A Catalog of Transformations to Remove Smells From Natural Language Tests
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
A Catalog of Transformations to Remove Smells From Natural Language Tests
Original language description
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.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
—
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering
ISBN
979-840071701-7
ISSN
—
e-ISSN
—
Number of pages
10
Pages from-to
7-16
Publisher name
Association for Computing Machinery
Place of publication
—
Event location
Salerno Italy
Event date
Jan 1, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—