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Detta är en lärobok i grundläggande programmering. Den fokuserar på att lära ut det som är gemensamt för de flesta programmeringsspråk – de grundläggande elementen och programkonstruktionerna och hur dessa relaterar till varandra, oberoende av språket. Vilket språk programmet skrivs i måste vara underordnat den uppgift programmet skall lösa. Boken går därför igenom grunderna i strukturerad programmering och visar otaliga exempel i såväl flödesdiagram, strukturdiagram, pseudokod som i källkod. I slutet av boken finns kapitel som går igenom grunderna även i objektorienterad programmering.

Boken tonar ner inlärningen av ett specifikt programmeringsspråk, men i slutändan måste program ändå skrivas i något språk. Exemplen är skrivna i C# som har slagit igenom som ett praktiskt programmeringsspråk på mycket kort tid och redan börjat göra sitt intåg i högskolekurser i programmering.

I första hand är boken avsedd för nybörjare i programmering på högskolenivå, som vill lära sig programmeringens grunder.

Despite the general acceptance that software engineering datasets often contain noisy, irrele- vant or redundant variables, very few benchmark studies of feature subset selection (FSS) methods on real-life data from software projects have been conducted. This paper provides an empirical comparison of state-of-the-art FSS methods: information gain attribute ranking (IG); Relief (RLF); principal com- ponent analysis (PCA); correlation-based feature selection (CFS); consistency-based subset evaluation (CNS); wrapper subset evaluation (WRP); and an evolutionary computation method, genetic program- ming (GP), on five fault prediction datasets from the PROMISE data repository. For all the datasets, the area under the receiver operating characteristic curve—the AUC value averaged over 10-fold cross- validation runs—was calculated for each FSS method-dataset combination before and after FSS. Two diverse learning algorithms, C4.5 and na ??ve Bayes (NB) are used to test the attribute sets given by each FSS method. The results show that although there are no statistically significant differences between the AUC values for the different FSS methods for both C4.5 and NB, a smaller set of FSS methods (IG, RLF, GP) consistently select fewer attributes without degrading classification accuracy. We conclude that in general, FSS is beneficial as it helps improve classification accuracy of NB and C4.5. There is no single best FSS method for all datasets but IG, RLF and GP consistently select fewer attributes without degrading classification accuracy within statistically significant boundaries.

In enterprise-scale companies, where processing complex test results is often a time-consuming task for testers and developers, the need for an Application Programming Interface (API) testing visualization tool is vital. Furthermore, as various stakeholders require insights into the API testing results, a clear dashboard can facilitate effective communication among them. 

This thesis aims to fulfill the need for a generic API testing visualization tool within the mobile network industry through the implementation of TestUp, a user-friendly solution. TestUp simplifies the analysis of complex API test results for various stakeholders, including testers, developers, managers, and product owners. To accomplish the objectives of this thesis, an industrial case study was conducted at Nokia, beginning with a pre-study phase to explore industry needs and challenges. TestUp was designed based on the Agile methodology, evolving through feedback from industry and academia. Additionally, a post-tool questionnaire was employed to gather data on the tool’s effectiveness and limitations. Subsequently, the data analysis was conducted using the thematic analysis approach. 

The thesis demonstrates that TestUp provides valuable benefits to stakeholders by effectively addressing critical issues found in existing tools. TestUp is compatible with a range of test automation frameworks and serves as a user-friendly tool for visualizing test coverage. These facts fulfill the company's requirements. All in all, this thesis improves the analysing of API testing results within the mobile network management sector. Additionally, future work can involve enhancing the tool by adding extra features, such as export functionality and the ability to indicate timeout requests. Also, integrating TestUp with the continuous integration pipelines is a potential area for future work.

In this thesis work, our main goal is to improve IoT communications of an edge platform by selecting suitable solutions to work with the MQTT protocol. Our primary focus in this thesis is to investigate two quality attributes: data throughput and latency of message brokers.There are two research questions that are to be answered: how do protocols like MQTT and their architecture contribute to messaging in IoT communications? andHow to Enhance MQTT Architecture to Match the Requirements for ABB IoT Edge Platform?.  This thesis work comprises a mixed-methods research methodology that includes both quantitative and qualitative phases. The quantitative phase involves experimental work on examining data throughput and latency of a message broker, while the qualitative phase includes interviews with stakeholders and literature reviews. According to the qualitative and quantitative data, we found that event-driven architecture, publisher-subscriber design pattern, and NATS message broker are suitable choices to work with the MQTT-based architecture of IoT edge platforms. Since NATS showed a decent result in terms of high throughput and low latency in comparison to other message brokers. The results of this thesis work identify the best practices of message brokers in an MQTT-based IoT platform, for software architects, specifically the ABB IoT edge platform.

Software testing is a widely used quality assurance activity and often starts from the early development stages. However, starting early in the development process raises difficulties and challenges practitioners must deal with; most typically, hardware is not available in the required quantities, and there is the risk of damaging the hardware while testing. Emulating the physical hardware into virtual versions is a popular approach to overcome the mentioned obstacles. This master thesis, carried out at Westermo AB, investigates the differences between the physical and virtual hardware used for embedded system software testing and the possible benefits of combining both hardware versions in a hybrid system. Investigating differences between the hardware options helps identify which type of tests are more suitable in physical versus virtual hardware. The selected method for this thesis is a case study, starting with a pre-study phase investigating how other industries tackle the difficulties and challenges mentioned. Further, data were collected from two sources, historical test reports, and a questionnaire. The historical test reports showed a timing difference between virtual and physical hardware. The reset process of physical hardware is often faster than virtual hardware, but the link-up/link-down time is slower in physical hardware. The questionnaire also confirmed the timing differences as a significant challenge often experienced by engineers. Another challenge highlighted by the questionnaire answers is that "false positives" are typically caused by virtual hardware, where issues do not always turn up due to the virtual nature of communication. Another difference proven from this thesis is that virtual hardware is more failure-prone during the early stages of testing than physical hardware. The hybrid system could be advantageous in various ways, such as quantitatively expanding the current test systems and increasing test coverage. Future work could contribute with a proof-of-concept implementation of the hybrid system to confirm the advantages and demonstrate the third option of a test system. 

Testing plays a vital role in the software development life cycle by verifying and validating the software's quality. Since software testing is considered as an expensive activity and due to thelimitations of budget and resources, it is necessary to know the execution time of the test cases for an efficient planning of test-related activities such as test scheduling, prioritizing test cases and monitoring the test progress. In this thesis, an approach is proposed to predict and estimate the execution time of manual test cases written in English natural language. The method uses test specifications and historical data that are available from previously executed test cases. Our approach works by obtaining timing information from each and every step of previously executed test cases. The collected data is used to estimate the execution time for non-executed test cases by mapping them using text from their test specifications. Using natural language processing, texts are extracted from the test specification document and mapped with the obtained timing information. After estimating the time from this mapping, a linear regression analysis is used to predict the execution time of non-executed test cases. A case study has been conducted in Bombardier Transportation (BT) where the proposed method is implemented and the results are validated. The obtained results show that the predicted execution time of studied test cases are close to their actual execution time.

The Software Product Line (SPL) paradigm has proven to be an effective way to achieve large scale reuse in different domains. It takes advantage of common aspects between different products, while also considering product specific features. The architecture plays an important role in SPL engineering, by providing means to better understand and maintain the product-derivation environment. However, it is difficult to evolve such architecture because it is not always clear where and how to refactor. The contribution of this thesis is twofold. First, the current state of the art of software Product Line Architectures (PLAs) is investigated through a systematic mapping study. It provides an overview of the field through the analysis, and categorization of evidence. The study identifies gaps, trends and provides future directions for research. Furthermore, this thesis addresses the phenomenon of architectural bad smells in the context of SPLs. A case study provides an investigation on the implications of such structural properties in a variability-based environment. Prior to the search for smells, the architecture of a sample SPL in the text editor domain is recovered from the source code.

DCU2 (Drive Control Unit 2) is an important control system used in applications for train systems that are configured by a set of parameters. Traditionally, parameterization is conducted by using an excel workbook during the software development. The parameters are set up and further export the parameters to the compilation step. Such approach has a number of disadvantages, e.g., delays on the validation and verification steps, system configuration overhead, and suboptimal system reliability generated by the parameter configurations.

To improve the parameterization process, this thesis implements a model-based software architecture approach and automotive industry standards via rapid prototyping by using scrum methodology. We do this by using Matlab/Simulink, TDL (Time Description Language) and UML (Unified Modeling Language) architectural description languages to enable different views of the software architecture. We then develop different prototypes that implement ASAM (Association for Standardization of Automation and Measuring Systems) standards like XCP protocol over Ethernet (code ASAM MCD-1 XCP V1.1.0) and ASAP2 (code ASAM MCD-2 MC) in every scrum sprint. An evaluation then shows that the thesis successfully implements previously defined standards that use commercial tools from e.g., Vector, proving that the parameter‟s unit control can be handled via online calibration and measurement, leading to a significant improvement in Bombardier‟s software development process in a distributed development environment.

Internet of Things (IoT) has revolutionized transportation systems by connecting vehicles consequently enabling their tracking, as well as monitoring of driver activities. The IoT platform for most vehicles typically consists of 1) an on-board system consisting of the communication unit, sensors and a set of ECU’s that are interconnected using a CAN network, 2) an off-board system consisting of the applications deployed on the servers (e.g., cloud) that processes the data send by the communication unit over the internet, and 3) mobile devices like a mobile phone or a computer that communicates with the on-board and off-board systems. Such an IoT platform requires a significant amount of data to be send from the on-board system to the off-board servers, contributing to high network usage. There are two main architectural paradigms for sending data: 1) interval based architecture, in which data is send at regular intervals and 2) event based architecture, in which data is send whenever relevant events occur. Currently, (e.g., at Scania), the data is being send at regular intervals, i.e., using an interval based approach. In this case, data is send even if it is not relevant for reporting leading to a wastage of network resources, e.g., when the data does not change considerably compared to the previously sent value. Sending data in an event-based manner, when the data is relevant for reporting, e.g., changes significantly, reduces the network usage when compared to the interval based approach.  In this thesis, we investigate the possibility of using an event based architecture to send data from the on-board system to the off-board system in order to reduce network usage and improve the accuracy of the data available off-board. We first propose an event based architecture for data transfer in the context of Internet of vehicles. We then implement a simulator to evaluate our proposed architecture for the specific case of position data. Finally, we perform extensive experiments varying different parameters and compare, for example, average message size per minute and average off-board error distance. The results show that our event based architecture improves the accuracy of data available at the off-board system, by a careful selection of events. Moreover, we found that our event based architecture significantly decreases the frequency of sending messages, particularly during highway driving, leading to reduced average data transfer rates. Our results enable a customer to perform trade-offs between accuracy and data transfer rates. Future work will aim at implementing the event based architecture on a real platform as well as investigating the possibility of using the event based architecture for more accurate prediction by incorporating additional details such as the final destination of the vehicle and odometer values.

During the last three decades, automation in software development has gone mainstream. Software development teams strive to automate as much of the software development activ-ities as possible, spanning requirements specification, system modeling, code generation, testing, deployment, verification, as well as release phases, project status reporting and system maintenance. Automation helps to reduce development time and cost, as well as to concentrate know ledge by bringing quality into every step of the development process. 

Software systems that are embedded in autonomous Cyber-Physical Systems (CPSs) usually have a large life-cycle, both during its development and in maintenance. This software evolves during its life-cycle in order to incorporate new requirements, bug fixes, and to deal with hardware obsolescence. The current process for developing and maintaining this software is very fragmented, which makes developing new software versions and deploying them in the CPSs extremely expensive. In other domains, such as web engineering, the phases of development and operation are tightly connected, making it possible to easily perform software updates of the system, and to obtain operational data that can be analyzed by engineers at development time. However, in spite of the rise of new communication technologies (e.g., 5G) providing an opportunity to acquire Design-Operation Continuum Engineering methods in the context of CPSs, there are still many complex issues that need to be addressed, such as the ones related with hardware-software co-design. Therefore, the process of Design-Operation Continuum Engineering for CPSs requires substantial changes with respect to the current fragmented software development process. In this paper, we build a taxonomy for Design-Operation Continuum Engineering of CPSs based on case studies from two different industrial domains involving CPSs (elevation and railway). This taxonomy is later used to elicit requirements from these two case studies in order to present a blueprint on adopting Design-Operation Continuum Engineering in any organization developing CPSs.

An essential aspect of resilience within Cyber-Physical Systems stands in their capacity of early detection of faults before they generate failures. Faults can be of any origin, either natural or intentional. Detection of faults enables predictive maintenance, where faults are managed through diagnosis and prognosis. In this paper we focus on intelligent predictive maintenance based on a class of machine learning techniques, namely transfer learning, which overcomes some limitations of traditional approaches in terms of availability of appropriate training datasets and discrepancy of data distribution. We provide a conceptual approach and a reference architecture supporting transfer learning within intelligent predictive maintenance applications for cyber-physical systems. The approach is based on the emerging paradigms of Industry 4.0, the industrial Internet of Things, and Digital Twins hosting run-time models for providing the training data set for the target domain. Although we mainly focus on health monitoring and prognostics of industrial machinery as a reference application, the general approach is suitable to both physical- and cyber-threat detection, and to any combination of them within the same system, or even in complex systems-of-systems such as critical infrastructures. We show how transfer learning can aid predictive maintenance with intelligent fault detection, diagnosis and prognosis, and describe some the challenges that need to be addressed for its effective adoption in real industrial applications.

Selecting sourcing options for software assets and components is an important process that helps companies to gain and keep their competitive advantage. The sourcing options include: in-house, COTS, open source and outsourcing. The objective of this paper is to further refine, extend and validate a solution presented in our previous work. The refinement includes a set of decision-making activities, which are described in the form of a process-line that can be used by decision-makers to build their specific decision-making process. We conducted five case studies in three companies to validate the coverage of the set of decision-making activities. The solution in our previous work was validated in two cases in the first two companies. In the validation, it was observed that no activity in the proposed set was perceived to be missing, although not all activities were conducted and the activities that were conducted were not executed in a specific order. Therefore, the refinement of the solution into a process-line approach increases the flexibility and hence it is better in capturing the differences in the decision-making processes observed in the case studies. The applicability of the process-line was then validated in three case studies in a third company. 

Software testing is a crucial activity when it comes to the software lifecycle as it can say with a certain confidence that the software will behave according to its specified behavior. However, due to the large input space, it is almost impossible to check all the combinations that might possibly lead to failures. Input partitioning and combinatorial testing are two techniques that can partially solve the test creation and selection problem, by minimizing the number of test cases to be executed. These techniques work closely together, with input partitioning providing a selection of values that are more likely to expose software faults, and combinatorial testing generating all the possible combinations between two to six parameters. The aim of this Thesis is to study how exactly input partitioning impacts combinatorial test coverage, in terms of the measured t-way coverage percentage and the number of missing test cases to achieve full t-way coverage. For this purpose, six manually written test suites were provided by Bombardier Transportation. We performed an experiment, where the combinatorial coverage is measured for four systematic strategies of input partitioning, using a tool called Combinatorial Coverage Measurement (CCM) tool. The strategies are based on the interface documentations, where we can partition using information about data types or predefined partitions, and specification documentations, where we can partition while using Boundary Value Analysis (BVA) or not. The results show that input partitioning affects the combinatorial test coverage through two factors, the number of partitions or intervals and the number of representative values per interval. A high number of values will lead to a higher number of combinations that increases exponentially. The strategy based on specifications without considering BVA always scored the highest coverage per test suite ranging between 22% and 67% , in comparison to the strategy with predefined partitions that almost always had the lowest score ranging from 4% to 41%. The strategy based on the data types was consistent in always having the second highest score when it came to combinatorial coverage ranging from 8% to 56%, while the strategy that considers BVA would vary, strongly depending on the number of non-boolean parameters and their respective number of boundary values, ranging from 3% to 41%. In our study, there were also some other factors that affected the combinatorial coverage such as the number of manually created test cases, data types of the parameters and their values present in the test suites. In conclusion, an input partitioning strategy must be chosen carefully to exercise parts of the system that can potentially result in the discovery of an unintended behavior. At the same time, a test engineer should also consider the number of chosen values. Different strategies can generate different combinations, and thus influencing the obtained combinatorial coverage. Tools that automate the generation of the combinations are adviced to achieve 100% combinatorial coverage.

Well-trained software development personnel, in the art and science of software testing, will effectively and efficiently develop quality software products with potentially fewer, less-critical defects. Thus software testing education is considered to be an important part of curricula for a university degree in Computer Science or Information Systems. The objective of this paper is to determine how much dedicated knowledge in the field of software testing is taught within Swedish universities. To achieve this objective, a systematic search of syllabi for software testing-related courses was done. From 25 Swedish universities offering Computer Science (or related) degrees, 14 currently offer dedicated courses in software testing. Some findings include: 32% of the individual courses were offered at the undergraduate level; 28% of the universities offer courses for specialised testing training; and, for the vast majority of the universities, dedicated software testing courses account for about 5% of the total degree credits. While some universities fare better than others, the overall state of academic software testing education in Sweden is limited but promising.

[Context and Motivation] Requirements in tender documents are often mixed with other supporting information. Identifying requirements in large tender documents could aid the bidding process and help estimate the risk associated with the project. [Question/problem] Manual identification of requirements in large documents is a resource-intensive activity that is prone to human error and limits scalability. This study compares various state-of-the-art approaches for requirements identification in an industrial context. For generalizability, we also present an evaluation on a real-world public dataset. [Principal ideas/results] We formulate the requirement identification problem as a binary text classification problem. Various state-of-the-art classifiers based on traditional machine learning, deep learning, and few-shot learning are evaluated for requirements identification based on accuracy, precision, recall, and F1 score. Results from the evaluation show that the transformer-based BERT classifier performs the best, with an average F1 score of 0.82 and 0.87 on industrial and public datasets, respectively. Our results also confirm that few-shot classifiers can achieve comparable results with an average F1 score of 0.76 on significantly lower samples, i.e., only 20% of the data. [Contribution] There is little empirical evidence on the use of large language models and few-shots classifiers for requirements identification. This paper fills this gap by presenting an industrial empirical evaluation of the state-of-the-art approaches for requirements identification in large tender documents. We also provide a running tool and a replication package for further experimentation to support future research in this area.

The increasing use of software and connectivity in modern vehicles has made cybersecurity an important issue in the automotive industry. ISO 21434 is a standard for automotive cybersecurity engineering that provides guidelines for the development and validation of secure automotive systems. For effective implementation and practical use of ISO 21434, it must be incorporated into existing automotive industry development workflows.

In this paper, we investigate the practical applicability of ISO 21434 in the context of the Security Abstraction Model (SAM), a security modeling approach for the domain-specific modeling language EAST-ADL, and provide insights into the benefits and consequences of this approach. In doing so, we describe the methodological opportunities of integrating ISO 21434 into SAM on the one hand and present a case study illustrating the application of this integrated approach in the development of a secure automotive system on the other hand. Our results suggest that the integration of ISO 21434 into SAM better supports automotive system security in the early development phases and makes it transparent to a wide range of stakeholders. At the same time, it becomes clear that a representation of the interrelationships in the form of a metamodel, in contrast to ISO 21434 in which these are only described textually, significantly improves conceptual understanding and ultimately enables pragmatic usability in industrial development.

Security cannot be implemented into a system retrospectively without considerable effort, so security must be takeninto consideration already at the beginning of the system development. The engineering of automotive softwareis by no means an exception to this rule. For addressing automotive security, the AUTOSAR and EAST-ADLstandards for domain-specific system and component modeling provide the central foundation as a start. The EASTADLextension SAM enables fully integrated security modeling for traditional feature-targeted attacks. Due to theCOVID-19 pandemic, the number of cyber-attacks has increased tremendously and of these, about 98 percent arebased on social engineering attacks. These social engineering attacks exploit vulnerabilities in human behaviors,rather than vulnerabilities in a system, to inflict damage. And these social engineering attacks also play a relevantbut nonetheless regularly neglected role for automotive software. The contribution of this paper is a novel modelingconcept for social engineering attacks and their criticality assessment integrated into a general automotive softwaresecurity modeling approach. This makes it possible to relate social engineering exploits with feature-related attacks.To elevate the practical usage, we implemented an integration of this concept into the established, domain-specificmodeling tool MetaEdit+. The tool support enables collaboration between stakeholders, calculates vulnerabilityscores, and enables the specification of security objectives and measures to eliminate vulnerabilities.

Development of reliable systems requires that safety and security concerns are acknowledged during system development. Adding them afterwards is risky as many concerns are missed if not elicited together with the system requirements. Unfortunately, languages for systems engineering, like SysML, typically ignore security and safety forcing development teams to split the work into different formats, languages and tools without easy collaboration, with limited traceability, separate versioning and restricted use of automation that tools can provide. We present a model-based approach targeting automotive that integrates safety and security aspects with other system development practices. This is achieved via a comprehensive domain-specific modeling language that is extendable by language users. We demonstrate this approach with practical examples on how security and safety concerns are recognized along with traditional system design and analysis phases.

Usability Supporting Architectural Patterns (USAP) has already introduced a concept in software architecture for coping usability issues in better style and revealing its obscured dimensions. A support is also needed to develop the safety systems in such a way that they employ the same rules and get a better understanding of safety, its requirements and the architecture. A way to determine safety requirements from the patterns and working with the responsibilities of patterns was the aim for this thesis report. On the other hand, a useful tool with the name “ArchWiz” was to be developed further from its prototypical form-an assisting tool for architects to look for requirements and evaluation of their architecture. The mature development of ArchWiz tool, and incorporating the safety perspective with respect to USAP vogue was also the goal of the thesis.

In a development process, architecture designing is a crucial and vital part of software system. During architecture designing process very first decisions and information are gained to validate if the system has the potential to meet its requirements and intended behaviours. Along with other important quality attributes, safety architecture has played an important role in developing today’s critical software and automated systems. These safety issues especially in software architecture are to protect, recover, discover and mitigate the hazards, faults, failures and catastrophic perils. The deficiency and obscurity of these inherent dangers can be reduced by understanding the safety in general and analysing its requirements from unseen perspectives. Later, these requirements can be traced into the architecture of a similar system as a knowledge base or experience gained.

Architectural patterns and their investigation in safety provide a broad horizon for requirement and solution in various aspects. They help to bring out the requirements in refined way and in general manners too. The report, therefore, presents the suggestion to formalize the suggestions in safety with respect to requirement engineering in architectural context as well as reusable solution for these issues; alike in USAP style.

Kadesjös Ingenjörsbyrå AB, ett konsultföretag inom bygg- och VVS-sektorn med ca 50 anställda, använder ett egenskrivet BASIC program i DOS för beräkning av grundfundament i betong med grundsula och plintskaft avseende stabilitet och erforderlig armering. I dagsläget finns det ungefär 10 användare av programmet.

Några kända problem med programmet är att varje dator måste konfigureras manuellt med kommandopromptens NET USE kommando. Detta för att en anslutning av nätverksskrivaren till den lokala porten LPT1 måste finnas för att utskriften ska fungera. Dessutom kan varken indata eller resultat från ett fundament sparas.

Detta examensarbete behandlar arbetet för att konvertera det äldre DOS programmet till ett modernare fönsterbaserat programspråk med möjlighet att kunna spara fundamenten för respektive projekt.

In several types of embedded systems the applications are deployed both as software and as hardware components. For such systems, the partitioning decision is highly important since the implementation in software or hardware heavily influences the system properties. In the industry, it is rather common practice to take deployment decisions in an early stage of the design phase and based on a limited number of aspects. Often such decisions are taken based on hardware and software designers‟ expertise and do not account the requirements of the entire system and the project and business development constraints. This approach leads to several disadvantages such as redesign, interruption, etc. In this scenario, we see the need of approaching the partitioning process from a multiple decision perspective. As a consequence, we start by presenting an analysis of the most important and popular Multiple Criteria Decision Analysis (MCDA) methods and tools. We also identify the key requirements on the partitioning process. Subsequently, we evaluate all of the MCDA methods and tools with respect to the key partitioning requirements. By using the key partitioning requirements the methods and tools that the best suits the partitioning are selected. Finally, we propose two MCDA-based partitioning processes and validate their feasibility thorough an industrial case study.

Considering the ubiquitousness of software in modern vehicles, its increased value and development cost, an efficient software development became of paramount importance for the vehicular domain. It has been identified that early verification of non functional properties of  vehicular embedded software such as, timing, reliability and safety, is crucial to efficiency. However, early verification of non functional properties is hard to achieve with traditional software development approaches due to the abstraction and the lack of automation of these methodologies.

This doctoral thesis aims at improving efficiency in vehicular embedded software development by minimising the need for late, expensive and time consuming software modifications with early design changes, identified through timing verification, which usually are cheaper and faster. To this end, we introduce a novel model-driven approach which exploits the interplay of two automotive-specific modelling languages for the representation of functional and execution models and defines a suite of model transformations for their automatic integration.

Starting from a functional model (expressed by means of EAST-ADL), all the execution models (expressed by means of the Rubus Component Model) entailing unique timing configurations are derived. Schedulability analysis selects the set of the feasible execution models with respect to specified timing requirements. Eventually, a reference to the selected execution models along with their analysis results is automatically created in the related functional model to allow the engineer to investigate them.

The main scientific contributions of this doctoral thesis are i) a metamodel definition for the Rubus Component Model, ii) an automatic mechanism for the generation of Rubus models from EAST-ADL, iii) an automatic mechanism for the selection and back-propagation of the analysis results and related Rubus models to design level and iv) a compact notation for visualising the selected Rubus models by means of a single execution model.

In 2014, a new software development approach started to get a foothold: low-code development. Already from its early days, practitioners in software engineering have been showing a rapidly growing interest in low-code development. In 2021 only, the revenue of low-code development technologies reached 13.8 billion USD. Moreover, the business success of low-code development has been sided by a growing interest from the software engineering research community. The model-driven engineering community has shown a particular interest in low-code development due to certain similarities between the two. In this article, we report on the planning, execution, and results of a multi-vocal systematic review on low-code development, with special focus to its relation to model-driven engineering. The review is intended to provide a structured and comprehensive snapshot of low-code development in its peak of inflated expectations technology adoption phase. From an initial set of potentially relevant 720 peer-reviewed publications and 199 grey literature sources, we selected 58 primary studies, which we analysed according to a meticulous data extraction, analysis, and synthesis process. Based on our results, we tend to frame low-code development as a set of methods and/or tools in the context of a broader methodology, often being identified as model-driven engineering.

Software architectures are pivotal in the success of software-intensive systems and serve as foundational elements that significantly impact the overall software quality. Reference architectures abstract software elements, define main responsibilities and interactions within a domain, and guide the architectural design of new systems. Using reference architectures offers advantages like enhanced interoperability, cost reduction through reusability, decreased project risks, improved communication, and adherence to best practices. However, these benefits are most pronounced when software architectures align with reference architectures. Deviations from prescribed reference architectures can nullify these benefits. Uncontrolled misalignment can become prohibitively expensive, necessitating costly redevelopments, with maintenance costs reaching up to 90% of development costs. Conformance-checking processes and identifying and resolving violations in the software architecture are essential to mitigate misalignment. To address these challenges, we introduce the concept of continuous conformance that is expressed as a distance function, together with a process supporting it. Continuous conformance quantifies the degree to which a software architecture adheres to a designated reference architecture. The conformance concept enables multi-level, incremental, and non-blocking checking and restoration tasks and allows the check of partial architectures without obstructing the design process. We operationalize this process through an assistive modeling tool to architect an Internet of things-based system. 

Reference architectures (RAs) are successfully used to represent families of concrete software architectures in several domains such as automotive, banking, and the Internet of Things. RAs inspire architects when designing concrete architectures, and they help to guarantee compliance with architectural decisions, regulatory requirements, as well as architectural qualities. Despite their importance, reference architectures still suffer from a number of open technical issues, including (i) the lack of a common interpretation, a precise notation for their representation and documentation, and (ii) the lack of conformance mechanisms for checking the compliance of concrete architectures to their related reference architecture, architectural decisions, regulatory requirements, etc. This paper addresses these two issues by introducing a model-driven approach that leverages (i) a domain-independent metamodel for the representation of reference architectures and (ii) the combination of model transformation and weaving techniques for the automatic conformance checking of concrete architectures. We evaluate the applicability, effectiveness, and generalizability of our approach using illustrative examples from the web browsers and automotive domains, including an assessment from an independent practitioner.

Modern real-time data-intensive systems generate large amounts of data that are processed using complex data-related computations such as data aggregation. In order to maintain logical data consistency and temporal correctness of the computations, one solution is to model the latter as transactions and manage them using a Real-Time Database Management System (RTDBMS). Ideally, depending on the particular system, the transactions are customized with the desired logical and temporal correctness properties, which should be enforced by the customized RTDBMS via appropriate transaction management mechanisms. However, developing such a data management solution with high assurance is not easy, partly due to inadequate support for systematic specification and analysis during the design. Firstly, designers do not have means to identify the characteristics of the computations, especially data aggregation, and to reason about their implications. Design flaws might not be discovered early enough, and thus they may propagate to the implementation. Secondly, meeting more properties simultaneously might not be possible, so trading-off the less critical ones for the critical one, for instance, temporal correctness, is sometimes required. Nevertheless, trade-off analysis of conflicting properties, such as transaction atomicity, isolation and temporal correctness, is mainly performed ad-hoc, which increases the risk of unpredictable behavior.

In this thesis, we address the above problems by showing how to systematically design and provide assurance of transaction-based data management with data aggregation support, customized for real-time systems. We propose a design process as our methodology for the systematic design and analysis of the trade-offs between desired properties, which is facilitated by a series of modeling and analysis techniques. Our design process consists of three major steps as follows: (i) Specifying the data-related computations, as well as the logical data consistency and temporal correctness properties, from system requirements, (ii) Selecting the appropriate transaction models to model the computations, and deciding the corresponding transaction management mechanisms that can guarantee the properties, via formal analysis, and, (iii) Generating the customized RTDBMS with the proved transaction management mechanisms, via configuration or implementation. In order to support the first step of our process, we propose a taxonomy of data aggregation processes for identifying their common and variable characteristics, based on which their inter-dependencies can be captured, and the consequent design implications can be reasoned about. Tool support is provided to check the consistency of the data aggregation design specifications. To specify transaction atomicity, isolation and temporal correctness, as well as the transaction management mechanisms, we also propose a Unified Modeling Language (UML) profile with explicit support for these elements. The second step of our process relies on the systematic analysis of trade-offs between transaction atomicity, isolation and temporal correctness. To achieve this, we propose two formal frameworks for modeling transactions with abort recovery, concurrency control, and scheduling. The first framework UPPCART utilizes timed automata as the underlying formalism, based on which the desired properties can be verified by model checking. The second framework UPPCART-SMC models the system as stochastic timed automata, which allows for probabilistic analysis of the properties for large complex RTDBMS using statistical model checking. The encoding of high-level UTRAN specifications into corresponding formal models is supported by tool automation, which we also propose in this thesis. The applicability and usefulness of our proposed techniques are validated via several industrial use cases focusing on real-time data management.

The development of autonomous Mobile Robot Systems is attracting nowadays more and moreinterest from both researchers and practitioners, mainly because they may open for a wide rangeof improvements for quality of life. Mobile robots are systems capable of accomplishing missionsby moving in an unknown environment without human supervision. Throughout mechanisms ofdetection, communication and adaptation, they can adapt their behavior according to changes ofthe environment. Individual robots can even join teams of autonomous mobile robots that, throughindividual tasks, accomplish common missions. These are called Mobile Multi-Robot Systems andare meant to perform missions that a single robot would not be able to carry out by itself.When it comes to the development of Mobile Robot Systems, currently there is no standard methodology.This is mainly due to the complexity of the domain and the variety of di↵erent platformsthat are available on the market. A promising methodology that recently has gained attention insoftware industry for its ability of mitigating complexity and boosting platform-independence, isModel-Driven Engineering.This thesis proposes a systematic mapping study on the state-of-the-art of Model-Driven Engineeringfor Mobile Robot Systems. Through our contribution, researchers can get a picture of theactual trends and open challenges for further research, while practitioners can realize the suitabilityof Model-Driven Engineering by checking to what extent it has been applied to real-world projects.

Industries have adopted a standardized set of practices for developing their products. In the automotive domain, the provision of safety-compliant systems is guided by ISO 26262, a standard that specifies a set of requirements and recommendations for developing automotive safety-critical systems. For being in compliance with ISO 26262, the safety lifecycle proposed by the standard must be included in the development process of a vehicle. Besides, a safety case that shows that the system is acceptably safe has to be provided. The provision of a safety case implies the execution of a precise documentation process. This process makes sure that the work products are available and traceable. Further, the documentation management is defined in the standard as a mandatory activity and guidelines are proposed/imposed for its elaboration. It would be appropriate to point out that a well-documented safety lifecycle will provide the necessary inputs for the generation of an ISO 26262-compliant safety case. The OSLC (Open Services for Lifecycle Collaboration) standard and the maturing stack of semantic web technologies represent a promising integration platform for enabling semantic interoperability between the tools involved in the safety lifecycle. Tools for requirements, architecture, development management, among others, are expected to interact and shared data with the help of domains specifications created in OSLC.This thesis proposes the creation of an OSLC tool-chain infrastructure for sharing safety-related information, where fragments of safety information can be generated. The steps carried out during the elaboration of this master thesis consist in the identification, representation, and shaping of the RDF resources needed for the creation of a safety case. The focus of the thesis is limited to a tiny portion of the ISO 26262 left-hand side of the V-model, more exactly part 6 clause 8 of the standard:  Software unit design and implementation. Regardless of the use of a restricted portion of the standard during the execution of this thesis, the findings can be extended to other parts, and the conclusions can be generalize.This master thesis is considered one of the first steps towards the provision of an OSLC-based and ISO 26262-compliant methodological approach for representing and shaping the work products resulting from the execution of the safety lifecycle, documentation required in the conformation of an ISO-compliant safety case.

Manual compliance with process-based standards is time-consuming and prone-to-error. No ready-to-use solution is currently available for increasing efficiency and confidence. In our previous work, we have presented our automated compliance checking vision to support the process engineer’s work. This vision includes the creation of a process model, given by using a SPEM 2.0 (Systems & Software Process Engineering Metamodel)-reference implementation, to be checked by Regorous, a compliance checker used in the business context. In this paper, we move a step further for the concretization of our vision by defining the transformation, necessary to automatically generate the models required by Regorous. Then, we apply our transformation to a small portion of the design phase recommended in the rail sector. Finally, we discuss our findings, and present conclusions and future work. 

Designing modern Cyber-Physical Systems (CPSs) is posing new challenges to both industrial practitioners and academics. In this context, adopting cutting-edge paradigms, such as Model-Based Systems Engineering (MBSE), DevOps, and Artificial Intelligence (AI), can offer new opportunities for improving CPS design automation. While such paradigms are already jointly used in the research community to support system design activities, there is a need to fill the gap between academia and industrial practitioners. Indeed, system specification is still mainly performed manually in many industrial projects. In this paper, we present a collaboration between industrial and academic partners of the AIDOaRt European project towards a model-based approach for CPS engineering applied in one of the project use cases. We identify key challenges and corresponding solutions to enhance the automation of CPS design processes. Notably, we consider a combination of prescriptive modeling, model transformations, model views, modeling process mining, and AI-based modeling recommendations. As an initial evaluation, the proposed approach is applied to a practical industrial case study.

In the Systems Engineering (SE) domain there has been a paradigm shift from document-based to model-based system development artefacts; in fact, new methodologies are emerging to meet the increasing complexity of current systems and the corresponding growing need of digital workflows. In this regard, Model-Based Systems Engineering (MBSE) is considered as a key enabler by many central players of the SE community. MBSE has reached an adequate level of maturity and there exist documented success stories in its adoption in industry. In particular, one significant benefit of utilising MBSE when compared to the traditional manual and document-centric workflows is that models are available from early phases of systems development; these enable a multitude of analyses prior any implementation effort together with other relevant capabilities, like the automation of development tasks. Nonetheless, it is noticeable there is a lack of a common understanding for how formal analyses for the verification and validation (V&V) of systems behaviour, specifically in the early phases of development, could be placed in an MBSE setting.

In this article, we report on the planning, execution, and results of a systematic literature review regarding the early V&V of systems behaviour in the context of model-based systems engineering. The review aims to provide a structured representation of the state-of-the-art with respect to motivations, proposed solutions, and limitations. From an initial set of potentially relevant 701 peer-reviewed publications we selected 149 primary studies, which we analysed according to a rigorous data extraction, analysis, and synthesis process. Based on our results, early V&V has usually the goal of checking the quality of a system design to avoid discovering flaws when parts are being concretely realised; SysML is a de facto standard for describing the system under study, while the solutions for the analyses tend to be varied; also V&V analyses tend to target varied properties with a slight predominance of functional concerns, and following the variation mentioned so far the proposed solutions are largely context specific; the proposed approaches are usually presented without explicit limitations, while when limitations are discussed, readiness of the solutions, handling of analyses simplifications/assumptions, and languages/tools integration are among the most frequently mentioned issues.

Based on the survey results and the standard SE practices, we discuss how the current state-of-the-art MBSE supports early V&V of systems behaviour with a special focus on industrial adoption, and identify relevant challenges to be researched further.

Cyber-physical systems (CPSs) are increasing in developmental complexity. Several emerging technologies, such as Model-based engineering, DevOps, and Artificial intelligence, are expected to alleviate the associated complexity by introducing more advanced capabilities. The AIDOaRt research project investigates how the aforementioned technologies can assist in developing complex CPSs in various industrial use cases. In this paper, we discuss the experiences of industry and academia collaborating to improve the development of complex CPSs through the experiences in the research project. In particular, the paper presents the results of two working groups that examined the challenges of developing complex CPSs from an industrial and academic perspective when considering the previously mentioned technologies. We present five identified challenge areas from developing complex CPSs and discuss them from the perspective of industry and academia: data, modeling, requirements engineering, continuous software and system engineering, as well as intelligence and automation. Furthermore, we highlight practical experience in collaboration from the project via two explicit use cases and connect them to the challenge areas. Finally, we discuss some lessons learned through the collaborations, which might foster future collaborative efforts. 

Model-Based Systems Engineering (MBSE) has emerged as a de facto standard practice for complex systems development. However, despite standard frameworks, methods, and tools, the MBSE practices in industrial contexts are far from mature. This is particularly true for traditionally hardware-intensive industrial systems and complex products such as heavy construction machinery. This paper outlines a light-weight MBSE methodology developed within the construction equipment domain. The approach is based on customizing a general MBSE methodology, such as RFLP, guided by a core ontology for architecture modeling. The ontology defines the main architecture concepts and corresponding modeling views to develop an architecture baseline for the corresponding system model. The initial architecture baseline is developed bottom-up instead of a traditional top-down approach. As we demonstrate in this paper, the minimalist approach paves the way for faster deployment of MBSE in industrial contexts with low modeling experience and legacy development silos across electronics, software, and hardware domains.

Society 5.0 is a visionary project aimed at creating sustainable smart societies, which relies on advanced computer science and software engineering techniques. Hence, software engineering plays a critical role in enabling Society 5.0 by providing the necessary technological advances and practices to address societal issues. This paper presents a systematic mapping study that focuses on identifying the key software engineering technologies and challenges that are critical for achieving the goals of Society 5.0. The study begins with an initial set of 1646 peer-reviewed publications, from which a final set of 29 primary studies was selected through a rigorous selection process. The selected studies were subjected to meticulous data extraction, analysis, and synthesis. The primary studies identified 13 software engineering technologies that act as enablers of Society 5.0. However, the application of these technologies also comes with technical challenges. The selected primary studies identified ten software engineering open challenges that hamper the realisation of Society 5.0. The findings of this study have important implications for software engineering researchers and practitioners involved in developing sustainable smart societies. The identification of the key technologies and challenges in Society 5.0 can help guide future research and development efforts in this field. 

Making a decision today is quite important, especially in companies, where the consequences can bring benefits or costs. Sometimes the decisions to be made are complex and we need to evaluate many criterions that can involve several factors. In those cases, it is not easy to have a good overview of all choices and for this reason it is important to have a system that helps us in making complex decisions, when it is not possible to evaluate all the alternatives manually. This thesis describes different algorithms and tools that can aid in the process of making decisions. Based on the review of existing tools a new web based application is proposed. The new tool, Decision Maker, uses both the full Analytical Hierarchical Process approach and Chainwise Paired Comparisons method to evaluate different alternatives.

In order for model-driven engineering to succeed, automated code generation from models through model transformations has to guarantee that extra-functional properties modelled at design level are preserved at code level. A full round-trip engineering approach could be needed in order to evaluate quality attributes of the embedded system by code execution monitoring/analysis tools and then provide backpropagation of the target code analysis results to modelling level. In this way, properties that can only be estimated statically are evaluated against runtime values and this consequently allows to optimize the design models for ensuring preservation of analysed extra-functional aspects. This paper presents an approach to support the whole round-trip process starting from the generation of source code for a target platform, passing through the monitoring of selected system quality attributes at code level, and nishing with the back-propagation of measured values to modelling level. The technique is validated against an industrial casestudy in the telecommunications applicative domain.

Model-driven and component-based software engineering have been widely recognized as promising paradigms for development of a wide range of systems. Moreover, in the embedded real-time domain, their combination is believed to be helpful in handling the ever-increasing complexity of such systems design.However, in order for these paradigms and their combination to definitely break through at an industrial level for development of embedded real-time systems, both functional and extra-functional properties need to be addressed at each level of abstraction.

This research focuses on the preservation of extra-functional properties. More specifically, the aim is to provide support for easing such preservation throughout the entire development process at different abstraction levels.The main outcome of the research work is a round-trip engineering approach aiding the preservation of extra-functional properties by providing code generators, supporting monitoring and analysis of code execution, and then enabling back-propagation of the results to modelling level. In this way, properties that can only be roughly estimated statically are evaluated against runtime values and this consequently allows to optimize the design models for ensuring preservation of analysed extra-functional properties.

Moreover, a solution for managing evolution of computational context in which extra-functional properties are defined by means of validity analysis is provided. Such solution introduces a new language for the description of the computational context in which a given property is provided and/or computed by some analysis, enables detection of changes performed to the context description, and analyses the possible impacts on the extra-functional property values based on a precise representation of differences between previous and current version of the model.

Thanks to continuous advances in both software and hardware technologies the power of modern embedded systems is ever increasing along with their complexity. Among the others, Model-Driven Engineering has grown consideration for mitigating this complexity through its ability to shift the focus of the development from hand-written code to models from which correct-by-construction implementation is automatically generated. However, the path towards correctness-by-construction is often twisted by the inability of current MDE approaches to preserve certain extra-functional properties such as CPU and memory usage, execution time and power consumption. With SMARTCore we address open challenges, described in this paper together with an overview of possible solutions, in modelling, generating code from models, and exploiting back-propagated extra-functional properties observed at runtime for deployment optimisation of embedded systems on multicore. SMARTCore brings together world leading competence in software engineering, model-driven engineering for embedded systems (Mälardalen University), and market leading expertise in the development of these systems in different business areas (ABB Corporate Research, Ericsson AB, Alten Sweden AB).

The main goal of this thesis is to investigate efficient searching mechanisms for searching and retrieving software components across different remote repositories and implement a supporting prototype called “Component Repository Browser” using the plug-in based Eclipse technology for PROGRESS-IDE. The prototype enables users to search the ProCom components and to import the desired components from a remote repository server over different protocols such as HTTP, HTTPS, and/or SVN. Several component searching mechanisms and suggestions were studied and examined such as keyword, facet-based search, folksonomy classification, and signature matching, from which we selected keyword search along with facet-based searching technique to help component searchers to efficiently find the desired components from a remote repository.

This thesis work is a comparative study of technical features between three distinctivemethods for database access. A web store which offers software components to download,for registered users has been built with three different database access methods to drawcomparisons.

1. SQL Server 2005 with stored procedures

2. LINQ to SQL

3. Db4o

Working in Visual Studio with three different methods for database access was not difficult.SQL Server with Stored procedures is efficient in performance and offers maintainability ofthe database access logic. LINQ to SQL makes queries to database as first-class languageconstruct providing type-safety and Intellisense. LINQ to SQL has relatively lowperformance compared to Stored procedures because of the translation of LINQ queries toSQL Queries to communicate with the database. Db4o solves the problem of impedancemismatch and making the development of Database model much simpler and similar to theapplication domain model. Although Db4o has its own drawbacks with database size andconcurrency. Db4o can be considered as an alternative to Relational Database ManagementSystems. Db4o works particularly well with applications which have a small data footprint.

During the last decade the gap between software modeling and performancemodeling has been closing. For example, UML annotations have been developed to enable the transformation of UML software models to performance models, thereby making performance modeling more accessible. However, as of yet few of these tools are ready for industrial application. In this thesis we explorer the current state of performance modeling tooling, the selection of a performance modeling tool for industrial application is described and a performance modeling case study on one of ABB's remote diagnostics systems (RDS) is presented. The case study shows the search for the best architectural alternative during a multi-million dollar redesign project of the ASP.Net web services based RDS back-end. The performance model is integrated with a cost model to provide valuable decision support for the construction of an architectural roadmap. Despite our success we suggest that the stability of software performance modeling tooling and the semantic gap between performance modeling and software architecture concepts are major hurdles to widespread industrial adaptation. Future work may use the experiences recorded in this thesis to continue improvement of performance modeling processes and tools for industrial use.

The electronics in automotive systems give great possibilities. It has contributed to environmental improvements through reduced emissions and reduced fuel consumption, safety, driver assistance, and quality through better diagnostic capabilities.

Automotive systems are today distributed embedded systems that consist of several nodes that communicate with each other. The increasing possibilities have led to a situation where functions that used to be stand-alone, are today dependent on several inter-connected systems which all contribute to the desired functionality. This has increased the costs and the complexity to deal with the systems.

The automotive industry is adopting a new open software architecture, called AUTOSAR, that is intended to reduce the complexity. AUTOSAR also gives possibilities for coping with large product ranges and for component sharing. The introduction of AUTOSAR is an example of an architecture change without modifying the external functionality. We have chosen to call such changes system refactoring.

However, if the introduction of AUTOSAR is not successfully performed, there are risks for delayed development projects, which are costly for the automotive companies. Unfortunately, existing engineering standards and literature focus mostly on new product development and less on system re-factoring, and this gap needs to be filled. The goal of this research is to provide guidelines for refactoring, which provides support throughout the complete process of system architects in efforts to refactor the system.

This thesis identifies the characteristics of refactoring processes. This is done by empirical studies of the drivers behind refactoring, the effects we can expect from refactoring, and the process activities and characteristics. The result can be used to create guidelines for improving the work of refactoring.