Unsupervised Machine Learning Approaches for Test Suite Reduction

Unsupervised Machine Learning Approaches for Test Suite Reduction

Ensuring quality and reliability mandates thorough software testing at every stage of the development cycle. As software systems grow in size, complexity, and functionality, the parallel expansion of the test suite leads to an inefficient utilization of computational power and time, presenting chall...

Full description

Bibliographic Details
Main Authors:	Anila Sebastian, Hira Naseem, Cagatay Catal
Format:	Article
Language:	English
Published:	Taylor & Francis Group 2024-12-01
Series:	Applied Artificial Intelligence
Online Access:	https://www.tandfonline.com/doi/10.1080/08839514.2024.2322336

Similar Items

Test suite reduction and prioritization framework in regression testing
by: Musa, Samaila, et al.
Published: (2021)

Predicting Plasma Vitamin C Using Machine Learning
by: Daniel Kirk, et al.
Published: (2022-12-01)

Test Suite Reduction via Evolutionary Clustering
by: Chunyan Xia, et al.
Published: (2021-01-01)

Test suite reduction in android application using refactoring
by: Ahmed, Maryam Temitayo
Published: (2016)

Test Suite Reduction via Submodular Function Maximization
by: WEN Jin, ZHANG Xing-yu, SHA Chao-feng, LIU Yan-jun
Published: (2021-12-01)

Fault Detection of Bearing: An Unsupervised Machine Learning Approach Exploiting Feature Extraction and Dimensionality Reduction
by: Lucas Costa Brito, et al.
Published: (2021-11-01)

A Comparison of Semi-Supervised Classification Approaches for Software Defect Prediction
by: Catal Cagatay
Published: (2014-01-01)

Pattern-Based Test Suite Reduction Method for Smart Contracts
by: Tomasz Górski
Published: (2025-01-01)

A Study of Wolf Pack Algorithm for Test Suite Reduction
by: Zemin Li, et al.
Published: (2022-01-01)

Test Suite Optimization Using Machine Learning Techniques: A Comprehensive Study
by: Abid Mehmood, et al.
Published: (2024-01-01)

Test Suite Prioritization Based on Optimization Approach Using Reinforcement Learning
by: Muhammad Waqar, et al.
Published: (2022-07-01)

Machine Learning-Based Software Defect Prediction for Mobile Applications: A Systematic Literature Review
by: Manzura Jorayeva, et al.
Published: (2022-03-01)

Sensor Failure Tolerable Machine Learning-Based Food Quality Prediction Model
by: Aydin Kaya, et al.
Published: (2020-06-01)

A Study of Test Suite Reduction Based on Ant Lion Optimizer
by: Wei Wei, et al.
Published: (2022-01-01)

Detection of overdose and underdose prescriptions-An unsupervised machine learning approach.
by: Kenichiro Nagata, et al.
Published: (2021-01-01)

Detection of overdose and underdose prescriptions—An unsupervised machine learning approach
by: Kenichiro Nagata, et al.
Published: (2021-01-01)

A Systematic Review on Test Suite Reduction: Approaches, Experiment’s Quality Evaluation, and Guidelines
by: Saif Ur Rehman Khan, et al.
Published: (2018-01-01)

BRTSRDM: Bi-Criteria Regression Test Suite Reduction based on Data Mining
by: Mohammad Reza Keyvanpour, et al.
Published: (2023-04-01)

Maximal frequent sequence based test suite reduction through DU-pairs
by: Narendra Kumar Rao Bangole, et al.
Published: (2014-08-01)

Distributed t-way test suite execution with code coverage on multiple machines
by: Zainal Hisham, Che Soh, et al.
Published: (2017)

Unsupervised learning approach to automation of hammering test using topological information
by: Jun Younes Louhi Kasahara, et al.
Published: (2017-05-01)

Validating Unsupervised Machine Learning Techniques for Software Defect Prediction With Generic Metamorphic Testing
by: Pak Yuen Patrick Chan, et al.
Published: (2024-01-01)

Unsupervised Machine Learning for Improved Delaunay Triangulation
by: Tao Song, et al.
Published: (2021-12-01)

Unsupervised Machine Learning to Identify Depressive Subtypes
by: Benson Kung, et al.
Published: (2022-07-01)

Application of Unsupervised Machine Learning for Event Classification
by: Kryhin, Serhii
Published: (2022)

Multilingual Part-of-Speech Tagging Two Unsupervised Approaches
by: Naseem, Tahira, et al.
Published: (2011)

Unsupervised Machine Learning Applied to Seismic Interpretation: Towards an Unsupervised Automated Interpretation Tool
by: Alimed Celecia, et al.
Published: (2021-09-01)

Approach for reduced test suite generation based on predicate abstraction
by: Xi GUO, et al.
Published: (2012-03-01)

Approach for reduced test suite generation based on predicate abstraction
by: Xi GUO, et al.
Published: (2012-03-01)

Unsupervised machine learning approach for tailoring educational content to individual student weaknesses
by: Shabab Intishar Rahman, et al.
Published: (2024-12-01)

Unsupervised machine learning clustering approach for hospitalized COVID-19 pneumonia patients
by: Nuttinan Nalinthasnai, et al.
Published: (2025-02-01)

Novel Phenotyping for Acute Heart Failure—Unsupervised Machine Learning-Based Approach
by: Szymon Urban, et al.
Published: (2022-06-01)

An Unsupervised Machine Learning Approach for Monitoring Data Fusion and Health Indicator Construction
by: Lin Huang, et al.
Published: (2023-08-01)

Differentiating a pachychoroid and healthy choroid using an unsupervised machine learning approach
by: Reza Mirshahi, et al.
Published: (2022-09-01)

An unsupervised machine learning approach to evaluate sports facilities condition in primary school.
by: Jun Xia, et al.
Published: (2022-01-01)

An unsupervised machine learning approach to evaluate sports facilities condition in primary school
by: Jun Xia, et al.
Published: (2022-01-01)

Characterization of clinical patterns of dengue patients using an unsupervised machine learning approach
by: Gleicy Macedo Hair, et al.
Published: (2019-07-01)

Classification of malignant tumours in breast ultrasound using unsupervised machine learning approaches
by: Wei-Chung Shia, et al.
Published: (2021-01-01)

Hybrid Deep Learning-based Models for Crop Yield Prediction
by: Alexandros Oikonomidis, et al.
Published: (2022-12-01)

Deriving Test Suites with the Guaranteed Fault Coverage for Extended Finite State Machines
by: A. D. Ermakov, et al.
Published: (2016-12-01)