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Author

John Stasko

Other affiliations: University of Wisconsin-Madison
Bio: John Stasko is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Visualization & Information visualization. The author has an hindex of 66, co-authored 283 publications receiving 17229 citations. Previous affiliations of John Stasko include University of Wisconsin-Madison.


Papers
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Proceedings ArticleDOI
19 May 2002
TL;DR: A new technique that uses color to visually map the participation of each program statement in the outcome of the execution of the program with a test suite, consisting of both passed and failed test cases is presented.
Abstract: One of the most expensive and time-consuming components of the debugging process is locating the errors or faults. To locate faults, developers must identify statements involved in failures and select suspicious statements that might contain faults. This paper presents a new technique that uses visualization to assist with these tasks. The technique uses color to visually map the participation of each program statement in the outcome of the execution of the program with a test suite, consisting of both passed and failed test cases. Based on this visual mapping, a user can inspect the statements in the program, identify statements involved in failures, and locate potentially faulty statements. The paper also describes a prototype tool that implements our technique along with a set of empirical studies that use the tool for evaluation of the technique. The empirical studies show that, for the subject we studied, the technique can be effective in helping a user locate faults in a program.

1,063 citations

Journal ArticleDOI
TL;DR: Seven general categories of interaction techniques widely used in Infovis are proposed, organized around a user's intent while interacting with a system rather than the low-level interaction techniques provided by a system.
Abstract: Even though interaction is an important part of information visualization (Infovis), it has garnered a relatively low level of attention from the Infovis community. A few frameworks and taxonomies of Infovis interaction techniques exist, but they typically focus on low-level operations and do not address the variety of benefits interaction provides. After conducting an extensive review of Infovis systems and their interactive capabilities, we propose seven general categories of interaction techniques widely used in Infovis: 1) Select, 2) Explore, 3) Reconfigure, 4) Encode, 5) Abstract/Elaborate, 6) Filter, and 7) Connect. These categories are organized around a user's intent while interacting with a system rather than the low-level interaction techniques provided by a system. The categories can act as a framework to help discuss and evaluate interaction techniques and hopefully lay an initial foundation toward a deeper understanding and a science of interaction.

1,018 citations

Journal ArticleDOI
TL;DR: How students use AV technology has a greater impact on effectiveness than what AV technology shows them, and an agenda for future research into AV effectiveness is formulated.
Abstract: Algorithm visualization (AV) technology graphically illustrates how algorithms work. Despite the intuitive appeal of the technology, it has failed to catch on in mainstream computer science education. Some have attributed this failure to the mixed results of experimental studies designed to substantiate AV technology's educational effectiveness. However, while several integrative reviews of AV technology have appeared, none has focused specifically on the software's effectiveness by analyzing this body of experimental studies as a whole. In order to better understand the effectiveness of AV technology, we present a systematic meta-study of 24 experimental studies. We pursue two separate analyses: an analysis ofindependent variables , in which we tie each study to a particular guiding learning theory in an attempt to determine which guiding theory has had the most predictive success; and an analysis of dependent variables, which enables us to determine which measurement techniques have been most sensitive to the learning benefits of AV technology. Our most significant finding is that how students use AV technology has a greater impact on effectiveness than what AV technology shows them. Based on our findings, we formulate an agenda for future research into AV effectiveness.

646 citations

Proceedings ArticleDOI
23 Oct 2005
TL;DR: This work presents a set of ten low level analysis tasks that largely capture people's activities while employing information visualization tools for understanding data, and hopes that the tasks may provide a form of checklist for system designers.
Abstract: Existing system level taxonomies of visualization tasks are geared more towards the design of particular representations than the facilitation of user analytic activity We present a set of ten low level analysis tasks that largely capture people's activities while employing information visualization tools for understanding data To help develop these tasks, we collected nearly 200 sample questions from students about how they would analyze five particular data sets from different domains The questions, while not being totally comprehensive, illustrated the sheer variety of analytic questions typically posed by users when employing information visualization systems We hope that the presented set of tasks is useful for information visualization system designers as a kind of common substrate to discuss the relative analytic capabilities of the systems Further, the tasks may provide a form of checklist for system designers

615 citations

Journal ArticleDOI
TL;DR: The first-fit bin-packing algorithm is animated to illustrate how the path-transition paradigm simplifies algorithm animation.
Abstract: The role of animation in understanding and evaluating programs and developing new programs is discussed. A framework for algorithm animation, called Tango, and a system based on that framework are introduced. Related work is reviewed, and the conceptual framework on which Tango is based is examined. The implementation of the Tango system is described. The first-fit bin-packing algorithm is animated to illustrate how the path-transition paradigm simplifies algorithm animation. >

496 citations


Cited by
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Journal ArticleDOI
TL;DR: Reading a book as this basics of qualitative research grounded theory procedures and techniques and other references can enrich your life quality.

13,415 citations

Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations

01 Jan 2002

9,314 citations

Proceedings ArticleDOI
03 Sep 1996
TL;DR: A task by data type taxonomy with seven data types and seven tasks (overview, zoom, filter, details-on-demand, relate, history, and extracts) is offered.
Abstract: A useful starting point for designing advanced graphical user interfaces is the visual information seeking Mantra: overview first, zoom and filter, then details on demand. But this is only a starting point in trying to understand the rich and varied set of information visualizations that have been proposed in recent years. The paper offers a task by data type taxonomy with seven data types (one, two, three dimensional data, temporal and multi dimensional data, and tree and network data) and seven tasks (overview, zoom, filter, details-on-demand, relate, history, and extracts).

5,290 citations

01 Jan 2012

3,692 citations