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Dan Bruce

dblp:247/6499 · DBLP profile ↗
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2ranked-venue papers
2as first author
1since 2021 · last 2023
—ORCID · none

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

Software engineering, systems software and programming languages · 2 · 2 first-author · 1 since 2021Artificial intelligence and machine learning · 1 · 1 first-author

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 · 100%

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

TopicWeightPapersLastEvidence papers
Software testing
test generation
0.712023
June: A Type Testability Transformation for Improved ATG Performance · ISSTA 2023
Software testing
testability transformation
0.212023
June: A Type Testability Transformation for Improved ATG Performance · ISSTA 2023

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

search-based testing · 0.7annotation-driven transformation · 0.7
YearPublicationVenuePosition
2023 June: A Type Testability Transformation for Improved ATG Performance
abstract
Strings are universal containers: they are flexible to use, abundant in code, and difficult to test. String-controlled programs are programs that make branching decisions based on string input. Automatically generating valid test inputs for these programs considering only character sequences rather than any underlying string-encoded structures, can be prohibitively expensive. We present June, a tool that enables Java developers to expose any present latent string structure to test generation tools. June is an annotation-driven testability transformation and an extensible library, JuneLib, of structured string definitions. The core JuneLib definitions are empirically derived and provide templates for all structured strings in our test set. June takes lightly annotated source code and injects code that permits an automated test generator (ATG) to focus on the creation of mutable substrings inside a structured string. Using June costs the developer little, with an average of 2.1 annotations per string-controlled class. June uses standard Java build tools and therefore deploys seamlessly within a Java project. By feeding string structure information to an ATG tool, June dramatically reduces wasted effort; branches are effortlessly covered that would otherwise be extremely difficult, or impossible, to cover. This waste reduction both increases and speeds coverage. EvoSuite, for example, achieves the same coverage on June-ed classes in 1 minute, on average, as it does in 9 minutes on the un-June-ed class. These gains increase over time. On our corpus, June-ing a program compresses 24 hours of execution time into ca. 2 hours. We show that many ATG tools can reuse the same June-ed code: a few June annotations, a one-off cost, benefit many different testing regimes.
Dan Bruce, David A. Kelly, Héctor D. Menéndez 0001, Earl T. Barr, David Clark 0001
ISSTA1
2019 Dorylus: An Ant Colony Based Tool for Automated Test Case Generation
Dan Bruce, Héctor D. Menéndez 0001, David Clark 0001
SSBSE1