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Joshua Hoeflich

dblp:334/4355 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2025
0000-0001-7867-6113ORCID · corroborated

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

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

Software engineering, system software, and programming languages
1 paper
Program analysis · 61% Software testing · 30% Software maintenance and evolution · 9%
Human-computer interaction and pervasive computing
1 paper
Accessibility and assistive technology · 77% User interface design and tools · 23%

Topics — the 4 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program analysis
static analysis
0.612022
Highly illogical, Kirk: spotting type mismatches in the large despite broken contracts, unsound types, and too many linters · Proc. ACM Program. Lang. 2022
Software testing
test suite evaluation
0.612022
Highly illogical, Kirk: spotting type mismatches in the large despite broken contracts, unsound types, and too many linters · Proc. ACM Program. Lang. 2022
Program analysis › type analysis
type error detection
0.612022
Highly illogical, Kirk: spotting type mismatches in the large despite broken contracts, unsound types, and too many linters · Proc. ACM Program. Lang. 2022
Software maintenance and evolution
software ecosystems
0.212022
Highly illogical, Kirk: spotting type mismatches in the large despite broken contracts, unsound types, and too many linters · Proc. ACM Program. Lang. 2022

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

within-subject user study · 0.9dynamic analysis · 0.6contract installation · 0.6
YearPublicationVenuePosition
2025 FormA11y - Research and Development of a Tool for Remediating PDF Forms for Accessibility
abstract
PDF documents are usually not born-accessible, and so document authors need to put in additional work (remediation) to make them accessible for people with disabilities. Unfortunately, this step is often overlooked and hard to execute, resulting in a large number of inaccessible PDF documents on the internet. Previously, there have been research efforts to investigate potential solutions for remediating PDF documents for accessibility. However, most of the existing research focuses on accessibility of long or scientific PDF documents meant for passive reading. PDF documents come in different types, and this research project focuses on a distinct type of PDF document-forms-where the user is required to interact with the PDF document and enter data. Through our research work we identified that the PDF form remediation process is non-intuitive, repetitive, and overwhelming due to the high-information density of PDF forms, and existing research and tools do not yet address the challenges. Our research work culminated in the creation of a tool - FormA11y - that addresses these challenges by making the repetitive and painstaking process of form remediation easier. To evaluate the effectiveness and efficiency of FormA11y against the industry standard tool - Adobe Acrobat - for PDF form remediation, we performed a within-subject user study with 20 participants. With FormA11y, users remediated forms 2.8 times faster while creating more accurately accessible PDF forms.
Sparsh Paliwal, Joshua Hoeflich, J. Bern Jordan, Rajiv Jain, Vlad I. Morariu, Alexa F. Siu, Jonathan Lazar
ACM Trans. Comput. Hum. Interact.2
2022 Highly illogical, Kirk: spotting type mismatches in the large despite broken contracts, unsound types, and too many linters
abstract
The DefinitelyTyped repository hosts type declarations for thousands of JavaScript libraries. Given the lack of formal connection between the types and the corresponding code, a natural question is are the types right? An equally important question, as DefinitelyTyped and the libraries it supports change over time, is how can we keep the types from becoming wrong? In this paper we offer Scotty, a tool that detects mismatches between the types and code in the Definitely-Typed repository. More specifically, Scotty checks each package by converting its types into contracts and installing the contracts on the boundary between the library and its test suite. Running the test suite in this environment can reveal mismatches between the types and the JavaScript code. As automation and generality are both essential if such a tool is going to remain useful in the long term, we focus on techniques that sacrifice completeness, instead preferring to avoid false positives. Scotty currently handles about 26% of the 8006 packages on DefinitelyTyped (61% of the packages whose code is available and whose test suite passes). Perhaps unsurprisingly, running the tests with these contracts in place revealed many errors in Definitely-Typed. More surprisingly, despite the inherent limitations of the techniques we use, this exercise led to one hundred accepted pull requests that fix errors in DefinitelyTyped, demonstrating the value of this approach for the long-term maintenance of DefinitelyTyped. It also revealed a number of lessons about working in the JavaScript ecosystem and how details beyond the semantics of the language can be surprisingly important. Best of all, it also revealed a few places where programmers preferred incorrect types, suggesting some avenues of research to improve TypeScript.
Joshua Hoeflich, Robert Bruce Findler, Manuel Serrano
Proc. ACM Program. Lang.1