Implementing level 4 liveness in declarative visual programming languages

Burnett, Margaret; Atwood, J. William; Welch, Zachary T. Welch

doi:10.1109/vl.1998.706155

Cited by 32 publications

(22 citation statements)

References 13 publications

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“…Solstice removes the burden of creating and maintaining the copy codebase, and relying on external operations from such impure analyses. Similarly, live programming focuses on providing continuous feedback to developers for the tasks they are working on [3,33] by making the behavior of a program visible as that program is being developed [7]. Solstice enables continuous analyses that facilitate live programming practices.…”

Section: Related Workmentioning

confidence: 99%

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Making offline analyses continuous

Muşlu

Brun

Ernst

et al. 2013

Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering

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Developers use analysis tools to help write, debug, and understand software systems under development. A developer's change to the system source code may affect analysis results. Typically, to learn those effects, the developer must explicitly initiate the analysis. This may interrupt the developer's workflow and/or the delay until the developer learns the implications of the change. The situation is even worse for impure analyses -ones that modify the code on which it runs -because such analyses block the developer from working on the code. This paper presents Codebase Replication, a novel approach to easily convert an offline analysis -even an impure one -into a continuous analysis that informs the developer of the implications of recent changes as quickly as possible after the change is made. Codebase Replication copies the developer's codebase, incrementally keeps this copy codebase in sync with the developer's codebase, makes that copy codebase available for offline analyses to run without disturbing the developer and without the developer's changes disturbing the analyses, and makes analysis results available to be presented to the developer.We have implemented Codebase Replication in Solstice, an opensource, publicly-available Eclipse plug-in. We have used Solstice to convert three offline analyses -FindBugs, PMD, and unit testing -into continuous ones. Each conversion required on average 436 NCSL and took, on average, 18 hours. Solstice-based analyses experience no more than 2.5 milliseconds of runtime overhead per developer action.

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Section: Related Workmentioning

confidence: 99%

“…While continuous testing is integrated into Eclipse [27] and IntelliJ [15], Solstice provides a generic framework for converting offline analyses into continuous ones, integrated into the IDE. 7 http://wiki.eclipse.org/FAQ_What_is_a_working_copy%3F…”

Section: Related Workmentioning

confidence: 99%

Making offline analyses continuous

Muşlu

Brun

Ernst

et al. 2013

Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering

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“…Liveness as an attribute of a programming environment seems to have first been studied in the context of visual languages [1] [2]. Visual languages and program visualization attempt to solve a similar problem to the one that liveness addresses, which is the problem of making programming easier by making it easier to understand quickly what a program is doing or supposed to do.…”

Section: B Liveness and Visual Languagesmentioning

confidence: 99%

“…A detailed study of the implementation requirements for achieving level-4 liveness was carried out for declarative visual languages by the leading academic research group on spreadsheet languages [2]. The 1995 release of the computer game "Widget Workshop" [6] marked an important point in the availability of live programming-like systems to the public.…”

Section: A Few Example Systemsmentioning

confidence: 99%

A perspective on the evolution of live programming

Tanimoto

2013

2013 1st International Workshop on Live Programming (LIVE)

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Liveness in programming environments generally refers to the ability to modify a running program. Liveness is one form of a more general class of behaviors by a programming environment that provide information to programmers about what they are constructing. This paper gives a brief historical perspective on liveness and proposes an extension of a hierarchy given in 1990, to now account for even more powerful executionoriented tools for programmers. In addition, while liveness concerns the timeliness of execution feedback, considering a broader array of forms of feedback is helpful both in better understanding liveness and in designing ever more powerful development tools.

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“…Burnett et al [5] survey these languages and detail how they can support live programming efficiently. In contrast, we describe how live programming can be supported in the context of a fully expressive textual, imperative language with standard control flow constructs.…”

Section: Related Workmentioning

confidence: 99%

It's alive! continuous feedback in UI programming

et al. 2013

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Live programming allows programmers to edit the code of a running program and immediately see the effect of the code changes. This tightening of the traditional edit-compile-run cycle reduces the cognitive gap between program code and execution, improving the learning experience of beginning programmers while boosting the productivity of seasoned ones. Unfortunately, live programming is difficult to realize in practice as imperative languages lack welldefined abstraction boundaries that make live programming responsive or its feedback comprehensible.This paper enables live programming for user interface programming by cleanly separating the rendering and non-rendering aspects of a UI program, allowing the display to be refreshed on a code change without restarting the program. A type and effect system formalizes this separation and provides an evaluation model that incorporates the code update step. By putting live programming on a more formal footing, we hope to enable critical and technical discussion of live programming systems.

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Implementing level 4 liveness in declarative visual programming languages

Cited by 32 publications

References 13 publications

Making offline analyses continuous

Making offline analyses continuous

A perspective on the evolution of live programming

It's alive! continuous feedback in UI programming

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