirements, adaptation mechanism are added to the systems to handle large number of situations appropriately. Although necessary, adaptations can cause inconsistent and unstable configurations that must be prevented for the embedded system to remain dependable and safe. Therefore, verifying the behavior of adaptive embedded systems during the design phase of the production process is highly desirable.

    A hard real time embedded system and its environment can be modeled using timed automata. Such model can describe the system at various levels of abstraction. In this thesis, we model the adaptive responses of a system in terms of tasks that are executed to handle changes in the environmental or internal parameters.

    Schedulability, a property that all tasks complete execution within their respective deadlines, is a key element in designing hard real-time embedded systems. A system that is unschedulable immediately compromises safety and hard real-time requirements and can cause fatal failure. Given specifications of all tasks in the system, we can model the system, an abstraction of the environment, and adaptive strategies to investigate whether the system retains safety properties, including schedulability, regardless of the changes in the environment and adaptations to those changes.

  • 2.
    Hatvani, Leo
    et al.
    Technische Universiteit, The Netherlands.
    Afshar, Sara Zargari
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    J. Bril, Reinder
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Technische Universiteit, The Netherlands.
    Optimal Priority and Threshold Assignment for Fixed-priority Preemption Threshold Scheduling2018In: ACM SIGBED Review, E-ISSN 1551-3688, no 1, p. 43-49Article in journal (Refereed)
    Abstract [en]

    Fixed-priority preemption-threshold scheduling (FPTS) is a generalization of fixed-priority preemptive scheduling (FPPS) and fixed-priority non-preemptive scheduling (FPNS). Since FPPS and FPNS are incomparable in terms of potential schedulability, FPTS has the advantage that it can schedule any task set schedulable by FPPS or FPNS and some that are not schedulable by either. FPTS is based on the idea that each task is assigned a priority and a preemption threshold. While tasks are admitted into the system according to their priorities, they can only be preempted by tasks that have priority higher than the preemption threshold.

    This paper presents a new optimal priority and preemption threshold assignment (OPTA) algorithm for FPTS which in general outperforms the existing algorithms in terms of the size of the explored state-space and the total number of worst case response time calculations performed. The algorithm is based on back-tracking, i.e. it traverses the space of potential priorities and preemption thresholds, while pruning infeasible paths, and returns the first assignment deemed schedulable.

    We present the evaluation results where we compare the complexity of the new algorithm with the existing one. We show that the new algorithm significantly reduces the time needed to find a solution. Through a comparative evaluation, we show the improvements that can be achieved in terms of schedulability ratio by our OPTA compared to a deadline monotonic priority assignment.

  • 3.
    Hatvani, Leo
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    David, Alexandre
    Aalborg University, Danmark.
    Seceleanu, Cristina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Pettersson, Paul
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Adaptive Task Automata with Earliest-Deadline-First Scheduling2014Report (Other (popular science, discussion, etc.))
    Abstract [en]

    Adjusting to resource changes, dynamic environmental conditions, or new usage modes are some of the reasons why real-time embedded systems need to be adaptive. This requires a rigorous framework for designing such systems, to ensure that the adaptivity does not result in invalidating the system's real-time constraints.

    To address this need, we have recently introduced adaptive task automata, a framework for modeling, verification, and schedulability analysis in adaptive, hard real-time embedded systems, assuming a fixed-priority scheduler.

    In this work, we extend the adaptive task automata framework to incorporate the earliest-deadline-first scheduling policy, as well as enable implementation of any other dynamic scheduling policy. To prove the decidability of our model, and at the same time maintain a manageable degree of conciseness, we show an encoding of our model as a network of timed automata with clock updates. To support this, we also show that reachability in our class of timed automata with updates is decidable. Our contribution helps to streamline the process of designing safety critical adaptive embedded systems.

  • 4.
    Hatvani, Leo
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    David, Alexandre
    Aalborg University, Danmark.
    Seceleanu, Cristina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Pettersson, Paul
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Adaptive Task Automata with Earliest-Deadline-First Scheduling2014In: Electronic Communications of the EASST, ISSN 1863-2122, E-ISSN 1863-2122, Vol. 70Article in journal (Refereed)
    Abstract [en]

    Adjusting to resource changes, dynamic environmental conditions, or new usage modes are some of the reasons why real-time embedded systems need to be adaptive. This requires a rigorous framework for designing such systems, to ensure that the adaptivity does not result in invalidating the system's real-time constraints.

    To address this need, we have recently introduced adaptive task automata, a framework for modeling, verification, and schedulability analysis in adaptive, hard real-time embedded systems, assuming a fixed-priority scheduler.

    In this work, we extend the adaptive task automata framework to incorporate the earliest-deadline-first scheduling policy, as well as enable implementation of any other dynamic scheduling policy. To prove the decidability of our model, and at the same time maintain a manageable degree of conciseness, we show an encoding of our model as a network of timed automata with clock updates. To support this, we also show that reachability in our class of timed automata with updates is decidable. Our contribution helps to streamline the process of designing safety critical adaptive embedded systems.

  • 5.
    Hatvani, Leo
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Jansen, Anton
    Mälardalen University, School of Innovation, Design and Engineering.
    Seceleanu, Cristina
    ABB Corporate Research, Västerås, Sweden.
    Pettersson, Paul
    Mälardalen University, School of Innovation, Design and Engineering.
    An integrated tool for trade-off analysis of quality-of-service attributes2010In: Proceedings of The 2nd International Workshop on the Quality of Service-Oriented Software Systems, New York: ACM , 2010, p. Art no. 2-Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a tool for performing trade-off analysis of Quality-of-Service attributes of design solutions resulted from architectural, behavioral, or deployment changes in service-oriented systems. The tool allows for comparing the performance, reliability, and maintainability of such solutions, in an attempt to compute the optimal one with respect to the weighted sum of the considered quality attributes. Our tool uses the Analytic Hierarchy Process for computing trade-offs, and is integrated into the Quality Impact Prediction for Evolving Service-Oriented Software IDE.

  • 6.
    Hatvani, Leo
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Pettersson, Paul
    Mälardalen University, School of Innovation, Design and Engineering.
    Seceleanu, Cristina
    Mälardalen University, School of Innovation, Design and Engineering.
    Adaptive task automata: A framework for verifying adaptive embedded systems2012In: Lecture Notes in Computer Science, vol. 7212, Springer, 2012, p. 115-129Chapter in book (Refereed)
    Abstract [en]

    We present a framework for modeling and analysis of adaptive embedded systems, based on the model of timed automata with tasks. The model is extended with primitives allowing modeling of adaptivity, by testing the potential schedulability of a given task, in the context of the set of currently enqueued tasks. This makes it possible to describe adaptive embedded systems, in which decisions to admit further tasks or take other measures of adaptivity is based on available CPU resources, external, or internal events. We show that this model can be encoded in the framework of timed automata, and hence that the problem is decidable. We also validate the framework, by using the Uppaal tool.

  • 7.
    Hatvani, Leo
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Seceleanu, Cristina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Pettersson, Paul
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Modeling and Analysis of Adaptive Embedded Systems using Adaptive Task Automata2013In: SIGBED Rev., ISSN 1551-3688, Vol. 10, no 1, p. 43-47Article in journal (Refereed)
    Abstract [en]

    Most embedded systems need to continually function in unpredictable environments. One way to achieve high dependability is to make the system adaptive to changes, if possible, without sacrificing maintainability. To be able to reason about adaptivity, one needs a modeling and analysis framework suitable for adaptive systems. Recently, we have introduced Adaptive Task Automata, to meet this goal. In this paper, we overview the current functionality implemented in the Adaptive Task Automata framework (ATA), as well as some of the challenges encountered during the development. In the end, we enumerate possible future extensions of ATA.

  • 8.
    Tahvili, Sahar
    et al.
    RISE SICS Västerås.
    Hatvani, Leo
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Felderer, Michael
    University of Innsbruck Innsbruck, Austria.
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bohlin, Markus
    RISE SICS Västerås AB , Västerås , Sweden.
    Automated Functional Dependency Detection Between Test Cases Using Text Semantic Similarity2019In: 2019 IEEE International Conference On Artificial Intelligence Testing (AITest), 2019, p. 19-26, article id 8718215Conference paper (Other academic)
    Abstract [en]

    Knowing about dependencies and similarities between test cases is beneficial for prioritizing them for cost-effective test execution. This holds especially true for the time consuming, manual execution of integration test cases written in natural language. Test case dependencies are typically derived from requirements and design artifacts. However, such artifacts are not always available, and the derivation process can be very time-consuming. In this paper, we propose, apply and evaluate a novel approach that derives test cases' similarities and functional dependencies directly from the test specification documents written in natural language, without requiring any other data source. Our approach uses an implementation of Doc2Vec algorithm to detect text-semantic similarities between test cases and then groups them using two clustering algorithms HDBSCAN and FCM. The correlation between test case text-semantic similarities and their functional dependencies is evaluated in the context of an on-board train control system from Bombardier Transportation AB in Sweden. For this system, the dependencies between the test cases were previously derived and are compared to the results our approach. The results show that of the two evaluated clustering algorithms, HDBSCAN has better performance than FCM or a dummy classifier. The classification methods' results are of reasonable quality and especially useful from an industrial point of view. Finally, performing a random undersampling approach to correct the imbalanced data distribution results in an F1 Score of up to 75% when applying the HDBSCAN clustering algorithm.

  • 9.
    Tahvili, Sahar
    et al.
    RISE, SICS, Västerås, Sweden.
    Hatvani, Leo
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Felderer, Michael
    University of Innsbruck, Austria, Sweden.
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Saadatmand, Mehrdad
    RISE, SICS, Västerås, Sweden.
    Bohlin, Markus
    RISE, SICS, Västerås, Sweden.
    Cluster-Based Test Scheduling Strategies Using Semantic Relationships between Test Specifications2018In: 5th International Workshop on Requirements Engineering and Testing RET'18, 2018, Vol. F137811, p. 1-4Conference paper (Refereed)
    Abstract [en]

    One of the challenging issues in improving the test efficiency is that of achieving a balance between testing goals and testing resources. Test execution scheduling is one way of saving time and budget, where a set of test cases are grouped and tested at the same time. To have an optimal test execution schedule, all related information of a test case (e.g. execution time, functionality to be tested, dependency and similarity with other test cases) need to be analyzed. Test scheduling problem becomes more complicated at high-level testing, such as integration testing and especially in manual testing procedure. Test specifications at high-level are generally written in natural text by humans and usually contain ambiguity and uncertainty. Therefore, analyzing a test specification demands a strong learning algorithm. In this position paper, we propose a natural language processing (NLP) based approach that, given test specifications at the integration level, allows automatic detection of test cases’ semantic dependencies. The proposed approach utilizes the Doc2Vec algorithm and converts each test case into a vector in n-dimensional space. These vectors are then grouped using the HDBSCAN clustering algorithm into semantic clusters. Finally, a set of cluster-based test scheduling strategies are proposed for execution. The proposed approach has been applied in a sub-system from the railway domain by analyzing an ongoing testing project at Bombardier Transportation AB, Sweden.

1 - 9 of 9
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