Suggesting valid hole fits for typed-holes (experience report)

Gissurarson, Matthías Páll

doi:10.1145/3242744.3242760

Cited by 8 publications

(1 citation statement)

References 5 publications

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“…Given these benefits, it is unsurprising that simple assistants like code completion and "hotfix" systems are ubiquitous in modern programming environments, competing in frequency with manual editor actions like code insertion and deletion [7]. There has in turn been substantial research interest [8] in techniques that can synthesize better suggestions, including program synthesis using types [9], examples [10], program sketches [11], edit history [12], demonstrations [13], and logical constraints [14] to generate "hole completions" [15,16].…”

Section: Introductionmentioning

confidence: 99%

An Integrative Human-Centered Architecture for Interactive Programming Assistants

Blinn

Moon

Griffis

et al. 2022

2022 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)

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Programming has become a collaboration between human programmers, who drive intent, and interactive assistants that suggest contextually relevant editor actions. There has been considerable work on suggestion synthesis strategies-from semantic autocomplete to modern program synthesis, repair, and machine learning research. This diversity of contextually viable strategies creates a need for an integrative, human-centered perspective on the problem of programming assistant design that (1) confronts the problem of integrating a variety of synthesis strategies, fed by shared semantic analyses capable of operating on program sketches, and (2) centers the needs of the human programmer: comprehending, comparing, ranking, and filtering suggestions generated by various synthesizers, and in some cases participating in a synthesizer's search by supplying additional expressions of intent. This paper contributes a conceptual architecture and API to guide programming assistant designers as they confront these integration and human-centered design challenges. We then instantiate this architecture with two prototype end-toend assistant designs, both developed for the Hazel programming environment, that emphasize understudied design aspects, namely continuity, explainability, human-in-the-loop synthesis, and the integration of multiple analyses with multiple synthesis strategies.

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