A Catalog of Transformations to Remove Smells From Natural Language Tests

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3ABTMCELID" target="_blank" >RIV/00216208:11320/25:BTMCELID - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197373673&doi=10.1145%2f3661167.3661225&partnerID=40&md5=2ae2f09c9ab663300a99343814fe436c" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197373673&doi=10.1145%2f3661167.3661225&partnerID=40&md5=2ae2f09c9ab663300a99343814fe436c</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3661167.3661225" target="_blank" >10.1145/3661167.3661225</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Catalog of Transformations to Remove Smells From Natural Language Tests

Popis výsledku v původním jazyce

Test smells can pose difficulties during testing activities, such as poor maintainability, non-deterministic behavior, and incomplete verification. Existing research has extensively addressed test smells in automated software tests but little attention has been given to smells in natural language tests. While some research has identified and catalogued such smells, there is a lack of systematic approaches for their removal. Consequently, there is also a lack of tools to automatically identify and remove natural language test smells. This paper introduces a catalog of transformations designed to remove seven natural language test smells and a companion tool implemented using Natural Language Processing (NLP) techniques. Our work aims to enhance the quality and reliability of natural language tests during software development. The research employs a two-fold empirical strategy to evaluate its contributions. First, a survey involving 15 software testing professionals assesses the acceptance and usefulness of the catalog's transformations. Second, an empirical study evaluates our tool to remove natural language test smells by analyzing a sample of real-practice tests from the Ubuntu OS. The results indicate that software testing professionals find the transformations valuable. Additionally, the automated tool demonstrates a good level of precision, as evidenced by a F-Measure rate of 83.70%. © 2024 ACM.

Název v anglickém jazyce

A Catalog of Transformations to Remove Smells From Natural Language Tests

Popis výsledku anglicky

Test smells can pose difficulties during testing activities, such as poor maintainability, non-deterministic behavior, and incomplete verification. Existing research has extensively addressed test smells in automated software tests but little attention has been given to smells in natural language tests. While some research has identified and catalogued such smells, there is a lack of systematic approaches for their removal. Consequently, there is also a lack of tools to automatically identify and remove natural language test smells. This paper introduces a catalog of transformations designed to remove seven natural language test smells and a companion tool implemented using Natural Language Processing (NLP) techniques. Our work aims to enhance the quality and reliability of natural language tests during software development. The research employs a two-fold empirical strategy to evaluate its contributions. First, a survey involving 15 software testing professionals assesses the acceptance and usefulness of the catalog's transformations. Second, an empirical study evaluates our tool to remove natural language test smells by analyzing a sample of real-practice tests from the Ubuntu OS. The results indicate that software testing professionals find the transformations valuable. Additionally, the automated tool demonstrates a good level of precision, as evidenced by a F-Measure rate of 83.70%. © 2024 ACM.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

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Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering

ISBN

979-840071701-7

ISSN

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e-ISSN

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Počet stran výsledku

10

Strana od-do

7-16

Název nakladatele

Association for Computing Machinery

Místo vydání

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Místo konání akce

Salerno Italy

Datum konání akce

1. 1. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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