Evidence map›Paper›PMID 39668943›Full record

ArticleEmpirical software engineering2024

Semantic matching in GUI test reuse.

Farideh Khalili, Leonardo Mariani, Ali Mohebbi, Mauro Pezzè, Valerio Terragni

Abstract read
In one paragraph

Article in Empirical software engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Farideh KhaliliNortheastern University, Boston, MA USA.
Leonardo MarianiUniversity of Milano - Bicocca, Milan, Italy.
Ali MohebbiUSI Universitá della Svizzera italiana, Lugano, Switzerland.ORCID 0000-0002-4844-4351
Mauro PezzèUSI Universitá della Svizzera italiana, Lugano, Switzerland.ORCID 0000-0001-5193-7379
Valerio TerragniUniversity of Auckland, Auckland, New Zealand.ORCID 0000-0001-5885-9297

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reusing test cases across apps that share similar functionalities reduces both the effort required to produce useful test cases and the time to offer reliable apps to the market. The main approaches to reuse test cases across apps combine different semantic matching and test generation algorithms to migrate test cases across Android apps. In this paper we define a general framework to evaluate the impact and effectiveness of different choices of semantic matching with Test Reuse approaches on migrating test cases across Android apps. We offer a thorough comparative evaluation of the many possible choices for the components of test migration processes. We propose an approach that combines the most effective choices for each component of the test migration process to obtain an effective approach. We report the results of an experimental evaluation on 8,099 GUI events from 337 test configurations. The results attest the prominent impact of semantic matching on test reuse. They indicate that sentence level perform better than word level embedding techniques. They surprisingly suggest a negligible impact of the corpus of documents used for building the word embedding model for the Semantic Matching Algorithm. They provide evidence that semantic matching of events of selected types perform better than semantic matching of events of all types. They show that the effectiveness of overall Test Reuse approach depends on the characteristics of the test suites and apps. The replication package that we make publicly available online (https://star.inf.usi.ch/#/software-data/11) allows researchers and practitioners to refine the results with additional experiments and evaluate other choices for test reuse components.

Indexed as

Automatic test generationFastGloveSemantic matching for testingSoftware testingTesting Android appsTest reuseUniversal sentence encoderWord2vecWord Mover

Identifiers

PMID39668943
PMCPMC11636732

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.