Preface

DAMSS-2018 is the jubilee 10th international workshop on data analysis methods for software systems, organized in Druskininkai, Lithuania, at the end of the year. The same place and the same time every year. Ten years passed from the first workshop. History of the workshop starts from 2009 with 16 presentations. The idea of such workshop came up at the Institute of Mathematics and Informatics. Lithuanian Academy of Sciences and the Lithuanian Computer Society supported this idea. This idea got approval both in the Lithuanian research community and abroad. The number of this year presentations is 81. The number of registered participants is 113 from 13 countries. In 2010, the Institute of Mathematics and Informatics became a member of Vilnius University, the largest university of Lithuania. In 2017, the institute changes its name into the Institute of Data Science and Digital Technologies. This name reflects recent activities of the institute. The renewed institute has eight research groups: Cognitive Computing, Image and Signal Analysis, Cyber-Social Systems Engineering, Statistics and Probability, Global Optimization, Intelligent Technologies, Education Systems, Blockchain Technologies. The main goal of the workshop is to introduce the research undertaken at Lithuanian and foreign universities in the fields of data science and software engineering. Annual organization of the workshop allows the fast interchanging of new ideas among the research community. Even 11 companies supported the workshop this year. This means that the topics of the workshop are actual for business, too. Topics of the workshop cover big data, bioinformatics, data science, blockchain technologies, deep learning, digital technologies, high-performance computing, visualization methods for multidimensional data, machine learning, medical informatics, ontological engineering, optimization in data science, business rules, and software engineering. Seeking to facilitate relations between science and business, a special session and panel discussion is organized this year about topical business problems that may be solved together with the research community. This book gives an overview of all presentations of DAMSS-2018.DAMSS-2018 is the jubilee 10th international workshop on data analysis methods for software systems, organized in Druskininkai, Lithuania, at the end of the year. The same place and the same time every year. Ten years passed from the first workshop. History of the workshop starts from 2009 with 16 presentations. The idea of such workshop came up at the Institute of Mathematics and Informatics. Lithuanian Academy of Sciences and the Lithuanian Computer Society supported this idea. This idea got approval both in the Lithuanian research community and abroad. The number of this year presentations is 81. The number of registered participants is 113 from 13 countries. In 2010, the Institute of Mathematics and Informatics became a member of Vilnius University, the largest university of Lithuania. In 2017, the institute changes its name into the Institute of Data Science and Digital Technologies. This name reflects recent activities of the institute. The renewed institute has eight research groups: Cognitive Computing, Image and Signal Analysis, Cyber-Social Systems Engineering, Statistics and Probability, Global Optimization, Intelligent Technologies, Education Systems, Blockchain Technologies. The main goal of the workshop is to introduce the research undertaken at Lithuanian and foreign universities in the fields of data science and software engineering. Annual organization of the workshop allows the fast interchanging of new ideas among the research community. Even 11 companies supported the workshop this year. This means that the topics of the workshop are actual for business, too. Topics of the workshop cover big data, bioinformatics, data science, blockchain technologies, deep learning, digital technologies, high-performance computing, visualization methods for multidimensional data, machine learning, medical informatics, ontological engineering, optimization in data science, business rules, and software engineering. Seeking to facilitate relations between science and business, a special session and panel discussion is organized this year about topical business problems that may be solved together with the research community. This book gives an overview of all presentations of DAMSS-2018

Introducing the Game Design Matrix: A Step-by-Step Process for Creating Serious Games

The Game Design Matrix makes effective game design accessible to novice game designers. Serious Games are a powerful tool for educators seeking to boost the level of student engagement and application in academic environments, but the can be difficult to incorporate into existing courses due to availability and the cost of quality game design. The Game Design Matrix was used by two educators, novice game designers, to create a serious game. The games were assessed in an academic setting and observed to be effective in engagement, interaction, and achieving higher levels of learning

Mega-modeling of complex, distributed, heterogeneous CPS systems

Model-Driven Design (MDD) has proven to be a powerful technology to address the development of increasingly complex embedded systems. Beyond complexity itself, challenges come from the need to deal with parallelism and heterogeneity. System design must target different execution platforms with different OSs and HW resources, even bare-metal, support local and distributed systems, and integrate on top of these heterogeneous platforms multiple functional component coming from different sources (developed from scratch, legacy code and third-party code), with different behaviors operating under different models of computation and communication. Additionally, system optimization to improve performance, power consumption, cost, etc. requires analyzing huge lists of possible design solutions. Addressing these challenges require flexible design technologies able to support from a single-source model its architectural mapping to different computing resources, of different kind and in different platforms. Traditional MDD methods and tools typically rely on fixed elements, which makes difficult their integration under this variability. For example, it is unlikely to integrate in the same system legacy code with a third-party component. Usually some re-coding is required to enable such interconnection. This paper proposes a UML/MARTE system modeling methodology able to address the challenges mentioned above by improving flexibility and scalability. This approach is illustrated and demonstrated on a flight management system. The model is flexible enough to be adapted to different architectural solutions with a minimal effort by changing its underlying Model of Computation and Communication (MoCC). Being completely platform independent, from the same model it is possible to explore various solutions on different execution platforms.This work has been partially funded by the EU and the Spanish MICINN through the ECSEL MegaMart and Comp4Drones projects and the TEC2017-86722-C4-3-R PLATINO project

Developing Secure and Safe Systems with Knowledge Acquisition for Automated Specification

On spetsiaalsed tehnikad, mida kasutatakse riskihalduses nii turvalisuse kui ohutuse konstrueerimise domeenides. Nende tehnikate väljundid, mida tuntakse artefaktidena, on üksteisest eraldatud, mis toob kaasa mitmeid probleeme, kuna domeenid on sõltumatud ja ei ole domeeni, mis ühendaks neid mõlemat. Probleemi keskmes on see, et turvalisus- ja ohutusinsenerid töötavad erinevates meeskondades kogu süsteemiarenduse elutsükli jooksul, mille tulemusena riskid ja ohud on ebapiisavalt kaetud. Käesolevas magistritöös rakendatakse struktuurset lähenemist, turvalisuse ja ohutuse integreerimiseks läbi SaS (Safety and Security) domeeni mudeli loomise, mis integreerib neid mõlemaid. Lisaks töö käigus näidatakse, et on võimalik kasutada eesmärgipõhist KAOS (Knowledge Acquisition in autOmated Specification) keelt ohtude ja riskide analüüsiks, nii et kaetud saavad nii ohutus- kui ka turvadomeen, muutes nende väljundid e. artefaktid hästi struktureerituks, mille tulemusena toimub põhjalik analüüs ja suureneb usaldatavus. Me pakume välja lahenduse, mis sisaldab sellise domeeni mudeli loomist, milles on integreeritud ohtutuse ja turvalisuse domeenid. See annab parema võrdlus- ja integreerimisvõimaluse, leidmaks kahe domeeni vahelise kesktee ning ühendavad definitsioonid läbi nende kaardistamise üldises ontoloogias. Selline lahendus toob kokku turvalisuse ja ohutusedomeenide integratsiooni ühtsesse mudelisse, mille tulemusena tekib ohutus- ja turvalisustehnikate vahel vastastikune mõjustus ning toodab väljundeid, mida peetakse usaldusartefaktideks ning kasutab KAOSt domeeni mudeliga, mis on ehitatud juhtumianalüüsi põhjal. Peale vastloodud mudeli rakendumist viiakse läbi katse, milles analüüsitakse sedasama juhtumit, võrdlemaks selle tulemusi teiste juba olemasolevate mudelite tulemustega, et uurida sellise domeeni mõttekust. Struktureeritud lähenemine võib seega toimida liidesena, mis lihtsustab aktiivset interaktsiooni riski- ja ohuhalduses, aidates leida lahendusi probleemidele ja vastuoludele, mille lahendamiseks on vaja integreerida ohutuse ja turvalisuse domeenid ja kasutada unifitseeritud süsteemianalüüsi tehnikat, mille tulemusena tekib analüüsi tsentraalsus.There are special techniques languages that are used in risk management in both domains of safety engineering and security engineering. The outputs, known as artifacts, of these techniques are separated from each other leading to several difficulties due to the fact that domains are independent and that there is no one unifying domain for the two. The problem is that safety engineers and security engineers work in separated teams from throughout the system development life cycle, which results in incomplete coverage of risks and threats. The thesis applies a structured approach to integration between security and safety by creating a SaS (Safety and Security) domain model. Furthermore, it demonstrates that it is possible to use goal-oriented KAOS (Knowledge Acquisition in automated Specification) language in threat and hazard analysis to cover both safety and security domains making their outputs, or artifacts, well-structured and comprehensive, which results in dependability due to the comprehensiveness of the analysis. The structured approach can thereby act as an interface for active interactions in risk and hazard management in terms of universal coverage, finding solutions for differences and contradictions which can be overcome by integrating the safety and security domains and using a unified system analysis technique (KAOS) that will result in analysis centrality

Ontology in Information Security

The past several years we have witnessed that information has become the most precious asset, while protection and security of information is becoming an ever greater challenge due to the large amount of knowledge necessary for organizations to successfully withstand external threats and attacks. This knowledge collected from the domain of information security can be formally described by security ontologies. A large number of researchers during the last decade have dealt with this issue, and in this paper we have tried to identify, analyze and systematize the relevant papers published in scientific journals indexed in selected scientific databases, in period from 2004 to 2014. This paper gives a review of literature in the field of information security ontology and identifies a total of 52 papers systematized in three groups: general security ontologies (12 papers), specific security ontologies (32 papers) and theoretical works (8 papers). The papers were of different quality and level of detail and varied from presentations of simple conceptual ideas to sophisticated frameworks based on ontology

Comparison of Radio Frequency Distinct Native Attribute and Matched Filtering Techniques for Device Discrimination and Operation Identification

The research presented here provides a comparison of classification, verification, and computational time for three techniques used to analyze Unintentional Radio- Frequency (RF) Emissions (URE) from semiconductor devices for the purposes of device discrimination and operation identification. URE from ten MSP430F5529 16-bit microcontrollers were analyzed using: 1) RF Distinct Native Attribute (RFDNA) fingerprints paired with Multiple Discriminant Analysis/Maximum Likelihood (MDA/ML) classification, 2) RF-DNA fingerprints paired with Generalized Relevance Learning Vector Quantized-Improved (GRLVQI) classification, and 3) Time Domain (TD) signals paired with matched filtering. These techniques were considered for potential applications to detect counterfeit/Trojan hardware infiltrating supply chains and to defend against cyber attacks by monitoring executed operations of embedded systems in critical Supervisory Control And Data Acquisition (SCADA) networks

Software Components for Smart Industry Based on Microservices: A Case Study in pH Control Process for the Beverage Industry

[EN] Modern industries require constant adaptation to new trends. Thus, they seek greater flexibility and agility to cope with disruptions, as well as to solve needs or meet the demand for growth. Therefore, smart industrial applications require a lot of flexibility to be able to react more quickly to continuous market changes, offer more personalized products, increase operational efficiency, and achieve optimum operating points that integrate the entire value chain of a process. This requires the capture of new data that are subsequently processed at different levels of the hierarchy of automation processes, with requirements and technologies according to each level. The result is a new challenge related to the addition of new functionalities in the processes and the interoperability between them. This paper proposes a distributed computational component-based framework that integrates communication, computation, and storage resources and real-time capabilities through container technology, microservices, and the publish/subscribe paradigm, as well as contributing to the development and implementation of industrial automation applications by bridging the gap between generic architectures and physical realizations. The main idea is to enable plug-and-play software components, from predefined components with their interrelationships, to achieve industrial applications without losing or degrading the robustness from previous developments. This paper presents the process of design and implementation with the proposed framework through the implementation of a complex pH control process, ranging from the simulation part to its scaling and implementation to an industrial level, showing the plug-and-play assembly from a definition of components with their relationships to the implementation process with the respective technologies involved. The effectiveness of the proposed framework was experimentally verified in a real production process, showing that the results scaled to an industrial scale comply with the simulated design process. A qualitative comparison with traditional industrial implementations, based on the implementation requirements, was carried out. The implementation was developed in the beverage production plant "Punta Delicia", located in Colima, Mexico. Finally, the results showed that the platform provided a high-fidelity design, analysis, and testing environment for cyber information flow and their effect on the physical operation of the pH control.This work has been supported by for research cooperation between Universidad de Colima (Mexico), Universidad Autonoma de Occidente (Colombia), Universitat Politecnica de Valencia (Spain) and the juice production plant Punta Delicia located in Colima, Mexico.Serrano-Magaña, H.; González-Potes, A.; Ibarra-Junquera, V.; Balbastre, P.; Martínez-Castro, D.; Simó Ten, JE. (2021). Software Components for Smart Industry Based on Microservices: A Case Study in pH Control Process for the Beverage Industry. Electronics. 10(7):1-21. https://doi.org/10.3390/electronics1007076312110

Modeling 4.0: Conceptual Modeling in a Digital Era

Digitization provides entirely new affordances for our economies and societies. This leads to previously unseen design opportunities and complexities as systems and their boundaries are re-defined, creating a demand for appropriate methods to support design that caters to these new demands. Conceptual modeling is an established means for this, but it needs to be advanced to adequately depict the requirements of digitization. However, unlike the actual deployment of digital technologies in various industries, the domain of conceptual modeling itself has not yet undergone a comprehensive renewal in light of digitization. Therefore, inspired by the notion of Industry 4.0, an overarching concept for digital manufacturing, in this commentary paper, we propose Modeling 4.0 as the notion for conceptual modeling mechanisms in a digital environment. In total, 12 mechanisms of conceptual modeling are distinguished, providing ample guidance for academics and professionals interested in ensuring that modeling techniques and methods continue to fit contemporary and emerging requirements

Framework for the Integration of Mobile Device Features in PLM

Currently, companies have covered their business processes with stationary workstations while mobile business applications have limited relevance. Companies can cover their overall business processes more time-efficiently and cost-effectively when they integrate mobile users in workflows using mobile device features. The objective is a framework that can be used to model and control business applications for PLM processes using mobile device features to allow a totally new user experience