This thesis describes the AP1 system, which serves as a platform for model-based CASE technology. AP1 is a set of libraries and tools that support different activities in the software development process. It provides different layers of reusable CASE functionality, and thus facilitates CASE tool development and integration. Some key problems of software development are addressed, such as the storage and management of artifacts, their creation and modification, and the generation of program code. The main parts of the abstract platform are a typed repository for models and model data, and a generic editor that acts as an integrated software development environment (IDE). The former enables data integration; the latter serves as a basis for presentation integration. Both parts have an extensible and customizable architecture that makes it possible for developers to adapt the system to their own individual needs. The thesis discusses different data models, explaining why the parsimonious data model was chosen for the repository. A mapping onto the relational data model is given that makes it possible to leverage a RDBMS for data management. On top of the RDBMS, the AP1 system implements new mechanisms for caching, event notification and change control, resulting in a unique architecture. The thesis introduces novel concepts of robustness and reflection for user interfaces, and delineates their implementation in the generic editor. Furthermore, a concept for code generators is presented that offers a particularly high degree of type-safety, which we call generator type-safety.

This thesis describes the AP1 system, which serves as a platform for model-based CASE technology. AP1 is a set of libraries and tools that support different activities in the software development process. It provides different layers of reusable CASE functionality, and thus facilitates CASE tool development and integration. Some key problems of software development are addressed, such as the storage and management of artifacts, their creation and modification, and the generation of program code. The main parts of the abstract platform are a typed repository for models and model data, and a generic editor that acts as an integrated software development environment (IDE). The former enables data integration; the latter serves as a basis for presentation integration. Both parts have an extensible and customizable architecture that makes it possible for developers to adapt the system to their own individual needs. The thesis discusses different data models, explaining why the parsimonious data model was chosen for the repository. A mapping onto the relational data model is given that makes it possible to leverage a RDBMS for data management. On top of the RDBMS, the AP1 system implements new mechanisms for caching, event notification and change control, resulting in a unique architecture. The thesis introduces novel concepts of robustness and reflection for user interfaces, and delineates their implementation in the generic editor. Furthermore, a concept for code generators is presented that offers a particularly high degree of type-safety, which we call generator type-safety.

This dissertation supports human decision-making with a Model-Based Systems Engineering methodology enabling engineering analysis, and in particular Operations Research analysis of discrete-event logistics systems, to be more widely used in a cost-effective and correct manner. A methodology is a collection of related processes, methods, and tools, and the process of interest is posing a question about a system model and then identifying and building answering analysis models. Methods and tools are the novelty of this dissertation, which when applied to the process will enable the dissertation's goal. One method which directly enables the goal is adding automation to analysis model-building. Another method is abstraction, to make explicit a frequently-used bridge to analysis and also expose analysis model-building repetition to justify automation. A third method is formalization, to capture knowledge for reuse and also enable automation without human interpreters. The methodology, which is itself a contribution, also includes two supporting tool contributions. A tool to support the abstraction method is a definition of a token-flow network, an abstract concept which generalizes many aspects of discrete-event logistics systems and underlies many analyses of them. Another tool to support the formalization method is a definition of a well-formed question, the result of an initial study of semantics, categories, and patterns in questions about models which induce engineering analysis. This is more general than queries about models in any specific modeling language, and also more general than queries answerable by navigating through a model and retrieving recorded information. A final contribution follows from investigating tools for the automation method. Analysis model-building is a model-to-model transformation, and languages and tools for model-to-model transformation already exist in Model-Driven Architecture of software. The contribution considers if and how these tools can be re-purposed by contrasting software object-oriented code generation and engineering analysis model-building. It is argued that both use cases share a common transformation paradigm but executed at different relative levels of abstraction, and the argument is supported by showing how several Operations Research analyses can be defined in an object-oriented way across multiple layered instance-of abstraction levels. Enabling Operations Research analysis of discrete-event logistics systems to be more widely used in a cost-effective and correct manner requires considering fundamental questions about what knowledge is required to answer a question about a system, how to formally capture that knowledge, and what that capture enables. Developments here are promising, but provide only limited answers and leave much room for future work.

Testing is the dominant technique for quality assurance of software systems. It typically consumes considerable resources in development projects, and is often performed in an ad hoc manner. This thesis is concerned with model-based testing, which is an approach to make testing more systematic and more automated. The general idea in model-based testing is to start from a formal model, which captures the intended behavior of the software system to be tested. On the basis of this model, test cases can be generated in a systematic way. Since the model is formal, the generation of test suites can be automated and with adequate tool support one can automatically quantify to which degree they exercise the tested software. Despite the significant improvements on model-based testing in the last 20 years, acceptance by industry has so far been limited. A number of commercially available tools exist, but still most testing in industry relies on manually constructed test cases. This thesis address this problem by presenting a methodology and associated tool support, which is intended to be used for model-based testing of communication protocol implementations in industry. A major goal was to make the developed tool suitable for industrial usage, implying that we had to consider several problems that typically are not addressed by the literature on model-based testing. The thesis presents several technical contributions to the area of model-based testing, including - a new specification language based on the functional programming language Erlang, - a novel technique for specifying coverage criteria for test suite generation, and - a technique for automatically generating test suites. Based on these developments, we have implemented a complete tool chain that generates and executes complete test suites, given a model in our specification language. The thesis also presents a substantial industrial case study, where our technical contributions and the implemented tool chain are evaluated. Findings from the case study include that test suites generated using (model) coverage criteria have at least as good fault-detection capability as equally large random test suites, and that model-based testing could discover faults in previously well-tested software where previous testing had employed a relaxed validation of requirements.

The powertrain design and control strategies for three representative hybrid and plug-in hybrid electric vehicles (HEV/PHEVs), a plug-in hybrid passenger car, a plug-in hybrid race car, and a hybrid electric mining truck, have been investigated through the system modeling, simulation and design optimization. First, the pre-transmission gen-set couple Plug-in Series-Parallel Multi-Regime (SPMR) powertrain architecture was selected for PHEV passenger car. Rule-based load following control schemes based on engine optimal control strategy and Equivalent Consumption Minimization Strategy (ECMS) were used for the operation control of the passenger car PHEV powertrain. Secondly, the rear wheel drive (RWD) post-transmission parallel through road powertrain architecture was selected for race car PHEV. A high level supervisory control system and ECMS control strategy have been developed and implemented through the race car’s on-board embedded controller using dSPACE MicroAutobox II. In addition, longitudinal adaptive traction control has been added to the vehicle controller for improved drivability and acceleration performance. At last, the feasibility and benefits of powertrain hybridization for heavy-duty mining truck have been investigated, and three hybrid powertrain architectures, series, parallel and diesel-electric, with weight adjusting propulsion system have been modeled and studied. The research explored the common and distinct characteristics of hybrid electric propulsion system technology for different vehicular applications, and formed the foundation for further research and development. / Graduate / 0540 / ruicheng@uvic.ca

Retrofits of hydraulic and mechanical deep drawing presses often stop with the exchange of the electrical and the hydraulic parts. But that is only half the job. The use of high definition control electronics, faster CPUs and more dynamic hydraulic actuators, offers the opportunity of redesigning the already existing control concepts of the press. In this paper we present how the performance of the press, i.e. the control quality, can be increased for hydraulic ram and cushion axes. The improvement in control quality is achieved through the use of intelligent closed-loop and open-loopcontrol algorithms. Therefore, creasing and crack formation can be reduced, since enhancements in control quality have direct influence on the quality of the forming process. Results will be shown for hydraulic drawing cushion control, i.e. pressure control, as well as for hydraulic ram control, i.e. position, velocity and parallelism control. We present findings for hydraulic cushion control of a mechanical press type Arisa S-4-1600-470-230-LDE (link-drive press with 10 hydraulic cushions) and for ram- / cushion-control of hydraulic press type Müller-Weingarten ZE2100 (multi-curve press with 8-point cushion).

In the intensive care units, hyperglycaemia among the critically ill is associated with poor outcomes. Many studies have been done on managing hyperglycaemia in the critically ill. Patients in the ICU continue to benefit from the outcome of extensive studies including several randomized clinical trials on glycaemic control with intensive insulin therapy. Tight glycaemic control has now emerged as a major research focus in critical care due to its potential to simultaneously reduce both mortality and cost. Although the debate on tight glycaemic control is on going, managing glycaemic level in ICUs is gaining widespread acceptance as the adverse effects are well known. However, in the less acute wards, to date there have only been a single randomized, controlled study to examine the benefit of glycaemic control. Patients in the less acute wards do not receive the same level of care, as glycaemic control is not regarded as important and not a priority. Glycaemic goals in the less acute wards are often judged based on clinical experience rather than adhering to a standard protocol or a treatment guideline. It is important that patients in the less acute wards received the level of care as practised in the ICU. If hyperglycaemia worsens outcome in the ICU, a similar effect is seen within less acute wards. Hence, tight glycaemic control needs to be extended in the less critical setting as well. To support the establishment of a control protocol for patients in less acute wards, a method that has been successful in the critical care and can be adapted to the less acute wards, is the model based or model-derived control protocol. Model-based protocol can deliver a safe and effective patient-specific control, which means the glycaemic control protocol can be devised to each individual patient. Hence, a physiological model that represents the glucose-insulin regulatory system is presented in this thesis. The developed model, Intensive Control Insulin-Nutrition-Glucose (ICING) is based on the best aspects of two previous clinically-validated glucose-insulin models.

Acute Respiratory Distress Syndrome (ARDS) is associated with lung inflammation and fluid filling, resulting in a stiffer lung with reduced intrapulmonary gas volume. ARDS patients are admitted to the Intensive Care Unit (ICU) and require Mechanical Ventilation (MV) for breathing support. Positive End Expiratory Pressure (PEEP) is applied to aid recovery by improving gas exchange and maintaining recruited lung volume. However, high PEEP risks further lung injury due to overstretching of healthy lung units, and low PEEP risks further lung injury due to the repetitive opening and closing of lung units. Thus, selecting PEEP is a balance between avoiding over-stretching and repetitive opening of alveoli. Furthermore, specific protocols to determine optimal PEEP do not currently exist, resulting in variable PEEP selection. Thus, ensuring an optimal PEEP would have significant impact on patient mortality, and the cost and duration of MV therapy. Two important metrics that can be used to aid MV therapy are the elastance of the lungs as a function of PEEP, and the quantity of recruited lung volume as a function of PEEP. This thesis describes several models and model-based methods that can be used to select optimal PEEP in the ICU. Firstly, a single compartment lung model is investigated for its ability to capture the respiratory mechanics of a mechanically ventilated ARDS patient. This model is then expanded upon, leading to a novel method of mapping and visualising dynamic respiratory system elastance. Considering how elastance changes, both within a breath and throughout the course of care, provides a new clinical perspective. Next, a model using only the expiratory portion of the breathing cycle is developed and presented, providing an alternative means to track changes in disease state throughout MV therapy. Finally, four model-based methods are compared based on their capability of estimating the quantity of recruited lung volume due to PEEP. The models and model-based methods described in this thesis enable rapid parameter identification from readily available clinical data, providing a means of tracking lung condition and selecting optimal patient-specific PEEP. Each model is validated using data from clinical ICU patients and/or experimental ARDS animal models.

A case study for the tool LBTest illustrating benets and limitations of the tool along the terms of usability, results and costs. The study shows the use of learning based testing on a safety critical application in the avionics industry. While requiring the user to have the oretical knowledge of the tools inner workings, the process of using the tool has benefits in terms of requirement analysis and the possibility of finding design and implementation errors in both the early and late stages of development

There is a growing amount of digital information available from Open-Data initiatives, Internet-of-Things technologies, and web APIs in general. At the same time, an increasing amount of technology in our lives is creating a desire to take advantage of the generated data for personal or professional interests. Building interactive applications that would address this desire is challenging since it requires advanced engineering skills that are normally reserved for professional software developers. However, more and more interactive applications are prototyped outside of enterprise environments, in more opportunistic settings. For example, knowledge workers apply end-user development techniques to solve their tasks, or groups of friends get together for a weekend hackathon in the hope of becoming the next big startup. This thesis focuses on how to design prototyping tools that support opportunistic development of interactive applications that take advantage of the growing amount of available data. In particular, the goal of this thesis is to understand what are the current challenges of prototyping with data and to identify important qualities of tools addressing these challenges. To accomplish this, declarative development tools were explored, while keeping focus on what data and interaction the application should afford rather than on how they should be implemented (programmed). The work presented in this thesis was carried out as an iterative process which started with a design exploration of Model-based UI Development, followed by observations of prototyping practices through a series of hackathon events and an iterative design of Endev – a prototyping tool for data-driven web applications. Formative evaluations of Endev were conducted with programmers and interaction designers.  The main results of this thesis are the identified challenges for prototyping with data and the key qualities required of prototyping tools that aim to address these challenges. The identified key qualities that lower the threshold for prototyping with data are: declarative prototyping, familiar and setup-free environment, and support tools. Qualities that raise the ceiling for what can be prototyped are: support for heterogeneous data and for advanced look and feel. / Mer och mer digital information görs tillgänglig på olika sätt, t.ex. via öppna data-initiativ, Sakernas internet och API:er. Med en ökande teknikanvändning så skapas även ett intresse för att använda denna data i olika sammanhang, både privat och professionellt. Att bygga interaktiva applikationer som adresserar dessa intressen är en utmaning då det kräver avancerade ingenjörskunskaper, vilket man vanligtvis endast hittar hos professionella programmerare. Sam­tidigt byggs allt fler interaktiva applikationer utanför företagsmiljöer, i mer opportunistiska sammanhang. Detta kan till exempel vara kunskapsarbetare som använder sig av s.k. anveckling (eng. end-user development) för att lösa en uppgift, eller kompisar som träffas en helg för att hålla ett hackaton med hopp om att bli nästa framgångsrika startup-företag. Den här avhandlingen fokuserar på hur prototypverktyg kan utformas för att stödja utveckling av interaktiva applikationer i sådana opportunistiska sammanhang, som utnyttjar den ökande mängden av tillgänglig data. Målet med arbetet som presenteras i den här avhandlingen har varit att förstå utmaningarna som det innebär att använda data i prototyparbete och att identifiera viktiga kvalitéer för de verktyg som ska kunna hantera detta. För att uppnå detta mål har verktyg för deklarativ programmering utforskats med ett fokus kring vilken data och interaktion en applikationen ska erbjuda snarare än hur den ska implementeras. Arbetet som presenteras i den här avhandlingen har genomförts som en iterativ process, med en startpunkt i en utforskning av modellbaserad gränssnittsutveckling, vilket sedan följdes av observationer av prototyparbete i praktiken genom en serie hackathon och en iterativ design av Endev, som är ett prototypverktyg för att skapa datadrivna webbapplikationer. Formativa utvärderingar av Endev har utförts med programmerare och interaktionsdesigners. De viktigaste resultaten av den här avhandlingen är de utmaningar som har identifierats kring hur man skapar prototyper och de kvalitéer som krävs av prototypverktyg som ska adressera dessa utmaningar. De identifierade kvalitéerna som sänker trösklarna för att inkludera data i prototyper är: deklarativt prototyparbete, välbekanta och installationsfria miljöer, och supportverktyg. Kvalitéer som höjer taket för vad som kan göras i en prototyp är: stöd för olika typer av data och för avancerad “look and feel”.