The garnet user interface development environment

Myers, Brad A.; Giuse, Dario A.; Mickish, Andrew; Zanden, Brad Vander; Kosbie, David S.; McDaniel, Richard G.; Landay, James A.; Golderg, Matthews; Pathasarathy, Rajan

doi:10.1145/259963.260472

Cited by 5 publications

(3 citation statements)

References 2 publications

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“…The literature presents requirements to program and understand interactive systems (Suchman, 1987;Myers, 1994;Ko and Myers, 2004;Victor, 2012;Schmidt and Bansler, 2016;Hornbaek and Oulasvirta, 2017;Basman et al, 2018), studies the specific challenges encountered by programmers (Hill, 1986;Myers, 1991;Myers et al, 1994;Myers, 1994;Myers et al, 2000;Casiez and Roussel, 2011;Bainomugisha et al, 2013;Salvaneschi et al, 2015) and introduces diverse models to help programmers reason about their programs (Dearden and Harrison, 1997;Campos and Harrison, 1997;Navarre et al, 2006Navarre et al, , 2009Canny et al, 2019). However, some HCI researchers note that the appropriate level of abstraction to account for interactive systems is still missing:…”

Section: The Engineering Of Interactive Systemsmentioning

confidence: 99%

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Computers as Interactive Machines: Can We Build an Explanatory Abstraction?

2023

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In this paper, we address the question of what current computers are from the point of view of human-computer interaction. In the early days of computing, the Turing machine (TM) has been the cornerstone of the understanding of computers. The TM defines what can be computed and how computation can be carried out. However, in the last decades, computers have evolved and increasingly become interactive systems, reacting in real-time to external events in an ongoing loop. We argue that the TM does not provide a mechanistic explanation for interactive computing. The reason is that the fundamental phenomena relevant to interactive computing are out of the scope of classical computability theory. Part of the explanatory power of the TM relies on what we propose to call an execution model. An execution model belongs to a level of abstraction where it is possible to describe both the functional architecture and the execution in mechanistic terms. An updated execution model is warranted to provide the minimal mechanistic description for interactive computation as a counterpart of what the TM could explain regarding Church-Turing computation. It would support an explanation of the ubiquitous computing devices we know -those interacting with humans, e.g., through digital interfaces. We show that such a model is not available within interactive models of computation and that relevant abstractions and concerns are available in computer engineering but need to be identified and gathered. To fill this void, we propose to reflect on the level of abstractionrequired to support the mechanistic description of an interactive execution and propose some preliminary requirements.

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Section: The Engineering Of Interactive Systemsmentioning

confidence: 99%

“…The causal vocabulary is pervasive in the literature when describing an interactive system: (Myers et al, 1994;Jacob et al, 1999;Ko and Myers, 2004;Myers, 2013;Leveson, 2020). The possibility of such causal relationships between processes is the mechanism to explain.…”

Section: Expressing Causal Relationshipsmentioning

confidence: 99%

Computers as Interactive Machines: Can We Build an Explanatory Abstraction?

2023

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“…There has been extensive research in automatic layout using design grids [10,14,17,23], machine learning [4,25,30,34], evaluation techniques [8,9,18,28,29,31], and constraint solvers [1,4,6,7,11,12,13,19,24,32,33], including those that adhere to aesthetic design criteria [21,27]. (See Lok and Feiner [20] for a survey of this work.…”

Section: Automatic Layoutmentioning

confidence: 99%

Content-aware layout

Ishak

Feiner

2007

CHI '07 Extended Abstracts on Human Factors in Computing Systems

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We describe content-aware layout (CAL), a technique that automatically arranges windows on a user's desktop. Unlike conventional window managers that automatically cascade or tile each window without regard to its content, CAL uses information about the contents of windows to help decide if and where they should be placed. We present the approach to designing CAL, as well as its implementation. We then conclude with a discussion about future work and CAL's potential use in large display environments.

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