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Summary
This summary is machine-generated.

Estimating software test set size is crucial. This study uses combinatorial methods and covering arrays to determine test coverage and detect t-way interaction faults, offering practical recommendations for test requirements.

Keywords:
combinatorial testingconfiguration modelfactor covering arraystate-space coveraget-way testingverification and validation (V&V)

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Area of Science:

  • Software Engineering
  • Combinatorial Mathematics

Background:

  • Estimating the required number of tests for adequate software coverage or fault detection is a significant challenge.
  • Current methods often rely on error rates or code coverage metrics like statement or branch coverage.

Purpose of the Study:

  • To introduce a novel approach for estimating test set size using combinatorial methods.
  • To evaluate the coverage and fault detection capabilities of test sets based on covering arrays, specifically for t-way interaction faults.

Main Methods:

  • Utilizing covering arrays to model test sets and estimate coverage for t-way interaction faults.
  • Establishing a theoretical link between static combinatorial coverage and dynamic code coverage.
  • Demonstrating conditions under which 100% branch coverage can be guaranteed.

Main Results:

  • Methods for estimating the coverage and fault detection ability of test sets based on covering arrays are presented.
  • A connection between combinatorial coverage and branch coverage is established, ensuring 100% branch coverage under specific conditions.
  • The study provides a new perspective on determining optimal test set sizes.

Conclusions:

  • Combinatorial methods offer a powerful alternative for estimating test set size and coverage.
  • The established link between combinatorial and code coverage provides a pathway to guarantee specific code coverage levels.
  • Practical recommendations are proposed for integrating combinatorial coverage into test requirement specifications.