Task-Centric User Interfaces

Software applications for design and creation typically contain hundreds or thousands of commands, which collectively give users enormous expressive power. Unfortunately, rich feature sets also take a toll on usability. Current interfaces to feature-rich software address this dilemma by adopting menus, toolbars, and other hierarchical schemes to organize functionality—approaches that enable efficient navigation to specific commands and features, but do little to reveal how to perform unfamiliar tasks. We present an alternative task-centric user interface design that explicitly supports users in performing unfamiliar tasks. A task-centric interface is able to quickly adapt itself to the user’s intended goal, presenting relevant functionality and required procedures in task-specific customized interfaces. To achieve this, task-centric interfaces (1) represent tasks as first-class objects in the interface; (2) allow the user to declare their intended goal (or infer it from the user’s actions); (3) restructure the interface to provide step-by-step scaffolding for the current goal; and (4) provide additional knowledge and guidance within the application’s interface. Our inspiration for task-centric interfaces comes from a study we conducted, which revealed that a valid use case for feature-rich software is to perform short, targeted tasks that use a small fraction of the application’s full functionality. Task-centric interfaces provide explicit support for this use. We developed and tested our task-centric interface approach by creating AdaptableGIMP, a modified version of the GIMP image editor, and Workflows, an iteration on AdaptableGIMP’s design based on insights from a semi-structured interview study and a think-aloud study. Based on a two-session study of Workflows, we show that task-centric interfaces can successfully support a guided-and-constrained problem solving strategy for performing unfamiliar tasks, which enables faster task completion and reduced cognitive load as compared to current practices. We also provide evidence that task-centric interfaces can enable a higher-level form of application learning, in which the user associates tasks with relevant keywords, as opposed to low-level commands and procedures. This keyword learning has potential benefits for memorability, because the keywords themselves are descriptive of the task being learned, and scalability, because a few keywords can map to an arbitrarily complex set of commands and procedures. Finally, our findings suggest a range of different ways that the idea of task-centric interfaces could be further developed

Design and Implementation of a Conceptual Modeling Assistant (CMA)

This Master's Thesis de nes an architecture for a Conceptual Modeling Assistant (CMA) along with an implementation of a running prototype. Our CMA is a piece of software that runs on top of current modeling tools whose purpose is to collaborate with the conceptual modelers while developing a conceptual schema. The main functions of our CMA are to actively criticize the state of a conceptual schema, to suggest actions to do in order to improve the conceptual schema, and to o er new operations to automatize building a schema. On the one hand, the presented architecture assumes that the CMA has to be adapted to a modeling tool. Thus, the CMA permits the inclusion of new features, such as the detection of new defects to be criticized and new operations a modeler can execute, in a modeling tool. As a result, all modeling tools to which the CMA is adapted bene t of all these features without further work. On the other hand, the construction of our prototype involves three steps: the de nition of a simple, custom modeling tool; the implementation of the CMA; and the adaptation of the CMA to the custom modeling tool. Furthermore, we also present and implement some examples of new features that can be added to the CMA

Fault tolerant software technology for distributed computing system

Issued as Monthly reports [nos. 1-23], Interim technical report, Technical guide books [nos. 1-2], and Final report, Project no. G-36-64

User Interface Management Systems: A Survey and a Proposed Design

The growth of interactive computing has resulted in increasingly more complex styles of interaction between user and computer. To facilitate the creation of highly interactive systems, the concept of the User Interface Management System (UIMS) has been developed. Following the definition of the term 'UIMS' and a consideration of the putative advantages of the UIMS approach, a number of User Interface Management Systems are examined. This examination focuses in turn on the run-time execution system, the specification notation and the design environment, with a view to establishing the features which an "ideal" UIMS should possess. On the basis of this examination, a proposal for the design of a new UIMS is presented, and progress reported towards the implementation of a prototype based on this design

Analysis and implementation of the software for personal sports records

Fyzická aktivita plní niekoľko dôležitých benefitov pri udržiavaní dobrého zdravia, prevencii voči chronických ochoreniam a má pozitívny vplyv na duševné zdravie a celkovú kvalitu života. Táto diplomová práca sa zaoberá touto problematikou. Cieľom diplomovej práce je pochopiť koncept fyzickej aktivity ako takej, preskúmať existujúce riešenia na trhu a vytvoriť špecifikáciu požiadaviek. Súčasťou je návrh architektúry a implementácia webovej aplikácie s ohľadom na použiteľnosť. Navrhnutá aplikácia podporuje fyzickú aktivitu a je pripravená pre jej ďalšie rozšírenie.Physical activity has important benefits in maintaining good health, preventing chronic diseases and it has a positive impact on a mental health and an overall quality of the life. This diploma thesis deals with this issue. The objectives of the thesis are to understand a construct of the physical activity, to make a research of existing solutions on the market and to collect a requirement specification. Consequently, a design and implementation of the web application in a respect of the usability is provided. The proposed application encourages to perform a physical activity and it can potentially be further developed

Generative Mesh Modeling

Generative Modeling is an alternative approach for the description of three-dimensional shape. The basic idea is to represent a model not as usual by an agglomeration of geometric primitives (triangles, point clouds, NURBS patches), but by functions. The paradigm change from objects to operations allows for a procedural representation of procedural shapes, such as most man-made objects. Instead of storing only the result of a 3D construction, the construction process itself is stored in a model file. The generative approach opens truly new perspectives in many ways, among others also for 3D knowledge management. It permits for instance to resort to a repository of already solved modeling problems, in order to re-use this knowledge also in different, slightly varied situations. The construction knowledge can be collected in digital libraries containing domain-specific parametric modeling tools. A concrete realization of this approach is a new general description language for 3D models, the "Generative Modeling Language" GML. As a Turing-complete "shape programming language" it is a basis of existing, primitv based 3D model formats. Together with its Runtime engine the GML permits - to store highly complex 3D models in a compact form, - to evaluate the description within fractions of a second, - to adaptively tesselate and to interactively display the model, - and even to change the models high-level parameters at runtime.Die generative Modellierung ist ein alternativer Ansatz zur Beschreibung von dreidimensionaler Form. Zugrunde liegt die Idee, ein Modell nicht wie üblich durch eine Ansammlung geometrischer Primitive (Dreiecke, Punkte, NURBS-Patches) zu beschreiben, sondern durch Funktionen. Der Paradigmenwechsel von Objekten zu Geometrie-erzeugenden Operationen ermöglicht es, prozedurale Modelle auch prozedural zu repräsentieren. Statt das Resultat eines 3D-Konstruktionsprozesses zu speichern, kann so der Konstruktionsprozess selber repräsentiert werden. Der generative Ansatz eröffnet unter anderem gänzlich neue Perspektiven für das Wissensmanagement im 3D-Bereich. Er ermöglicht etwa, auf einen Fundus bereits gelöster Konstruktions-Aufgaben zurückzugreifen, um sie in ähnlichen, aber leicht variierten Situationen wiederverwenden zu können. Das Konstruktions-Wissen kann dazu in Form von Bibliotheken parametrisierter, Domänen-spezifischer Modellier-Werkzeuge gesammelt werden. Konkret wird dazu eine neue allgemeine Modell-Beschreibungs-Sprache vorgeschlagen, die "Generative Modeling Language" GML. Als Turing-mächtige "Programmiersprache für Form" stellt sie eine echte Verallgemeinerung existierender Primitiv-basierter 3D-Modellformate dar. Zusammen mit ihrer Runtime-Engine erlaubt die GML, - hochkomplexe 3D-Objekte extrem kompakt zu beschreiben, - die Beschreibung innerhalb von Sekundenbruchteilen auszuwerten, - das Modell adaptiv darzustellen und interaktiv zu betrachten, - und die Modell-Parameter interaktiv zu verändern

Managing configuration history in domestic networks

Domestic Networks are gaining in complexity, with an increasing number and variety of devices. Increasing complexity results in greater difficulty managing configuration and troubleshooting when problems occur. This thesis presents strategies to assist users in managing the complexity of their networks. The work is split into several parts. First, configuration changes are tracked and users are presented with a timeline of changes to their network. Provision of a selective undo system is the second feature. The undo facility is designed to allow any change to be undone independently of any other. Users are also given the option of reverting to an earlier point, either before a specific change, or to a specific timestamp. The next feature is use of notifications. Any changes that require further actions can be broadcast to users directly. Changing Wi-Fi configuration is one example. The range of devices in use makes changing Wi-Fi configuration (and the subsequent reconfiguration of devices) a challenge, because the devices affected may be part of the infrastructure of a home (lights or thermostat for example). Because these devices have unique methods of network setup, restoring connectivity to every device can be challenging. This thesis also presents a method of changing Wi-Fi configuration which allows users a grace period to reconnect all their devices. Each of these features was assessed by a user study, the results of which are also discussed

Code generation based on inference and controlled natural language input

Over time the level of abstraction embodied in programming languages has continued to grow. Paradoxically, most programming languages still require programmers to conform to the language\u27s rigid constructs. These constructs have been implemented in the name of efficiency for the computer. However, the continual increase in computing power allows us to consider techniques not so limited. To this end, we have created CABERNET, a Controlled Natural Language (CNL) based approach to program creation. CABERNET allows programmers to use a simple outline-based syntax. This syntax enables increased programmer efficiency. CNLs have previously been used to document requirements. We have taken this approach beyond the typical application of creating requirements documents to creating functional programs. Using heuristics and inference to analyze and determine the programmer\u27s intent, the CABERNET toolchain can create functional mobile applications. This approach allows programs to align with how humans think rather than how computers process information. Using customizable templates, a CABERNET application can be processed to run on multiple run-time environments. Since processing a CABERNET program file results in a native application program, performance is maintained. This research explores whether a CNL-based programming tool can provide a readable, flexible, extensible, and easy-to-learn development methodology. To answer this question, we compared sample applications created in Swift, SwiftUI, and a prototype of the CABERNET toolchain. The CABERNET implementations were consistently shorter than those produced in the other two languages. In addition, users surveyed consistently found the CABERNET samples easier to understand

Extending Complex Event Processing for Advanced Applications

Recently numerous emerging applications, ranging from on-line financial transactions, RFID based supply chain management, traffic monitoring to real-time object monitoring, generate high-volume event streams. To meet the needs of processing event data streams in real-time, Complex Event Processing technology (CEP) has been developed with the focus on detecting occurrences of particular composite patterns of events. By analyzing and constructing several real-world CEP applications, we found that CEP needs to be extended with advanced services beyond detecting pattern queries. We summarize these emerging needs in three orthogonal directions. First, for applications which require access to both streaming and stored data, we need to provide a clear semantics and efficient schedulers in the face of concurrent access and failures. Second, when a CEP system is deployed in a sensitive environment such as health care, we wish to mitigate possible privacy leaks. Third, when input events do not carry the identification of the object being monitored, we need to infer the probabilistic identification of events before feed them to a CEP engine. Therefore this dissertation discusses the construction of a framework for extending CEP to support these critical services. First, existing CEP technology is limited in its capability of reacting to opportunities and risks detected by pattern queries. We propose to tackle this unsolved problem by embedding active rule support within the CEP engine. The main challenge is to handle interactions between queries and reactions to queries in the high-volume stream execution. We hence introduce a novel stream-oriented transactional model along with a family of stream transaction scheduling algorithms that ensure the correctness of concurrent stream execution. And then we demonstrate the proposed technology by applying it to a real-world healthcare system and evaluate the stream transaction scheduling algorithms extensively using real-world workload. Second, we are the first to study the privacy implications of CEP systems. Specifically we consider how to suppress events on a stream to reduce the disclosure of sensitive patterns, while ensuring that nonsensitive patterns continue to be reported by the CEP engine. We formally define the problem of utility-maximizing event suppression for privacy preservation. We then design a suite of real-time solutions that eliminate private pattern matches while maximizing the overall utility. Our first solution optimally solves the problem at the event-type level. The second solution, at event-instance level, further optimizes the event-type level solution by exploiting runtime event distributions using advanced pattern match cardinality estimation techniques. Our experimental evaluation over both real-world and synthetic event streams shows that our algorithms are effective in maximizing utility yet still efficient enough to offer near real time system responsiveness. Third, we observe that in many real-world object monitoring applications where the CEP technology is adopted, not all sensed events carry the identification of the object whose action they report on, so called €œnon-ID-ed€� events. Such non-ID-ed events prevent us from performing object-based analytics, such as tracking, alerting and pattern matching. We propose a probabilistic inference framework to tackle this problem by inferring the missing object identification associated with an event. Specifically, as a foundation we design a time-varying graphic model to capture correspondences between sensed events and objects. Upon this model, we elaborate how to adapt the state-of-the-art Forward-backward inference algorithm to continuously infer probabilistic identifications for non-ID-ed events. More important, we propose a suite of strategies for optimizing the performance of inference. Our experimental results, using large-volume streams of a real-world health care application, demonstrate the accuracy, efficiency, and scalability of the proposed technology