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Daniel Dickstein

dblp:375/7362 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0001-5706-6815ORCID · reported

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

Software engineering, systems software and programming languages · 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
Software testing · 50% Empirical software engineering · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Empirical software engineering
developer studies
0.812024
Property-Based Testing in Practice · ICSE 2024
Software testing › random testing
property-based testing
0.812024
Property-Based Testing in Practice · ICSE 2024

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

survey · 0.8interview study · 0.8
YearPublicationVenuePosition
2024 Property-Based Testing in Practice
abstract
Property-based testing (PBT) is a testing methodology where users write executable formal specifications of software components and an automated harness checks these specifications against many automatically generated inputs. From its roots in the QuickCheck library in Haskell, PBT has made significant inroads in mainstream languages and industrial practice at companies such as Amazon, Volvo, and Stripe. As PBT extends its reach, it is important to understand how developers are using it in practice, where they see its strengths and weaknesses, and what innovations are needed to make it more effective.
Harrison Goldstein, Joseph W. Cutler, Daniel Dickstein, Benjamin C. Pierce, Andrew Head
ICSE3