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Dynamic Test Case Prioritization in Industrial Test Result Datasets

Publiceringsår

2024

Upphovspersoner

Alina Torbunova; Per Erik Strandberg; Ivan Porres

Abstrakt

Regression testing in software development checks if new software features affect existing ones. Regression testing is a key task in<br/>continuous development and integration, where software is built in small increments and new features are integrated as soon as<br/>possible. It is therefore important that developers are notified about possible faults quickly. In this article, we propose a test case prioritization schema that combines the use of a static and a dynamic prioritization algorithm. The dynamic prioritization algorithm rearranges the order of execution of tests on the fly, while the tests are being executed. We propose to use a conditional probability<br/>dynamic algorithm for this. We evaluate our solution on three industrial datasets and utilize Average Percentage of Fault Detection<br/>for that. The main findings are that our dynamic prioritization algorithm can: a) be applied with any static algorithm that assigns<br/>a priority score to each test case b) can improve the performance of the static algorithm if there are failure correlations between test<br/>cases c) can also reduce the performance of the static algorithm, but only when the static scheduling is performed at a near optimal<br/>level.<br/>
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Organisationer och upphovspersoner

Åbo Akademi

Torbunova Alina

Porres Ivan Orcid -palvelun logo

Publikationstyp

Publikationsform

Artikel

Moderpublikationens typ

Konferens

Artikelstyp

Annan artikel

Målgrupp

Vetenskaplig

Kollegialt utvärderad

Kollegialt utvärderad

UKM:s publikationstyp

A4 Artikel i en konferenspublikation

Öppen tillgång

Öppen tillgänglighet i förläggarens tjänst

Ja

Öppen tillgång till publikationskanalen

Delvis öppen publikationskanal

Parallellsparad

Ja

Övriga uppgifter

Vetenskapsområden

Data- och informationsvetenskap

Nyckelord

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Förlagets internationalitet

Internationell

Språk

engelska

Internationell sampublikation

Ja

Sampublikation med ett företag

Ja

DOI

10.1145/3644032.3644452

Publikationen ingår i undervisnings- och kulturministeriets datainsamling

Ja