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Ishan Bhanuka

dblp:362/5991 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2023
0000-0002-7000-6534ORCID · reported

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 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
Programming languages and type systems · 100%

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

TopicWeightPapersLastEvidence papers
Programming languages and type systems › type checking
type error messages
0.712023
Getting into the Flow: Towards Better Type Error Messages for Constraint-Based Type Inference · Proc. ACM Program. Lang. 2023
Programming languages and type systems
type inference
0.712023
Getting into the Flow: Towards Better Type Error Messages for Constraint-Based Type Inference · Proc. ACM Program. Lang. 2023
Programming languages and type systems
type systems
0.712023
Getting into the Flow: Towards Better Type Error Messages for Constraint-Based Type Inference · Proc. ACM Program. Lang. 2023
Programming languages and type systems › type inference
hindley-milner type inference
0.212023
Getting into the Flow: Towards Better Type Error Messages for Constraint-Based Type Inference · Proc. ACM Program. Lang. 2023

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

user study · 0.7constraint solving · 0.7
YearPublicationVenuePosition
2023 Getting into the Flow: Towards Better Type Error Messages for Constraint-Based Type Inference
abstract
Creating good type error messages for constraint-based type inference systems is difficult. Typical type error messages reflect implementation details of the underlying constraint-solving algorithms rather than the specific factors leading to type mismatches. We propose using subtyping constraints that capture data flow to classify and explain type errors. Our algorithm explains type errors as faulty data flows, which programmers are already used to reasoning about, and illustrates these data flows as sequences of relevant program locations. We show that our ideas and algorithm are not limited to languages with subtyping, as they can be readily integrated with Hindley-Milner type inference. In addition to these core contributions, we present the results of a user study to evaluate the quality of our messages compared to other implementations. While the quantitative evaluation does not show that flow-based messages improve the localization or understanding of the causes of type errors, the qualitative evaluation suggests a real need and demand for flow-based messages.
Ishan Bhanuka, Lionel Parreaux, David Binder, Jonathan Immanuel Brachthäuser
Proc. ACM Program. Lang.1