Switching between windows on a computer is a frequent activity, but finding and switching to the target window can be inefficient. This thesis aims to better understand and support window switching. It explores two issues: (1) the lack of knowledge of how people currently interact with and switch between windows and (2) how window switching can be supported better. Having a good understanding of how users interact with windows is important for informing the design of new and improved window management tools. However, there have been relatively few empirical studies of window manipulation on commonly used operating systems, and those that do exist may no longer reflect current use. To address this lack of knowledge a three week log-based longitudinal study of window use by 25 participants was conducted using the custom-made tool PyLogger, which recorded actual window switching behaviour. However, the analysis of longitudinal log data, such as the data gathered by PyLogger, is problematic as it is difficult to extract meaningful characterisations. Therefore, this thesis also presents a visualisation tool called Window Watcher that assists understanding and interpreting the low level event logs of window use generated by PyLogger. Window Watcher’s design objectives are described, and examples demonstrate the ways that it summarises and elucidates window use. The results of the PyLogger study provide an empirical characterisation of interaction with windows, and results include the following: (1) the participants had fewer windows open and visible than in previous studies; (2) window switching is a frequent activity; (3) several findings related to specific window switching tools, including that acquiring a particular window by navigating through application-grouped items on the Taskbar is slow, and that Alt+Tab is seldom used for retrieving anything other than the most recently used window; (4) an updated classification of stereotypical window management styles (pilers, maximisers, near maximisers, and splatterers); and (5) there are strong window and application revisitation patterns. Finally, implications of the results of the log study for the design of window switching tools are discussed. The findings from the PyLogger study led to the development of a new window switcher called SCOTZ (for Spatially Consistent Thumbnail Zones). SCOTZ is a window switching interface which shows all windows grouped by application and allocates more space to the most frequently revisited applications. The two design objectives of SCOTZ are (1) to provide a spatially stable layout of applications and windows, and (2) to support revisitation to recently and frequently used windows. Additional design objectives are to support various display sizes, to support both keyboard and mouse input, to provide possibilities for application launching and to provide options for end-user customisation. The design and features of SCOTZ are described, followed by theoretical and empirical validation of its underlying design principles. Findings include that (1) spatially stable layouts allow for faster acquisition of targets than recency and random layouts, (2) the instability inevitably caused by size morphing does not severely impact user performance, (3) size morphing leads to an overall performance advantage because of the Fitts’ Law targetting time advantage of increased target size, and (4) size morphing facilitates finding items because of guided search. Also, findings from an empirical study demonstrate that SCOTZ yields performance and preference benefits over existing window switching tools. Finally, as SCOTZ employs a treemap algorithm to generate the layout of the application zones the suitability of various treemap algorithms for the purpose of SCOTZ is explored, particularly in terms of spatial stability. In previous work, many different treemap algorithms have been proposed, often with the aim being to optimise performance across several criteria, including spatial stability. However, none of the existing treemaps are stable when data updates, and when items are added/deleted, and when many changes have taken place (i.e., the cumulative effect of data changes). Therefore, this thesis introduces the novel ‘Hilbert’ and ‘Moore’ treemap algorithms, which are designed to achieve high spatial stability. Their performance is theoretically assessed in comparison to other treemaps by using various metrics, including a novel ‘location drift’ metric to better capture spatial stability than the commonly used ‘distance change’ metric. The theoretical evaluation demonstrates that Hilbert and Moore treemaps perform well across all stability metrics. An empirical study examines the validity and usefulness of the location drift metric, showing that location drift can explain some effects on user performance that distance change alone can not.

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2015-03-24T14:51:12Z No. of bitstreams: 2 Dissertação - Vinícius Rafael Lobo de Mendonça - 2014.pdf: 4110263 bytes, checksum: 2e2be342a6c3301f64fa41a675b85ba9 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2015-03-24T14:55:54Z (GMT) No. of bitstreams: 2 Dissertação - Vinícius Rafael Lobo de Mendonça - 2014.pdf: 4110263 bytes, checksum: 2e2be342a6c3301f64fa41a675b85ba9 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2015-03-24T14:55:54Z (GMT). No. of bitstreams: 2 Dissertação - Vinícius Rafael Lobo de Mendonça - 2014.pdf: 4110263 bytes, checksum: 2e2be342a6c3301f64fa41a675b85ba9 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2014-11-19 / Recommendation systems try to guide the user carrying out a task providing him with useful information about it. Considering the context of software development, programs are ever increasing, making it difficult to carry out a detailed verification of warnings generated by automatic static analyzers. In this work, we propose a recommendation system, called WarningsFIX, which aims at helping developers on handling the high number of warnings reported by automatic static analyzers. The back end of this system is composed of seven open-source static analysis tools collecting data, which subsequently are used for visualizing information through TreeMaps. The intention is to combine the outcomes of different static analyzers such that WarningsFIX recommends the analysis of warnings with highest chance to be a true positive. Therefore, the information related to warnings are displayed in four levels of detail: program, package, class, and line. The nodes may be classified in the first three levels: amount of warnings, number of tools and suspicions rate. An exploratory study was carried out and the limitations, advantages and disadvantages of the proposed approach were discussed. / O Sistema de Recomendação apoia um usuário na realização de uma tarefa. Considerando o atual contexto do desenvolvimento de software, programas estão cada vez maiores, tornando difícil a realização de uma avaliação detalhada dos avisos gerados pelos analisadores estáticos. Nesse trabalho, propõe-se um sistema de recomendação, chamado WarningsFIX, que tem objetivo de ajudar os desenvolvedores manipular o alto nível dos avisos emitidos pelos analisadores estáticos. O back end desse sistema é composto de sete ferramentas de análise estática de código aberto para coleta de dados, que são visualizados por meio de TreeMap. O objetivo é combinar os resultados de diferentes analisadores estáticos, assim recomendar a análise de avisos com alta chance de ser verdadeiro positivo. Portanto, a informações relacionadas ao nó são visualizadas em quatro níveis de visualização: programa, pacote, classe e linha. Além disso, os nós podem ser classificados em três tipos: quantidade de avisos, quantidade de ferramentas e taxa de suspeição. Um estudo exploratório foi realizado e as limitações, vantagens e desvantagens da abordagem proposta foram discutidas.

<p>As the development of the Internet and the rapid increase of data, information visualization is becoming more and more popular. Since human eyes receive visual information very quick and easy, the visualization can make complex and large data more understandable.</p><p>Describing sensory perceptions, such as taste, is a challenging task. For a customer, the visualization of the taste of a specific wine together with the other wine attributes such as color and grape type would help him/her choose the right one.    In the thesis, two suitable representations of wine attributes are implemented. And, the final system contains two parts. One is a user interface generating his/her fingerprint based on the two representations. The other one is generating the fingerprints of all wines in a database, and save these fingerprints as images. If the user compares his/her wine fingerpr</p>

As the development of the Internet and the rapid increase of data, information visualization is becoming more and more popular. Since human eyes receive visual information very quick and easy, the visualization can make complex and large data more understandable. Describing sensory perceptions, such as taste, is a challenging task. For a customer, the visualization of the taste of a specific wine together with the other wine attributes such as color and grape type would help him/her choose the right one.    In the thesis, two suitable representations of wine attributes are implemented. And, the final system contains two parts. One is a user interface generating his/her fingerprint based on the two representations. The other one is generating the fingerprints of all wines in a database, and save these fingerprints as images. If the user compares his/her wine fingerpr

Software being developed today can have years worth of history and hundreds if notthousands of files involved in a single project. When trying to determine what parts ofthe code need maintenance or updating it can be difficult to determine what will beproblematic in the future. Hours spent on code that will not cause problems in thefuture could be better used in other areas. Before changes are made to a codebase, themost error-prone parts of the code should be identified. In this thesis a method forcomparing what factors contribute to future bugs is developed, as well as testing severalfactors extracted from version control metadata using this method. In addition, avisualization was made using tree maps to show the most problematic files in a readablemanner, effectively using the produced data in an application to predict future bugs. Itwas determined that Age of newest change, Changes with age reducing importance andPrevious bugfixes with age reducing importance were all the most impactful factors forpredicting future bugs but that different repositories worked best with differentcombinations of the mentioned factors.

Time-dependently changing hierarchical data structures are commonly visualized with animated treemaps. Changes in the data structure produce correlated changes in the animation. While previous treemap animations exclusively consider hierarchical data where only the size of the data points are time-dependently changing, we present a novel method for animating treemaps where the hierarchy of the data structure is also evolving. A change in the hierarchy is referred to as a topological event of the animated treemap. Furthermore, animation stability is a quantitative indicator as to the visual quality of treemap animations. With the proposed method, the stability of animated Slice-and-Dice treemaps is maximized during topological events. Thus, the method produces topologically evolving Slice-and-Dice treemap animations of high visual quality. Inspiration for the proposed method was largely drawn from Köpp and Weinkauf’s recent work on the ordered visualization of time-dependently evolving nested graphs. The research question regarded whether their treemap method for spatially ordering hierarchical data could be translated to the 2D treemap space, in order to optimize the stability of animated Slice-and-Dice layouts. This study does not only report on the development of the proposed method, but also present an accompanying experimental evaluation. While evidence show that the proposed method is incapable of entirely mitigating decreasing stability scores, caused by any possible topological event in an evolving Slice-and-Dice hierarchy, the success of the proposed method has been proven for the most frequent topological events. / Tidsberoende förändringar i hierarkiska datastrukturer visualiseras ofta med animerade trädkartor (efter engelskans treemap). Förändringar i datastrukturen producerar korrelerade förändringar i animationen. Medan tidigare trädkartsanimationer sett till hierarkisk data där endast storleken på datapunkterna förändras över tid, så presenterar vi en ny metod för animation av trädkartor där även datastrukturens hierarki förändras. En förändring av hierarkin kallas för en topologisk händelse i den animerade trädkartan. Animationsstabilitet är vidare en kvantitativ indikator för animerade trädkartors visuella kvalitet. Med den föreslagna metoden så har stabiliteten av animerade Slice-and-Dice-trädkartor optimerats under topologiska händelser. Metoden producerar följaktligen topologiskt föränderliga Slice-and-Dice-animationer med hög visuell kvalitet. Studien har huvudsakligen inspirerats av Köpp och Weinkaufs arbete med den sorterade visualiseringen av tidsföränderliga, nästlade grafer. Forskningsfrågan gällde huruvida deras metod för att ordna den hierarkiska datan kunde översättas till trädkartors tvådimensionella rymd, för att i ett vidare steg optimera stabiliteten av animerade Slice-and-Dice-trädkartor. Studien rapporterar ej enbart om utvecklingen av den föreslagna metoden, utan presenterar även en medföljande experimentell utvärdering. Medan man ur bevisen kan utläsa att metoden ej fullständigt kan mildra minskningar i animationsstabilitet, orsakat av alla de möjliga topologiska händelser som kan ske i en föränderlig Slice-and-Dice-hierarki, så har den föreslagna metoden varit framgångsrik i de mest frekventa fallen.

The goal of this term project is create user friendly client of Twitter. They may use methods of machine learning as naive bayes classifier to mentions new interests tweets. For visualissation this tweets will be use hyperbolic trees and some others methods.