Enhancing Multi-Objective Test Case Selection through the Mutation Operator DOI Creative Commons
Miriam Ugarte, Pablo Valle, Miren Illarramendi

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: April 3, 2024

Abstract Test case selection has been a widely investigated technique to increase the cost-effectiveness of software testing. Because search space in this problem is huge, search-based approaches have found effective, where an optimization algorithm (e.g., genetic algorithm) applies mutation and crossover operators guided by corresponding objective functions with goal reducing test execution cost while maintaining overall quality. The de-facto operator bit-flip mutation, mutated probability $1/N$, $N$ being total number cases original suite. This core disadvantage: effective ineffective one same selected or removed. In paper, we advocate for novel that promotes selecting cost-effective removing expensive ones. To end, instead applying $1/N$ every single suite, calculate new removal probabilities. carried out based on adequacy criterion as well each case, determined before executing historical data). We evaluate our approach 13 study system, including 3 industrial studies, three different application domains (i.e., Cyber-Physical Systems (CPSs), continuous integration systems control systems). Our results suggests proposed can methods, especially when time budget low.

Language: Английский

Enhancing multi-objective test case selection through the mutation operator DOI
Miriam Ugarte, Pablo Valle, Miren Illarramendi

et al.

Automated Software Engineering, Journal Year: 2025, Volume and Issue: 32(1)

Published: Jan. 30, 2025

Language: Английский

Citations

0
An improved multi-objective particle swarm optimization algorithm for the design of foundation pit of rail transit upper cover project DOI Creative Commons
Jinyan Shao, Yuan Lu, Sun Yi

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 26, 2025

In this study, a multi-objective particle swarm optimization (MOIPSO) algorithm is proposed to address complex problems, including real-world engineering challenges. The retains the basic convergence mechanism of (PSO) as its core, while innovatively combining fast non-dominated sorting technique effectively evaluate and approximate Pareto optimal solution set. To enhance diversity generalization set, crowding distance introduced, ensuring good balance between multiple objectives wider coverage space. Additionally, an acceleration factor based on trigonometric functions adaptive Gaussian mutation strategy are incorporated, improving exploration ability particles in search space facilitating their movement towards global more effectively. performance verified using multi-modal benchmark function set provided by CEC2020, comparisons made with five advanced metaheuristics. MOIPSO also applied solve design problem rail transit upper cover foundation pit, further demonstrating practical effectiveness algorithm. results show that not only performs well testing but proves highly competitive solving problems. Note source codes MOGWO publicly available at https://au.mathworks.com/matlabcentral/fileexchange/177404-moipso-optimization-engineering-problem .

Language: Английский

Citations

0
Search-based Test Case Selection for PLC Systems using Functional Block Diagram Programs DOI
Miriam Ugarte, Eunkyoung Jee,

Lingjun Liu

et al.

Published: Oct. 9, 2023

Programmable Logic Controllers (PLCs) are the core unit of production system, which frequently need to implement new processes address customer needs. These changes must be fully tested ensure reliability PLC code, is commonly programmed through Functional Block Diagrams (FBDs). This a tedious task that requires considerable time and effort given manual nature process involved in testing. Hence, we present cost-effective test selection approach FBD programs dynamic environments. The proposed method uses search-based multi-objective case algorithm as regression technique recently modified programs. Specifically, derived total 7 fitness function combinations, by combining different cost quality-based functions. We carried out an empirical evaluation, employing metrics wellknown NSGA-II determine best configuration setup for testing Furthermore, benchmarked performance with baseline Random Search (RS). study was three studies reactor protection evaluated two sets mutants. results demonstrated significantly reduces time, while keeping high overall fault detection capability.

Language: Английский

Citations

3
A Novel Mutation Operator for Search-Based Test Case Selection DOI
Aitor Arrieta, Miren Illarramendi

Lecture notes in computer science, Journal Year: 2023, Volume and Issue: unknown, P. 84 - 98

Published: Dec. 3, 2023

Language: Английский

Citations

2
Enhancing Multi-Objective Test Case Selection through the Mutation Operator DOI Creative Commons
Miriam Ugarte, Pablo Valle, Miren Illarramendi

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: April 3, 2024

Abstract Test case selection has been a widely investigated technique to increase the cost-effectiveness of software testing. Because search space in this problem is huge, search-based approaches have found effective, where an optimization algorithm (e.g., genetic algorithm) applies mutation and crossover operators guided by corresponding objective functions with goal reducing test execution cost while maintaining overall quality. The de-facto operator bit-flip mutation, mutated probability $1/N$, $N$ being total number cases original suite. This core disadvantage: effective ineffective one same selected or removed. In paper, we advocate for novel that promotes selecting cost-effective removing expensive ones. To end, instead applying $1/N$ every single suite, calculate new removal probabilities. carried out based on adequacy criterion as well each case, determined before executing historical data). We evaluate our approach 13 study system, including 3 industrial studies, three different application domains (i.e., Cyber-Physical Systems (CPSs), continuous integration systems control systems). Our results suggests proposed can methods, especially when time budget low.

Language: Английский

Citations

0