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Parker Ziegler

dblp:344/8771 · DBLP profile ↗
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4ranked-venue papers
2as first author
4since 2021 · last 2025
0000-0001-9462-2123ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2 · 1 first-author · 2 since 2021Human-computer interaction and ubiquitous computing · 2 · 1 first-author · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
2 papers
Visualization and visual analytics · 100%
Human-computer interaction and pervasive computing
2 papers
User interface design and tools · 100%
Software engineering, system software, and programming languages
1 paper
Program synthesis and code generation · 100%
Theoretical computer science
1 paper
Logic in computer science · 100%
Databases, data mining, and information retrieval
1 paper
Data integration and cleaning · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational science and engineering · 100%

Topics — the 6 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics
geospatial visualization
1.522025
Fast Direct Manipulation Programming with Patch-Reconciliation Correspondence · Proc. ACM Program. Lang. 2025
A Need-Finding Study with Users of Geospatial Data · CHI 2023
Visualization and visual analytics › interactive visualization
incremental visualization
0.912025
Fast Direct Manipulation Programming with Patch-Reconciliation Correspondence · Proc. ACM Program. Lang. 2025
User interface design and tools › visual programming
direct manipulation programming
0.912025
Fast Direct Manipulation Programming with Patch-Reconciliation Correspondence · Proc. ACM Program. Lang. 2025
User interface design and tools
end-user programming
0.912025
HiLT: A Library for Generating Human-in-the-Loop Data Transformation GUIs · UIST 2025
Program synthesis and code generation › type-directed synthesis
type inhabitation
0.912025
Programming by Navigation · Proc. ACM Program. Lang. 2025
Data integration and cleaning
data transformation
0.312025
HiLT: A Library for Generating Human-in-the-Loop Data Transformation GUIs · UIST 2025

Methods — techniques the papers use, named apart from their topics

type inhabitation oracle · 1.7patch-reconciliation correspondence · 1.7forward evaluation · 1.7datalog · 1.7thematic analysis · 1.3contextual inquiry · 1.3
YearPublicationVenuePosition
2025 HiLT: A Library for Generating Human-in-the-Loop Data Transformation GUIs
Sora Kanosue, Parker Ziegler, Eric Rawn, Sarah E. Chasins
UIST3
2025 Programming by Navigation
abstract
When a program synthesis task starts from an ambiguous specification, the synthesis process often involves an iterative specification refinement process. We introduce the Programming by Navigation Synthesis Problem, a new synthesis problem adapted specifically for supporting iterative specification refinement in order to find a particular target solution. In contrast to prior work, we prove that synthesizers that solve the Programming by Navigation Synthesis Problem show all valid next steps ( Strong Completeness ) and only valid next steps ( Strong Soundness ). To meet the demands of the Programming by Navigation Synthesis Problem, we introduce an algorithm to turn a type inhabitation oracle (in the style of classical logic) into a fully constructive program synthesizer.We then define such an oracle via sound compilation to Datalog. Our empirical evaluation shows that this technique results in an efficient Programming by Navigation synthesizer that solves tasks that are either impossible or too large for baselines to solve. Our synthesizer is the first to guarantee that its specification refinement process satisfies both Strong Completeness and Strong Soundness .
Justin Lubin, Parker Ziegler, Sarah E. Chasins
Proc. ACM Program. Lang.2
2025 Fast Direct Manipulation Programming with Patch-Reconciliation Correspondence
abstract
Direct manipulation programming gives users a way to write programs without directly writing code, by using the familiar GUI-style interactions they know from direct manipulation interfaces. To date, direct manipulation programming systems have relied on two core components: (1) a patch component, which modifies the program based on a GUI interaction, and (2) a forward evaluator , which executes the modified program to produce an updated program output. This architecture has worked for developing short-running programs—i.e., programs that reliably execute in <1 second—generating outputs such as SVG and HTML documents. However, direct manipulation programming has not yet been applied to long-running programs (e.g., data visualization, mapping), perhaps because executing such programs in response to every GUI interaction would mean crossing outside of interactive speeds. We propose extending direct manipulation programming to long-running programs by pairing a standard patch component ( patch ) with a corresponding reconciliation component ( recon ). recon directly updates the program output in response to a GUI interaction, obviating the need for forward evaluation. We introduce corresponding patch and recon procedures for the domain of geospatial data visualization and prove them sound—that is, we show that the output produced by recon is identical to the output produced by forward-evaluating a patch -modified program. recon can operate both incrementally and in parallel with patch . Our implementation of our patch - recon instantiation achieves a 2.92× median reduction in interface latency compared to forward evaluation on a suite of real-world geospatial visualization tasks. Looking forward, our results suggest that patch-reconciliation correspondence offers a promising pathway for extending direct manipulation programming to domains involving large-scale computation.
Parker Ziegler, Justin Lubin, Sarah E. Chasins
Proc. ACM Program. Lang.1
2023 A Need-Finding Study with Users of Geospatial Data
abstract
Geospatial data is playing an increasingly critical role in the work of Earth and climate scientists, social scientists, and data journalists exploring spatiotemporal change in our environment and societies. However, existing software and programming tools for geospatial analysis and visualization are challenging to learn and difficult to use. The aim of this work is to identify the unmet computing needs of the diverse and expanding community of geospatial data users. We conducted a contextual inquiry study (n = 25) with domain experts using geospatial data in their current work. Through a thematic analysis, we found that participants struggled to (1) find and transform geospatial data to satisfy spatiotemporal constraints, (2) understand the behavior of geospatial operators, (3) track geospatial data provenance, and (4) explore the cartographic design space. These findings suggest design opportunities for developers and designers of geospatial analysis and visualization systems.
Parker Ziegler, Sarah E. Chasins
CHI1