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  • 1.
    Al Mamun, Abdullah
    et al.
    Division of Software Engineering Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.
    Berger, Christian
    Division of Software Engineering Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.
    Hansson, Jörgen
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Explicating, Understanding and Managing Technical Debt from Self-Driving Miniature Car Projects2014In: Proceedings 2014 6th IEEE International Workshop on Managing Technical Debt: MTD 2014, Los Alamitos, CA: IEEE Computer Society, 2014, p. 11-18Conference paper (Refereed)
    Abstract [en]

    Technical debt refers to various weaknesses in the design or implementation of a system resulting from trade-offs during software development usually for a quick release. Accumulating such debt over time without reducing it can seriously hamper the reusability and maintainability of the software. The aim of this study is to understand the state of the technical debt in the development of self-driving miniature cars so that proper actions can be planned to reduce the debt to have more reusable and maintainable software. A case study on a selected feature from two self-driving miniature car development projects is performed to assess the technical debt. Additionally, an interview study is conducted involving the developers to relate the findings of the case study with the possible root causes. The result of the study indicates that "the lack of knowledge" is not the primary reason for the accumulation of technical debt from the selected code smells. The root causes are rather in factors like time pressure followed by issues related to software/hardware integration and incomplete refactoring as well as reuse of legacy, third party, or open source code.

  • 2.
    Atif, Yacine
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lindström, Birgitta
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jeusfeld, Manfred
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Andler, Sten F.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Yuning, Jiang
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Brax, Christoffer
    CombiTech AB, Skövde, Sweden.
    Gustavsson, Per M.
    CombiTech AB, Skövde, Sweden.
    Cyber-Threat Intelligence Architecture for Smart-Grid Critical Infrastructures Protection2017Conference paper (Refereed)
    Abstract [en]

    Critical infrastructures (CIs) are becoming increasingly sophisticated with embedded cyber-physical systems (CPSs) that provide managerial automation and autonomic controls. Yet these advances expose CI components to new cyber-threats, leading to a chain of dysfunctionalities with catastrophic socio-economical implications. We propose a comprehensive architectural model to support the development of incident management tools that provide situation-awareness and cyber-threats intelligence for CI protection, with a special focus on smart-grid CI. The goal is to unleash forensic data from CPS-based CIs to perform some predictive analytics. In doing so, we use some AI (Artificial Intelligence) paradigms for both data collection, threat detection, and cascade-effects prediction. 

  • 3.
    Jiang, Yuning
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Multi-Level Vulnerability Modeling of Cyber-Physical Systems2018Conference paper (Refereed)
    Abstract [en]

    Vulnerability is defined as ”weakness of an asset or control that can be exploited by a threat” according to ISO/IEC 27000:2009, and it is a vital cyber-security issue to protect cyber-physical systems (CPSs) employed in a range of critical infrastructures (CIs). However, how to quantify both individual and system vulnerability are still not clear. In our proposed poster, we suggest a new procedure to evaluate CPS vulnerability. We reveal a vulnerability-tree model to support the evaluation of CPS-wide vulnerability index, driven by a hierarchy of vulnerability-scenarios resulting synchronously or propagated by tandem vulnerabilities throughout CPS architecture, and that could be exploited by threat agents. Multiple vulnerabilities are linked by boolean operations at each level of the tree. Lower-level vulnerabilities in the tree structure can be exploited by threat agents in order to reach parent vulnerabilities with increasing CPS criticality impacts. At the asset-level, we suggest a novel fuzzy-logic based valuation of vulnerability along standard metrics. Both the procedure and fuzzy-based approach are discussed and illustrated through SCADA-based smart power-grid system as a case study in the poster, with our goal to streamline the process of vulnerability computation at both asset and CPS levels.

  • 4.
    Jiang, Yuning
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jeusfeld, Manfred
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Andler, Sten
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lindström, Birgitta
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Brax, Christoffer
    Combitech, Sweden.
    Haglund, Daniel
    Combitech, Sweden.
    Complex Dependencies Analysis: Technical Description of Complex Dependencies in Critical Infrastructures, i.e. Smart Grids. Work Package 2.1 of the ELVIRA Project2018Report (Other academic)
    Abstract [en]

    This document reports a technical description of ELVIRA project results obtained as part of Work-package 2.1 entitled “Complex Dependencies Analysis”. In this technical report, we review attempts in recent researches where connections are regarded as influencing factors to  IT systems monitoring critical infrastructure, based on which potential dependencies and resulting disturbances are identified and categorized. Each kind of dependence has been discussed based on our own entity based model. Among those dependencies, logical and functional connections have been analysed with more details on modelling and simulation techniques.

  • 5.
    Laurell, Isak
    et al.
    University of Skövde, School of Engineering Science.
    Sjöholm, Linus
    University of Skövde, School of Engineering Science.
    System för insamling av väderdata2017Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
    Abstract [sv]

    På försvarets materielverk (FMV) i Karlsborg utförs prover av militära vapensystem. Ofta när prov genomförs samlas också väderdata in för att veta om yttre faktorer kan påverka en träffbild. Insamling av väderdata är en manuell process som FMV önskar att automatisera. Målet är att skapa ett system med hjälp av en befintlig vädersensor som kan visa väderparametrar i realtid på en skärm samt spara dem vid rätt tillfälle på ett flyttbart media. Vid utveckling av system för insamling av väderdata ska det väljas ut lämplig hårdvara där även mjukvaran ska formas. Den teoretiska referensramen och litteraturstudierna utgjorde en bra grund för hela projektet genom att få en förståelse om alla de delar som måste tas hänsyn till. FMV har som krav att hårdvaran ska vara baserad på en integrerad krets. Det innebär kortfattat att det inte finns något operativsystem utan att det består endast av en källkod. Den befintliga vädersensorn som ska användas kommunicerar via seriell kommunikation. Det gjordes också ett val mellan två utvecklingsmodeller där en av dem senare ska användas som ett hjälpmedel för utvecklingsprocessen av hela systemet. Den utvecklingsmodell som var mest lämplig för projektet var V-modellen. Genom att använda V-modellen togs det fram en bra struktur för hur arbetet skulle läggas upp gällande planering, verkställande och testning. Med en detaljerad planering underlättade det verkställandet genom att det fanns en tydlig bild av vad som skulle göras. Den noga planeringen gjorde att fel och brister i systemet vid testerna var få. En nyckelfaktor för utvecklingsprocessen var också att ha ett bra samarbete med FMV:s personal vilket gjorde att utvecklingen följde deras vision om systemet. När utvecklingsprocessen och arbetet med V-modellen var genomfört var också ett system för insamling av väderdata framtaget och godkänt av FMV. Systemet generar en minskad hantering av data eftersom det utför det arbete som tidigare har varit manuellt. Det generar också stabilare mätvärden eftersom tidpunkten för loggningen blir mer exakt än tidigare.

  • 6.
    Liebel, Grischa
    et al.
    Software Engineering Division, Chalmers / University of Gothenburg, Sweden.
    Marko, Nadja
    Virtual Vehicle Research Center, Graz, Austria.
    Tichy, Matthias
    Software Engineering Division, Chalmers / University of Gothenburg, Sweden.
    Leitner, Andrea
    Virtual Vehicle Research Center, Graz, Austria.
    Hansson, Jörgen
    University of Skövde, School of Informatics.
    Assessing the state-of-practice of model-based engineering in the embedded systems domain2014In: Model-Driven Engineering Languages and Systems: 17th International Conference, MODELS 2014, Valencia, Spain, September 28 – October 3, 2014. Proceedings / [ed] Juergen Dingel, Wolfram Schulte, Isidro Ramos, Silvia Abrahão, Emilio Insfran, Springer, 2014, p. 166-182Conference paper (Refereed)
    Abstract [en]

    Abstract Model-Based Engineering (MBE) aims at increasing the effectiveness of engineering by using models as key artifacts in the development process. While empirical studies on the use and the effects of MBE in industry exist, there is only little work targeting the embedded systems domain. We contribute to the body of knowledge with a study on the use and the assessment of MBE in that particular domain. We collected quantitative data from 112 subjects, mostly professionals working with MBE, with the goal to assess the ...

  • 7.
    Mellin, Jonas
    University of Skövde, The Informatics Research Centre. University of Skövde, School of Informatics.
    The effect of optimizing engine control on fuel consumption and roll amplitude in ocean-going vessels: An experimental study2015Report (Other academic)
    Abstract [en]

    We use data-generated models based on data from experiments of an ocean-going vessel to study the effect of optimizing fuel consumption. The optimization is an add-on module to the existing diesel-engine fuel-injection control built by Q-TAGG R&D AB. The work is mainly a validation of knowledge-based models based on a priori knowledge from physics. The results from a simulation-based analysis of the predictive models built on data agree with the results based on knowledge-based models in a companion study. This indicates that the optimization algorithm saves fuel. We also address specific problems of adapting data to existing machine learning methods. It turns out that we can simplify the problem by ignoring the auto-correlative effects in the time series by employing low-pass filters and resampling techniques. Thereby we can use mature and robust classification techniques with less requirements on the data to demonstrate that fuel is saved compared to the full-fledged time series analysis techniques which are harder to use. The trade-off is the accuracy of the result, that is, it is hard to tell exactly how much fuel is saved. In essence, however, this process can be automated due to its simplicity. 

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