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20112026
most citedGuiding Deep Learning System Testing using Surprise Adequacy

450 citations · 1.8k across the 77 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.SE2022

Similarity-based web element localization for robust test automation

Michel Nass, Emil Alégroth, Robert Feldt +2

Non-robust (fragile) test execution is a commonly reported challenge in GUI-based test automation, despite much research and several proposed solutions. A test script needs to be r…

cs.SE2022★ 1 cited

Automated Black-Box Boundary Value Detection

Felix Dobslaw, Robert Feldt, Francisco de Oliveira Neto

The input domain of software systems can typically be divided into sub-domains for which the outputs are similar. To ensure high quality it is critical to test the software on the…

cs.SE2022★ 2 cited

Test2Vec: An Execution Trace Embedding for Test Case Prioritization

Emad Jabbar, Soheila Zangeneh, Hadi Hemmati +1

Most automated software testing tasks can benefit from the abstract representation of test cases. Traditionally, this is done by encoding test cases based on their code coverage. S…

cs.SE2022★ 11 cited

A Taxonomy of Information Attributes for Test Case Prioritisation: Applicability, Machine Learning

Aurora Ramírez, Robert Feldt, José Raúl Romero

Most software companies have extensive test suites and re-run parts of them continuously to ensure recent changes have no adverse effects. Since test suites are costly to execute,…

cs.SE2022

Cognition in Software Engineering: A Taxonomy and Survey of a Half-Century of Research

Fabian Fagerholm, Michael Felderer, Davide Fucci +8

Cognition plays a fundamental role in most software engineering activities. This article provides a taxonomy of cognitive concepts and a survey of the literature since the beginnin…