I denne masteroppgaven ser vi på hvordan man kan bruke elementer fra spill til å øke motivasjonen for å gjøre ulike oppgaver. Et system som gir detaljert og ærlig tilbakemelding med medaljer og andre elementer fra spill ble utviklet, og testet på en del brukere. Konklusjonen er at ærlig tilbakemelding kan ha en motiverende effekt.

The RRB-tree is a confluently persistent data structure based on the persistent vector, with efficient concatenation and slicing, and effectively constant time indexing, updates and iteration. Although efficient appends have been discussed, they have not been properly studied.This thesis formally describes the persistent vector and the RRB-tree, and presents three optimisations for the RRB-tree which have been successfully used in the persistent vector. The differences between the implementations are discussed, and the performance is measured. To measure the performance, the C library librrb is implemented with the proposed optimisations.Results shows that the optimisations improves the append performance of the RRB-tree considerably, and suggests that its performance is comparable to mutable array lists in certain situations.

This master thesis looks at how clustering techniques can be appliedto a collection of scientific documents. Approximately one year of serverlogs from the CERN Document Server (CDS) are analyzed and preprocessed.Based on the findings of this analysis, and a review of thecurrent state of the art, three different clustering methods are selectedfor further work: Simple k-Means, Hierarchical Agglomerative Clustering(HAC) and Graph Partitioning. In addition, a custom, agglomerativeclustering algorithm is made in an attempt to tackle some of the problemsencountered during the experiments with k-Means and HAC. The resultsfrom k-Means and HAC are poor, but the graph partitioning methodyields some promising results.The main conclusion of this thesis is that the inherent clusters withinthe user-record relationship of a scientific collection are nebulous, butexisting. Furthermore, the most common clustering algorithms are notsuitable for this type of clustering.

Smartphones with capabilities for wireless Internet and GPS have become increasinglycommon in recent years, and a consequence of this is that pervasivegames have become more interesting from both an academical and a commercialpoint of view. Another area of interest is lifelong learning, which offers amore modern take on education compared to the traditional learning model. Inthis thesis we aim to discover whether or not pervasive gaming can help achievelifelong learning. This is done by creating a prototype of a pervasive game ina lifelong learning context for Android, analyzing the effectiveness of the prototype,and using the experiences drawn from it to design a platform to runknowledge competitions.We achieved this by conducting a prestudy on the Android mobile phone operatingsystem (including extension applications), the history of Trondheim, lifelonglearning, pervasive games, and the use of pervasive games in a lifelong learningcontext. During the prestudy we found out that there are several externalapplications and features of Android that can be utilized to expand the social,spatial, and temporal expansions of pervasive games. We also found that, intheory, pervasive games proved to be a suitable platform to support lifelonglearning.We then designed and developed a prototype on Android to run a puzzle racecalled ”The Amazing City Game”. The race consisted of completing differenttasks related to the history of Trondheim, while traveling between many of thehistorical sites in the city. A demonstration race was conducted in early May withfour groups of two students each, using the authors and supervisors of this thesisas group observers. At the end of the race, the participants filled out a survey.Using the observations from the race and the results from the survey we foundthat the prototype was perceived as fun and educational. However, constructionof the race was challenging with many pitfalls concerning ambiguous tasks, useof language, and game balance.Finally, we have provided a possible design for a platform for running knowledgecompetitions. We used the experiences from the development of the prototype,and the results from the demonstration race to design a cleaner and more completeframework. This includes a refinement of the existing functionality anduser interface, adding requirements, and providing an extended discussion ontopics such as having an online community, possible server solutions, and securitymeasures against cheating. We believe that the concept of puzzle races in alifelong learning context is an interesting concept that could have positive effectsif utilized in the real world.

Running automated tests can be a time-consuming task, especially when doing regression testing. If the sequence of the execution of the test cases is arbitrary, there is a good chance that many of the defects are not detected until the end of the test run. If the developer could get the failing tests first, he would almost immediately be able to get back to coding or correcting mistakes. In order to achieve this, we designed and analyzed a set of test case prioritization techniques. The prioritization techniques were compared in an experiment, and evaluated against two existing techniques for prioritizing test cases.Our implementation of the prioritization techniques resulted in a tool called Pritest, built according to good design principles for performance, adaptability and maintainability. This tool was compared to an existing similar tool through a discussion.The problem we address is relevant for the increased popularity of agile software methods, where rapid regression testing is of high importance. The experiment indicates that some prioritization techniques perform better than others, and that techniques based on code analysis is outperformed by techniques analyzing code changes, in the context of our experiment.

Popular Internet applications can grow rapidly into millions of users. This is an important challenge for application developers, as failing to handle increasing load can disrupt an application’s popularity surge and cause massive monetary losses.Many popular applications are ubiquitous, meaning they are used not only from web browsers on desktop computers, but also handheld devices, as well as other services operating on servers, connecting to the application via an Application Programming Interface (API). For traditionally designed web applications, this ubiquity is hard to achieve, as the difference in architecture creates a barrier for reusability of server side code.Using a design science research methology, this report details an approach to solving scalability issues and greatly improving reusability and development speed for modern ubiquitous Internet applications. The crux of the approach is a bare-essentials data access and user management API, whose implementation is intended to serve as the entire server side of the application.For applications that can cope with its reduced feature set, it has several major advantages. API implementations are interchangeable, eliminating vendor lock, and also completely reusable across applications, saving development effort. Presentation and application logic is shifted to the client side, reducing server strain, and the API is easily implemented with a modern, hyperscalable data store in a cloud environment, providing great elasticity and scalability.The functionality of the API is derived from an analysis of target applications, and the approach is evaluated through the development of a prototype, a blog application with clients for several platforms. The prototype development process reveals some architectural and practical limitations to the design, but also showcases the power of reusable components when those components are readily available.The approach presented here is not ideal for all types of applications. However, when applicable, it helps developers save time and overcome these important challenges in application development.

This thesis project explores and evaluates the use of a motion-controlled game as an interactive campaign in a public space. Through a collaboration with the Trondheim-based company Global Illumination, we were given the task of developing a prototype that would be tested in the field. The objective was to evaluate the relevant technology, how users relate to the prototype and what the marketing potential is.Through a literature study and using the technology, we found that while it is still new, the technology is both mature enough to be used for several different platforms and languages, and cheap enough that the cost of getting started should not be a hindrance.We developed a game prototype using the OpenNI and XNA frameworks, in which people who pass by the display would be reflected on the screen in the form of a silhouette and automatically be a part of the game. The prototype was tested at four different public locations in Trondheim, and was evaluated mainly through observation and questionnaires given to both participants and non-participants.Our findings suggest that there is definite potential for using motion-control in interactive campaigns in public settings. The game attracted a good amount of attention, and seemed to pique the curiosity of passers-by. We saw a trend emerge where participants were comfortable with playing the game in public and were easily engaged. Children and young people in groups were by far the most active participants. We also found that keeping a low threshold for interaction was essential, as adding an extra step in the form of a wave gesture to participate reduced the number of participants considerably.

This project explores the possibilities in detecting changes in opinion over time. For this purpose, different techniques and algorithms in opinion mining have been studied and used as a theoretic foundation when developing strategies towards detecting changes in opinions.Different approaches to a system that detects and visualises changes in opinions have been proposed. These approaches include using machine learning techniques like the naiveBayes algorithm and opinion mining techniques based on SentiWordNet. Additionally,feature extraction techniques and the impact of burst detection have been studied.During this project, experiments have been carried out in order to test some of the techniques and algorithms. A data set containing hotel reviews and a prototype have beenbuilt for this purpose, allowing easy support for testing and validation. Results found high accuracy in opinion mining with the lexicon SentiWordNet, and the prototype can detect hotel features and possible reasons for changes in opinion. It can also show "good" and "bad" geographical areas based on hotel reviews.For commercial use, the prototype can help analyse the massive amount of hotel informa-tion published each day by customers, and can help hotel managers analyse their products. It can also be used as a more advanced hotel search engine where users can find extra information in a map user interface.

In the course TDT4520 - Specialization Project, the preparatory course to this thesis, we looked at several safety analysis methods and how they could be exploited to identify software hazards in the early stages of development. After our evaluation, and with the results from a survey conducted on experts in the field, we proposed a procedure to improve software hazard identification in the concept phase of projects. The procedure consisted of a Misuse Case analysis with a sub-sequential HAZOP analysis. Our case study showed that this procedure will indeed aid in the identification process. However, testing the procedure on others is needed to see if this is correct. That is the main theme for this thesis. We performed an experiment with undergraduate students and an interview with an expert in the field. We use the results from the experiment to validate our assumptions and identify modifications that might be needed. The experiment gave us a good illustration of how the procedure would work in a real hazard analysis project, and the data collected showed us the differences between it and the more commonly used Preliminary Hazard Analysis. Our hypothesis was that the Misuse Case and HAZOP approach would improve the hazard identification with focus on software. The experiment resulted in no clear difference in non-software parts of the system, but a clear improvement on the software parts. Afterwards we conducted an interview with an expert in the field, in which we clarified many of our questions and assumptions, and aided us in modifying the procedure to the better.Although the procedure still needs to be tested thoroughly with real projects in the industry to make a final decision on whether it has merit or not, our conclusion is that the procedure deserves further attention. Software hazard identification in the concept phase is difficult but based on our findings, the Misuse Case and HAZOP combination can improve this problem.