Högskolan i Skövde

Chatbots are mainly data-driven and usually based on utterances that might be sensitive. However, training deep learning models on shared data can violate user privacy. Such issues have commonly existed in chatbots since their inception. In the literature, there have been many approaches to deal with privacy, such as differential privacy and secure multi-party computation, but most of them need to have access to users' data. In this context, Federated Learning (FL) aims to protect data privacy through distributed learning methods that keep the data in its location. This paper presents Fedbot, a proof-of-concept (POC) privacy-preserving chatbot that leverages large-scale customer support data. The POC combines Deep Bidirectional Transformer models and federated learning algorithms to protect customer data privacy during collaborative model training. The results of the proof-of-concept showcase the potential for privacy-preserving chatbots to transform the customer support industry by delivering personalized and efficient customer service that meets data privacy regulations and legal requirements. Furthermore, the system is specifically designed to improve its performance and accuracy over time by leveraging its ability to learn from previous interactions.

Background: The increasing up-trend of software size brings about challenges related to release planning and maintainability. Foreseeing the growth of software metrics can assist in taking proactive decisions regarding different areas where software metrics play vital roles. For example, source code metrics are used to automatically calculate technical debt related to code quality which may indicate how maintainable a software is. Thus, predicting such metrics can give us an indication of technical debt in the future releases of software. Objective: Estimation or prediction of software metrics can be performed more meaningfully if the relationships between different domains of metrics and relationships between the metrics and different domains are well understood. To understand such relationships, this empirical study has collected 25 metrics classified into four domains from 9572 software revisions of 20 open source projects from 8 well-known companies. Results: We found software size related metrics are most correlated among themselves and with metrics from other domains. Complexity and documentation related metrics are more correlated with size metrics than themselves. Metrics in the duplications domain are observed to be more correlated to themselves on a domain-level. However, a metric to domain level relationship exploration reveals that metrics with most strong correlations are in fact connected to size metrics. The Overall correlation ranking of duplication metrics are least among all domains and metrics. Contribution: Knowledge earned from this research will help to understand inherent relationships between metrics and domains. This knowledge together with metric-level relationships will allow building better predictive models for software code metrics. © 2017 Association for Computing Machinery.

Context

Software metrics play a significant role in many areas in the life-cycle of software including forecasting defects and foretelling stories regarding maintenance, cost, etc. through predictive analysis. Many studies have found code metrics correlated to each other at such a high level that such correlated code metrics are considered redundant, which implies it is enough to keep track of a single metric from a list of highly correlated metrics.

Objective

Software is developed incrementally over a period. Traditionally, code metrics are measured cumulatively as cumulative sum or running sum. When a code metric is measured based on the values from individual revisions or commits without consolidating values from past revisions, indicating the natural development of software, this study identifies such a type of measure as organic. Density and average are two other ways of measuring metrics. This empirical study focuses on whether measurement types influence correlations of code metrics.

Method

To investigate the objective, this empirical study has collected 24 code metrics classified into four categories, according to the measurement types of the metrics, from 11,874 software revisions (i.e., commits) of 21 open source projects from eight well-known organizations. Kendall’s τ -B is used for computing correlations. To determine whether there is a significant difference between cumulative and organic metrics, Mann-Whitney U test, Wilcoxon signed rank test, and paired-samples sign test are performed.

Results

The cumulative metrics are found to be highly correlated to each other with an average coefficient of 0.79. For corresponding organic metrics, it is 0.49. When individual correlation coefficients between these two measure types are compared, correlations between organic metrics are found to be significantly lower (with p <0.01) than cumulative metrics. Our results indicate that the cumulative nature of metrics makes them highly correlated, implying cumulative measurement is a major source of collinearity between cumulative metrics. Another interesting observation is that correlations between metrics from different categories are weak.

Conclusions

Results of this study reveal that measurement types may have a significant impact on the correlations of code metrics and that transforming metrics into a different type can give us metrics with low collinearity. These findings provide us a simple understanding how feature transformation to a different measurement type can produce new non-collinear input features for predictive models.

Context: Technical debt is known to impact maintainability of software. As source code files grow in size, maintainability becomes more challenging. Therefore, it is expected that the density of technical debt in larger files would be reduced for the sake of maintainability. Objective: This exploratory study investigates whether a newly introduced metric ‘technical debt density trend’ helps to better understand and explain the evolution of technical debt. The ‘technical debt density trend’ metric is the slope of the line of two successive ‘technical debt density’ measures corresponding to the ‘lines of code’ values of two consecutive revisions of a source code file. Method: This study has used 11,822 commits or revisions of 4,013 Java source files from 21 open source projects. For the technical debt measure, SonarQube tool is used with 138 code smells. Results: This study finds that ‘technical debt density trend’ metric has interesting characteristics that make it particularly attractive to understand the pattern of accrual and repayment of technical debt by breaking down a technical debt measure into multiple components, e.g., ‘technical debt density’ can be broken down into two components showing mean density corresponding to revisions that accrue technical debt and mean density corresponding to revisions that repay technical debt. The use of ‘technical debt density trend’ metric helps us understand the evolution of technical debt with greater insights. 

The complexity management of software code has become one of the major problems in software development industry. With growing complexity the maintenance effort of code increases. Moreover, various aspects of complexity create difficulties for complexity assessment. The objective of this paper is to investigate the relationships of various aspects of code complexity and propose a method for identifying the most complex functions. We have conducted an action research project in two software development companies and complemented it with a study of three open source products. Four complexity metrics are measured, and their nature and mutual influence are investigated. The results and possible explanations are discussed with software engineers in industry. The results show that there are two distinguishable aspects of complexity of source code functions: Internal and outbound complexities. Those have an inverse relationship. Moreover, the product of them does not seem to be greater than a certain limit, regardless of software size. We present a method that permits identification of most complex functions considering the two aspects of complexities. The evaluation shows that the use of the method is effective in industry: It enables identification of 0.5% most complex functions out of thousands of functions for reengineering.

Complexity management has become a crucial activity in continuous software development. While the overall perceived complexity of a product grows rather insignificantly, the small units, such as functions and files, can have noticeable complexity growth with every increment of product features. This kind of evolution triggers risks of escalating fault-proneness and deteriorating maintainability. The goal of this research was to develop a measurement system which enables effective monitoring of complexity evolution. An action research has been conducted in two large software development organizations. We have measured three complexity and two change properties of code for two large industrial products. The complexity growth has been measured for five consecutive releases of the products. Different patterns of growth have been identified and evaluated with software engineers in industry. The results show that monitoring cyclomatic complexity evolution of functions and number of revisions of files focuses the attention of designers to potentially problematic files and functions for manual assessment and improvement. A measurement system was developed at Ericsson to support the monitoring process.

Unequivocally understandable requirements are vital for software design process. However, in practice it is hard to achieve the desired level of understandability, because in large software products a substantial amount of requirements tend to have ambiguous or complex descriptions. Over time such requirements decelerate the development speed and increase the risk of late design modifications, therefore finding and improving them is an urgent task for software designers. Manual reviewing is one way of addressing the problem, but it is effort-intensive and critically slow for large products. Another way is using measurement, in which case one needs to design effective measures. In recent years there have been great endeavors in creating and validating measures for requirements understandability: most of the measures focused on ambiguous patterns. While ambiguity is one property that has major effect on understandability, there is also another important property, complexity, which also has major effect on understandability, but is relatively less investigated. In this paper we define a complexity measure for textual requirements through an action research project in a large software development organization. We also present its evaluation results in three large companies. The evaluation shows that there is a significant correlation between the measurement values and the manual assessment values of practitioners. We recommend this measure to be used with earlier created ambiguity measures as means for automated identification of complex specifications.

Validating software measures for using them in practice is a challenging task. Usually more than one complementary validation methods are applied for rigorously validating software measures: Theoretical methods help with defining the measures with expected properties and empirical methods help with evaluating the predictive power of measures. Despite the variety of these methods there still remain cases when the validation of measures is difficult. Particularly when the response variables of interest are not accurately measurable and the practical context cannot be reduced to an experimental setup the abovementioned methods are not effective. In this paper we present a complementary empirical method for validating measures. The method relies on action research principles and is meant to be used in combination with theoretical validation methods. The industrial experiences documented in this paper show that in many practical cases the method is effective. © 2016 ACM.

There is a high demand for program developers, but the dropouts from computer science courses are also high and course enrolments keep decreasing. In order to overcome that situation, several studies have found serious games as good tools for education in programming learning. As an outcome from such research, several game solutions for programming learning have appeared, each of them using a different approach. Some of these games are only used in the research field where others are published in commercial stores. The problem with commercial games is that they do not offer a clear map of the different programming concepts. This dissertation addresses this problem and analyses which fundamental programming concepts that are represented in commercial games for programming learning. The study also identifies game design patterns used to represent these concepts.

The result of this study shows topics that are represented more commonly in commercial games and what game design patterns are used for that. This thesis identifies a set of game design patterns in the 20 commercial games that were analysed. A description as well as some examples of the games where it is found is included for each of these patterns.

As a conclusion, this research shows that from the list of the determined fundamental programming topics only a few of them are greatly represented in commercial games where the others have nearly no representation. This shows potential spots for future research in games for programming teaching.

Computer games and virtual worlds are increasingly used throughout our society with people playing on the bus, at home and at work. Computer games thus affect larger and larger number of people and areas in the society of today. There are even scholars who advocate that games or virtual environments create better environments for learning than traditional classrooms. This situation motivates the use of games and game technology for additional purposes, e.g. education, training, health care or marketing.

In today’s global and aggressive market system, for manufacturing companies to remain competitive, they must manufacture high-quality products that can be produced at a low cost; they also must respond efficiently to customers’ predictable and unpredictable needs and demand variations. Increasingly shortened product lifecycles, as well as product customization degrees, lead to swift changes in the market that need to be supported by capable and flexible resources able to produce faster and deliver to the market in shorter periods while maintaining a high degree of cost-efficiency. To cope with all these challenges, the setup of production systems needs to shift toward Reconfigurable Manufacturing Systems (RMSs), making production capable of rapidly and economically changing its functionality and capacity to face uncertainties, such as unforeseen market variations and product changes. Despite the advantages of RMSs, designing and managing these systems to achieve a high-efficiency level is a complex and challenging task that requires optimization techniques. Simulation-based optimization (SBO) methods have been proven to improve complex manufacturing systems that are affected by predictable and unpredictable events. However, the use of SBO methods to tackle challenging RMS design and management processes is underdeveloped and rarely involves Multi-Objective Optimization (MOO). Only a few attempts have applied Simulation-Based Multi-Objective Optimization (SMO) to simultaneously deal with multiple conflictive objectives. Furthermore, due to the intrinsic complexity of RMSs, manufacturing organizations that embrace this type of system struggle with areas such as system configuration, number of resources, and task assignment. Therefore, this dissertation contributes to such areas by employing SMO to investigate the design and management of RMSs. The benefits for decision-makers have been demonstrated when SMO is employed toward RMS-related challenges. These benefits have been enhanced by combining SMO with knowledge discovery and Knowledge-Driven Optimization (KDO). This combination has contributed to current research practices proving to be an effective and supportive decision support tool for manufacturing organizations when dealing with RMS challenges.

This thesis analyses if the change of auditory feedback can improve the effectiveness of performance in the interaction with a non-visual system, or with a system used by individuals with visual impairment. Two prototypes were developed, one with binaural audio and the other with stereo audio. The interaction was evaluated in an experiment where 22 participants, divided into two groups, performed a number of interaction tasks. A post-interview were conducted together with the experiment. The result of the experiment displayed that there were no great difference between binaural audio and stereo regarding the speed and accuracy of the interaction. The post-interviews displayed interesting differences in the way participants visualized the virtual environment that affected the interaction. This opened up interesting questions for future studies.

Facing the task to design, simulate or optimize a complex system itis common to find models and data for the system expressed in differentformats, implemented in different simulation software tools. When a newmodel is developed, a target platform is chosen and existing componentsimplemented with different tools have to be converted. This results inunnecessary work duplication and lead times. The Modelica languageinitiative [2] partially solves this by allowing developers to move modelsbetween different tools following the Modelica standard. Another possi-bility is to exchange models using the Functional Mockup Interface (FMI)standard that allows computer models to be used as components in othersimulations, possibly implemented using other programming languages[1]. With the Modelica and FMI standards entering development, there isneed for an easy-to-use tool that supports design, editing and simulationof such multilingual systems, as well as for retracting system informationfor formulating and solving optimization problems.A prototype solution for a graphical block diagram tool for design, edit-ing, simulation and optimization of multilingual systems has been createdand evaluated for a specific system. The tool is named Composer [3].The block diagram representation should be generic, independent ofmodel implementations, have a standardized format and yet support effi-cient handling of complex data. It is natural to look for solutions amongmodern web technologies, specifically HTML5. The format for represent-ing two dimensional vector graphics in HTML5 is Scalable Vector Graphics(SVG). We combine the SVG format with the FMI standard. In a firststage, we take the XML-based model description of FMI as a form for de-scribing the interface for each component, in a language independent way.Simulation parameters can also be expressed on this form, and integratedas metadata into the SVG image. 

The prototype, using SVG in conjunction with FMI, is implementedin JavaScript and allow creation and modification of block diagrams directly in the web browser. Generated SVG images are sent to the serverwhere they are translated to program code, allowing the simulation ofthe dynamical system to be executed using selected implementations. Analternative mode is to generate optimization problem from the systemdefinition and model parameters. The simulation/optimization result is 

returned to the web browser where it is plotted or processed using otherstandard libraries.The fiber production process at SCA Packaging Obbola [4] is used asan example system and modeled using Composer. The system consists oftwo fiber production lines that produce fiber going to a storage tank [5].The paper machine is taking fiber from the tank as needed for production.A lot of power is required during fiber production and the purpose of themodel was to investigate weather electricity costs could be reduced byrescheduling fiber production over the day, in accordance with the electricity spot price. Components are implemented for dynamical simulationusing OpenModelica and for discrete event using Python. The Python implementation supports constraint propagation between components andoptimization over specified variables. Each component is interfaced as aFunctional Mock-up Unit (FMU), allowing components to be connectedand properties specified in language independent way. From the SVGcontaining the high-level system information, both Modelica and Pythoncode is generated and executed on the web server, potentially hosted ina high performance data center. More implementations could be addedwithout modifying the SVG system description.We have shown that it is possible to separate system descriptions onthe block diagram level from implementations and interface between thetwo levels using FMI. In a continuation of this project, we aim to integratethe FMI standard also for co-simulation, such that components implemented in different languages could be used together. One open questionis to what extent FMUs of the same component, but implemented withdifferent tools, will have the same model description. For the SVG-basedsystem description to be useful, the FMI model description must remainthe same, or at least contain a large overlap, for a single component implemented in different languages. This will be further investigated in futurework.

Flexibility is often cited as a desirable key characteristic of modern production systems. In ultra-flexible production, machinery and layouts are in a constant state of adaptation to accommodate changing orders, varying products, or evolving conditions. Cyber-physical integration has been proposed as a potential approach to increasing system flexibility with Cyber-Physical Production Systems (CPPS) and Digital Twins (DT) as central concepts. While numerous architectures, frameworks and approaches have been proposed for CPPS and DT development, further research is motivated regarding the development of a requirement-based framework that links together the high-level system property of flexibility and lower-level system components, enabling the analysis, prescription and comparison of systems. Such a framework could enable manufacturers to continuously evaluate and improve manufacturing systems' flexibility as well as make informed design decisions. Ultimately enhancing system flexibility and responsiveness to changing production conditions. This study aims to initiate the development and formulation of such a requirements-based framework linking flexibility and lower-level system components. Additionally, it seeks to introduce the concept of a”cyber-physical continuum, ” which the study aims to define as a potential quantifiable indicator reflecting flexibility within production systems. This is achieved by leveraging prior CPPS research based on high-level system requirements. These requirements were expanded by branching each requirement into lower-level components creating a more granular scope and providing a finer lens for analysis and assessment. The framework was then applied to assess a high-mix, low-volume manufacturing scenario. Application of the preliminary framework in the case study indicates its potential utility in providing a useful view of the cyber-physical content of a system. Moreover, it serves as a valuable guide for pinpointing areas for improvement and development. By developing a framework that seamlessly links high-level flexibility requirements with detailed implementation requirements, systems can be comprehensively evaluated, methodically prescribed, and effectively compared. As future work, further refinement and validation of this framework will be crucial to ensuring its validity and applicability across diverse manufacturing contexts. 

Denna studie utforskar hur valet mellan två metoder för evaluering av individer i en evolutionär algoritm påverkar procedurellt genererat innehåll. Evolutionär generering är ett delområde av sökbaserad-procedurell generering som tar inspiration från verkligevolution med implementation av koncept som; ärvda egenskaper, mutation och naturligselektion. Studiens två evalueringsmetoder användes vid framställningen av spelbanor till ett imaginärt spel inom genren realtidsstrategi. Banor skapades för i teorin två spelare och visualiserade i en egenskapad testmiljö.

Resultaten fastställde att valet av evalueringsmetod påverkar hur ett set av banor kan upplevas i förhållande till en spelare och till varandra. Användningen av studiens traditionella metod för evaluering resulterade i banor med mer snarlika egenskaper tillvarandra men kunde alla anses besitta balanserade förutsättningar för banornas två spelare. Användningen av studiens multiobjektiva metod för evaluering resulterade i banor mervarierande från varandra men som alla inte kunde anses besitta balanserade förutsättningarför spelare.

Utifrån studiens resultat skulle en utvecklare kunna skapa en evolutionär algoritm och veta till vilken grad valet av evalueringsmetod påverkar genererat innehåll. Framtida studierskulle även från resultaten i denna studie kunna undersöka personers upplevelse vidspelsessioner med evolutionärt genererade banor jämfört med manuellt skapade banor i existerande spel.

Reproducible builds (R-Bs) are software engineering practices that reliably create bit-for-bit identical binary executable files from specified source code. R-Bs are applied in someopen source software (OSS) projects and distributions to allow verification that the distrib-uted binary has been built from the released source code. The use of R-Bs has been advo-cated in software maintenance and R-Bs are applied in the development of some OSS secu-rity applications. Nonetheless, industry application of R-Bs appears limited, and we seekto understand whether awareness is low or if significant technical and business reasonsprevent wider adoption. Through interviews with software practitioners and business man-agers, this study explores the utility of applying R-Bs in businesses in the primary and sec-ondary software sectors and the business and technical reasons supporting their adoption.We find businesses use R-Bs in the safety-critical and security domains, and R-Bs are valu-able for traceability and support collaborative software development. We also found thatR-Bs are valued as engineering processes and are seen as a badge of software quality, butwithout a tangible value proposition. There are good engineering reasons to use R-Bs inindustrial software development, and the principle of establishing correspondence betweensource code and binary offers opportunities for the development of further applications.

Software interoperability is commonly achieved through the implementation of standards for communication protocols or data representation formats. Standards documents are often complex, difficult to interpret, and may contain errors and inconsistencies, which can lead to differing interpretations and implementations that inhibit interoperability. Through a case study of two years of activity in the Apache PDFBox project we examine day-to-day decisions made concerning implementation of the PDF specifications and standards in a community open source software (OSS) project. Thematic analysis is used to identify semantic themes describing the context of observed decisions concerning interoperability. Fundamental decision types are identified including emulation of the behaviour of dominant implementations and the extent to which to implement the PDF standards. Many factors influencing the decisions are related to the sustainability of the project itself, while other influences result from decisions made by external actors, including the developers of dependencies of PDFBox. This article contributes a fine grained perspective of decision-making about software interoperability by contributors to a community OSS project. The study identifies how decisions made support the continuing technical relevance of the software, and factors that motivate and constrain project activity. 

Open hardware and open source software platforms bring benefits to both implementers and users in the form of system adaptability and maintainability, and through the avoidance of lock-in, for example. Development of the \riscv\ Instruction Set Architecture and processors during the last ten years has made the implementation of a desktop computer using open hardware, including open processors, and open source software an approaching possibility. We use the SiFive Unmatched development board and Ubuntu Linux, and the recorded experiences of system builders using the Unmatched board to explore the extent to which it is possible to create an open desktop computer. The work identifies current limitations to implementing an open computer system, which lie mainly at the interface between the operating system and hardware components. Potential solutions to the challenges uncovered are proposed, including greater consideration of openness during the early stages of product design. A further contribution is made by an account of the synergies arising from open collaboration in a private-collective innovation process.

The majority of contributions to community open source software (OSS) projects are made by practitioners acting on behalf of companies and other organisations. Previous research has addressed the motivations of both individuals and companies to engage with OSS projects. However, limited research has been undertaken that examines and explains the practical mechanisms or work practices used by companies and their developers to pursue their commercial and technical objectives when engaging with OSS projects. This research investigates the variety of work practices used in public communication channels by company contributors to engage with and contribute to eight community OSS projects. Through interviews with contributors to the eight projects we draw on their experiences and insights to explore the motivations to use particular methods of contribution. We find that companies utilise work practices for contributing to community projects which are congruent with the circumstances and their capabilities that support their short- and long-term needs. We also find that companies contribute to community OSS projects in ways that may not always be apparent from public sources, such as employing core project developers, making donations, and joining project steering committees in order to advance strategic interests. The factors influencing contributor work practices can be complex and are often dynamic arising from considerations such as company and project structure, as well as technical concerns and commercial strategies. The business context in which software created by the OSS project is deployed is also found to influence contributor work practices.

Professionals contribute to open source software (OSS) projects aspart of their employment. Previous research has addressed motivationsof individuals and the ways they engage with OSS projects.However, there is a lack of research which examines and explainswork practices used by companies in their engagement with projects.Work practices used by companies to contribute to five establishedOSS projects are investigated through examination of the actions ofemployees in public communication channels and draw on our experienceswhen analysing engagement with the same projects. Wefind that companies utilise work practices for contributing whichare congruent with the circumstances and their capabilities thatsupport their short and long term needs. We find that companiescontribute to OSS projects in different ways, such as employing coreproject developers, making donations, and joining project steeringcommittees in order to advance strategic interests.

Performance is something that is always of concern when developing real-time 3D graphics applications. The way programs are made today with object-oriented programming has certain flaws that are rooted in the methodology itself. By exploring different programming paradigms we can eliminate some of these issues and find what is best for programming in different areas. Because real-time 3D applications need high performance the data-oriented design paradigm that makes the data the center of the application is experimented with. By using data-oriented design we can eliminate certain issues with object-oriented programming and deliver improved applications when it comes to performance, flexibility, and architecture. In this study, an experiment creating the same type of program with the help of different programming paradigms is made to compare the performance of the two. Some additional up- and downsides of the paradigms are also mentioned

This book constitutes the refereed proceedings of the 12th International IFIP WG 2.13 International Conference on Open Source Systems, OSS 2016, held in Gothenburg, Sweden, in May/June 2016. The 13 revised full papers presented were carefully reviewed and selected from 38 submissions. The papers cover a wide range of topics related to free, libre, and open source software, including: organizational aspects of communities; organizational adoption; participation of women; software maintenance and evolution; open standards and open data; collaboration; hybrid communities; code reviews; and certification.

Detta arbete har utförts för att undersöka frågeställningen ”Hur bör ett dataspels tutorial designas för att spelaren ska lära sig samtidigt som den främjar uppkomsten av flow?”. För att besvara detta har teorier inom pedagogik, lärande av spel, användbarhet och flow samt mer generella teorier kring spel studerats för att skapa en teoribildning inom området. För att testa detta har ett spel med två olika tutorials skapats. Detta spel har sedan använts för att, med hjälp av två testgrupper, samla data om hur spelare lär sig samt deras flowupplevelse. Resultaten visar på att den typ av inlärning som bör appliceras är beroende av vad som ska läras ut till spelaren. Huruvida någon av de olika typerna av tutorials är fördelaktiga för uppkomsten av flow har ej kunnat besvara då de båda testgruppernas data visat på snarlika flowupplevelser. 

Virtual robotics can be used to dramatically improve the capabilities and performance of industrial robotic systems. Virtual robotics encapsulates graphical off-line programming systems and Computer Aided Robotics (CAR). However current virtual robotic tools suffer from a number of major limitations which severely restrict the ways in which they can be deployed and the performance advantages they offer to the industrial user. The research study focuses on simulation of sensors, programming of event based robotic systerns and demonstrates how intelligent robots can be trained adaptive behaviours in virtual environments. Contemporary graphical programming systems for robots can only be used to program limited sections of a robot program, since i) they do not support methods for the simulation of sensors and event detection; ii) they normally use a post-processor to translate programs from a general language to a controller specific language; iii) conternporary robots can not easily adapt to changes in their environments; and iv) robot programs created off-line must be calibrated to adjust to differences between the virtual and real robotic workcells.

The thesis introduces a generic sensor model which can be used to model a variety of sensor types. This model allows virtual sensors to work as independent devices. It is demonstrated that using simulated sensors, event-based robot programs can be created and debugged entirely off-line. Off-line programming of event-based robotic systems demands methods for realistic handling of the communication between independent devices and process. The system must also possess the ability to manage and store information describing status and events in the environment. A blackboard architecture has been used in this research study to store environmental conditions and manage inter-process communication.

Self-learning robots is a possible strategy to allow robots to adapt to environmental changes and to learn from their experience. If suitable learning regimes are developed robots can learn to detect changes between virtual and real environments thus minimising the need for calibration. Most learning is based on experience and this requires experimental data to be fed to the learning system. This thesis demonstrates that robot controllers using artificial neural networks for knowledge acquisition and storage can be 'pre-emptively learnt' in virtual robotic environments using virtual robots and simulated sensors. The controllers are able to generalise from the information acquired by the virtual sensors operating in the virtual environment. Arguably the biggest obstacle to the use of self learning robotic systems in real applications has been the need to train the 'real robots' extensively in the 'real environment'. 'Pre-emptive learning' removes this problem. Furthermore, it is therefore possible to develop and evaluate new learning regimes using virtual robotic systems. This approach provides an opportunity to create a variety of environments and conditions which would be impractical to create in a real environment (due to constraints of time, cost and availability). 

Model-based test design is increasingly being applied in practice and studied in research. Model-based testing (MBT) exploits abstract models of the software behaviour to generate abstract tests, which are then transformed into concrete tests ready to run on the code. Given that abstract tests are designed to cover models but are run on code (after transformation), the effectiveness of MBT is dependent on whether model coverage also ensures coverage of key functional code. In this article, we investigate how MBT approaches generate tests from model specifications and how the coverage of tests designed strictly based on the model translates to code coverage. We used snowballing to conduct a systematic literature review. We started with three primary studies, which we refer to as the initial seeds. At the end of our search iterations, we analysed 30 studies that helped answer our research questions. More specifically, this article characterizes how test sets generated at the model level are mapped and applied to the source code level, discusses how tests are generated from the model specifications, analyses how the test coverage of models relates to the test coverage of the code when the same test set is executed and identifies the technologies and software development tasks that are on focus in the selected studies. Finally, we identify common characteristics and limitations that impact the research and practice of MBT: (i) some studies did not fully describe how tools transform abstract tests into concrete tests, (ii) some studies overlooked the computational cost of model-based approaches and (iii) some studies found evidence that bears out a robust correlation between decision coverage at the model level and branch coverage at the code level. We also noted that most primary studies omitted essential details about the experiments. 

Då den webb som vi idag använder har växt snabbt har ett antal problem uppstått. Antalet tjänster är många och mängden information är stor. Den enorma informationsmängden gör att det är svårt att hitta relevant sådan vid sökningar. Om maskiner kunde hjälpa till med sökningen skulle problemet minska.

Den semantiska webben beskrivs som en förlängning av den nuvarande webben skapad för att låta maskiner kunna utnyttja den information som finns representerad på webben. För att kunna göra webben maskinläsbar krävs det att webben kodas med semantisk information. Detta kan göras av personer som författar webbsidor. För att detta ska kunna göras krävs det att det finns verktyg som tillåter att det görs, verktygen ska gärna kunna användas samtidigt som webbsida skapas. Denna studie har utvärderat hur de webbsidesredigeringsverktyg som används idag kan användas för att skapa semantisk uppmärkning. Studien går igenom ett antal verktyg ur olika kategorier och utvärderar det semantiska stödet dessa ger användaren. Utvärderingen görs med hjälp av kriterier som tagits fram genom att studera ett antal prototypverktyg för semantisk uppmärkning.

Resultatet av studien ger en indikation på att de verktyg som idag används inte är redo för att låta användaren skapa webbsidor märkta med semantisk information.

The overarching goal in this paper is to investigate organisational engagement with an ICT standard and open source software (OSS) projects that implement the standard, with a specific focus on the multimedia field, which is relevant in light of the wide deployment of standards and different legal challenges in this field. The first part reports on experiences and insights from engagement with standards in the multimedia field and from implementation of such standards in OSS projects. The second part focuses on the case of the ITU-T H.264 standard and the two OSS projects OpenH264 and x264 that implement the standard, and reports on a characterisation of organisations that engage with and control the H.264 standard, and organisations that engage with and control OSS projects implementing the H.264 standard. Further, projects for standardisation and implementation of H.264 are contrasted with respect to mix of contributing organisations, and findings are related to organisational strategies of contributing organisations and previous research.

This paper presents novel results concerning influences between ICT standards and their implementations in open source software (OSS). Specifically, findings draw from observations and analysis related to the ITU-T H.264 standard and the two OSS projects OpenH264 and x264 that both implement the standard. The study reports on a characterisation of organisations that influence and control the H.264 standard, organisations that influence and control OSS projects implementing the H.264 standard, and influences between contributors involved with the H.264 standard and OSS projects implementing that standard. Further, projects for standardisation and implementation of H.264 are contrasted with respect to mix of contributing organisations, and findings are related to organisational strategies of contributing organisations and previous research.

It is known that standards implemented in Open Source software (OSS) can promote a competitive market, reduce the risk for lock-in and improve interoperability, whilst there is limited knowledge concerning the relationship between standards and their implementations in OSS. In this paper we report from an ongoing case study conducted in the context of the ORIOS (Open Source software Reference Implementations of Open Standards) project in which influences between OSS communities and software standard communities are investigated. The study focuses on the Drupal project and three of its implemented standards (RDFa, CMIS, and OpenID).

Denna uppsats handlar om hur de semantiska värdena kan överföras från ett koncept till en 3Dmodell. Detta innebär att vi tar de fysikaliska attribut av en karaktär i ett koncept bygger dessa i en 3-dimensionnell miljö. Med hjälp av genreteori kring semantik och syntax, gör vi oss medvetna om vad dessa begrepp kan innebära i den process som ingår i modellering av karaktärer. Vi bryter upp karaktärskonceptet i mindre beståndsdelar så som mjuka/hårda ytor och gör en granskning av karaktärernas semantiska drag. Därefter beskrivs den arbetsmetod som användes för att skapa 3D karaktären, där vi berör några av de viktiga punkterna i arbetsprocessen. Min frågeställning som var, Hur kan vi överföra de semantiska värdena av en karaktär till en tredimensionell modell som är anpassad för dator/TV-spel? Besvaras med de metoder som användes i skapandet av karaktären. Slutligen presenteras 3Dmodellen med en videosekvens

In this thesis, the overall conclusion is that combination strategies, (i.e., test case selection methods that manage the combinatorial explosion of possible things to test), can improve the software testing in most organizations. The research underlying this thesis emphasizes relevance by working in close relationship with industry.

Input parameter models of test objects play a crucial role for combination strategies. These models consist of parameters with corresponding parameter values and represent the input space and possibly other properties, such as state, of the test object. Test case selection is then defined as the selection of combinations of parameter values from these models.

This research describes a complete test process, adapted to combination strategies. Guidelines and step-by-step descriptions of the activities in process are included in the presentation. In particular, selection of suitable combination strategies, input parameter modeling and handling of conflicts in the input parameter models are addressed. It is also shown that several of the steps in the test process can be automated.

The test process is validated through a set of experiments and case studies involving industrial testers as well as actual test problems as they occur in industry. In conjunction with the validation of the test process, aspects of applicability of the combination strategy test process (e.g., usability, scalability and performance) are studied. Identification and discussion of barriers for the introduction of the combination strategy test process in industrial projects are also included.

This research also presents a comprehensive survey of existing combination strategies, complete with classifications and descriptions of their different properties. Further, this thesis contains a survey of the testing maturity of twelve software-producing organizations. The data indicate low test maturity in most of the investigated organizations. Test managers are often aware of this but have trouble improving. Combination strategies are suitable improvement enablers, due to their low introduction costs.

The System Architecture Virtual Integration (SAVI) initiative is a multiyear, multimillion dollar program that is developing the capability to virtually integrate systems before designs are implemented and tested on hardware. The purpose of SAVI is to develop a means of countering the costs of exponentially increasing complexity in modern aerospace software systems. The program is sponsored by the Aerospace Vehicle Systems Institute, a research center of the Texas Engineering Experiment Station, which is a member of the Texas A&M University System. This report presents an analysis of the economic effects of the SAVI approach on the development of software-reliant systems for aircraft compared to existing development paradigms. The report describes the detailed inputs and results of a return-on-investment (ROI) analysis to determine the net present value of the investment in the SAVI approach. The ROI is based on rework cost-avoidance attributed to earlier discovery of requirements errors through analysis of virtually integrated models of the embedded software system expressed in the SAE International Architecture Analysis and Design Language (AADL) standard architecture modeling language. The ROI analysis uses conservative estimates of costs and benefits, especially for those parameters that have a proven, strong correlation to overall system-development cost. The results of the analysis, in part, show that the nominal cost reduction for a system that contains 27 million source lines of code would be $2.391 billion (out of an estimated $9.176 billion), a 26.1% cost savings. The original study, reported here, had a follow-on study to validate and further refine the estimated cost savings.

The use of mobile ad-hoc networks (MANETs) is growing. The issue of security in MANETs is not trivial, since such networks have no fixed infrastructure and therefor centralised security is not applicable. MANETs are also more sensitive to attacks due to their wireless communication channels and their spontaneous nature.

All kind of cooperation requires a sense of trust. The opinion about trust in other entities can be used as a mean to dynamically allow for secure cooperation in MANETs, as soft security. And also to counter some of the inherited security problems of MANETs.

To use opinions as a security paradigm in MANETs the opinions about other nodes has to be spread as reputation about a node. This reputation spreading can be done through spreading of opinions or the spreading of evidences about a nodes behaviour.

In this work evidence and reputation spreading are compared to each other. This comparison shows that they are quite similar from a security point of view but that they differ in scalability.

As the performance of PCs is increasing it is of great interest to use these cheap devices as routers,which traditionally consisted of more expensive and customized hardware for that purpose. Thesoftware was also traditionally proprietary and thereby costly, but as the open source communityhas grown there have been development of open source solutions that can perform the task ofacting as a router. However as there are so many solutions out there, it can be hard for the potentialusers to choose which particular solution to use, without having to put in too much work intogetting a fully functional router solution. This study achieved this purpose by benchmarking themost popular open source software routers, in terms of performance and scalability as well asproviding a brief analysis of their basic security features. The routers that were studied wasClearOS, Untangle NG Firewall and IPFire, and after the study was complete IPFire was consideredthe superior with ClearOS as the second and Untangle as third and last.

DeepTelos is defined as a set of rules and constraints that enable multi-level modeling for the Telos metamodeling language. In its ConceptBase implementation, rules and constraints are realized by Datalog clauses. We start with demonstrating first the core functions of Telos, use of simple rules and constraints,then the meta-level rules and constraints defining DeepTelos. A couple of examples show how the DeepTelos rules and constraints are compiled to simple rules and constraints and then realize the desired multi-level modeling environment. The main example is taken from the Galileo satellite domain.