Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Evolutionary testing using an extended Chaining Approach.

P McMinn1, M Holcombe

  • 1University of Sheffield, Department of Computer Science, Regent Court, 211 Portobello Street, Sheffield, S1 4DP, UK. p.mcminn@dcs.shef.ac.uk

Evolutionary Computation
|March 16, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Decline in tuberculosis with 19 years of universal directly observed therapy in a comprehensive statewide program.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease·2011
Same author

Anti-bacterial IgE in the antibody responses of house dust mite allergic children convalescent from asthma exacerbation.

Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology·2009
Same author

Transmission networks and population turnover of echovirus 30.

Journal of virology·2008
Same author

An agent-based model to investigate the roles of attractive and repellent pheromones in ant decision making during foraging.

Journal of theoretical biology·2008
Same author

The epitheliome: agent-based modelling of the social behaviour of cells.

Bio Systems·2004
Same author

Tuberculosis contact investigation in a rural state.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease·2003
Same journal

Computing Optimal Populations for Binary Problems using Logic Minimization.

Evolutionary computation·2026
Same journal

Enhancing Generalization and Scalability for Multi-Objective Optimization with Population Pre-Training.

Evolutionary computation·2026
Same journal

XCS for Sequential Perceptual Aliasing in Multi-Step Decision Making.

Evolutionary computation·2026
Same journal

A dynamic multi-objective evolutionary algorithm using dual-space prediction and surrogate-based sampling.

Evolutionary computation·2026
Same journal

Adapting MOEA/D to CMA-ES for Dealing with Ill-conditioned Multiobjective Problems.

Evolutionary computation·2026
Same journal

Editorial of the Special Issue: Parallel Problem Solving from Nature PPSN 2024 Extended Versions of Best Paper Candidates.

Evolutionary computation·2026
See all related articles

This study enhances evolutionary software testing by integrating a chaining approach to guide test data generation. This hybrid method improves the discovery of test data for complex software, including the libpng library.

Area of Science:

  • Computer Science
  • Software Engineering
  • Artificial Intelligence

Background:

  • Evolutionary Testing (ET) often struggles with inadequate fitness functions for test data generation.
  • Lack of search guidance in ET stems from ignoring data dependencies and execution prerequisites.

Purpose of the Study:

  • To improve evolutionary software test data generation by addressing limitations in fitness functions.
  • To enhance search guidance by incorporating data dependencies and execution sequences.

Main Methods:

  • Hybridizing Evolutionary Testing with an extended Chaining Approach.
  • The Chaining Approach identifies and chains data dependencies for program statements.
  • Performing targeted test data searches for each generated event sequence.

Related Experiment Videos

Main Results:

  • The hybrid approach successfully generates test data for goals previously unattainable with standard ET.
  • Demonstrated effectiveness on a test goal from the libpng library.
  • Improved search direction into unexplored input domain areas.

Conclusions:

  • Hybridizing ET with the Chaining Approach significantly enhances test data generation capabilities.
  • This method overcomes limitations of traditional ET by considering program structure and data flow.
  • Offers a more effective strategy for white-box software testing.