A Method for Estimating Minimum Sizes of Covering Arrays Avoiding Forbidden Edges by Decomposing Graphs

2021 ◽  
Author(s):  
Jingli Yang ◽  
Shuangyan Yin ◽  
Jianfeng Wang ◽  
Shijie Li
Keyword(s):  
Covering Arrays

Factorials Experiments, Covering Arrays, and Combinatorial Testing

2021 ◽  
Author(s):  
Raghu N. Kacker ◽  
D. Richard Kuhn ◽  
Yu Lei ◽  
Dimitris E. Simos
Keyword(s):  
Combinatorial Testing ◽  
Covering Arrays

New optimal covering arrays using an orderly algorithm

2018 ◽  
Vol 10 (01) ◽  
pp. 1850011 ◽  
Author(s):  
Idelfonso Izquierdo-Marquez ◽  
Jose Torres-Jimenez
Keyword(s):  
Small Subset ◽  
Computational Results ◽  
Covering Array ◽  
Covering Arrays ◽  
Computational Search ◽  
Minimum Number ◽  
Orderly Algorithm

A covering array [Formula: see text] is an [Formula: see text] array such that every [Formula: see text] subarray covers at least once each [Formula: see text]-tuple from [Formula: see text] symbols. For given [Formula: see text], [Formula: see text], and [Formula: see text], the minimum number of rows for which exists a CA is denoted by [Formula: see text] (CAN stands for Covering Array Number) and the corresponding CA is optimal. Optimal covering arrays have been determined algebraically for a small subset of cases; but another alternative to find CANs is the use of computational search. The present work introduces a new orderly algorithm to construct non-isomorphic covering arrays; this algorithm is an improvement of a previously reported algorithm for the same purpose. The construction of non-isomorphic covering arrays is used to prove the nonexistence of certain covering arrays whose nonexistence implies the optimality of other covering arrays. From the computational results obtained, the following CANs were established: [Formula: see text] for [Formula: see text], [Formula: see text], and [Formula: see text]. In addition, the new result [Formula: see text], and the already known existence of [Formula: see text], imply [Formula: see text].

scholarly journals Refining the In-Parameter-Order Strategy for Constructing Covering Arrays

2008 ◽  
Vol 113 (5) ◽  
pp. 287 ◽  
Author(s):  
Michael Forbes ◽  
Jim Lawrence ◽  
Yu Lei ◽  
Raghu N. Kacker ◽  
D. Richard Kuhn
Keyword(s):  
Covering Arrays

Research Notes: Binary Test-Suites Using Covering Arrays

2018 ◽  
Vol 28 (09) ◽  
pp. 1321-1337 ◽  
Author(s):  
Jose Torres-Jimenez ◽  
Himer Avila-George ◽  
Ezra Federico Parra-González
Keyword(s):  
Software Testing ◽  
Test Generation ◽  
Software Systems ◽  
Combinatorial Testing ◽  
Covering Array ◽  
Covering Arrays ◽  
Almost All ◽  
Generation Problem ◽  
Test Suites

Software testing is an essential activity to ensure the quality of software systems. Combinatorial testing is a method that facilitates the software testing process; it is based on an empirical evidence where almost all faults in a software component are due to the interaction of very few parameters. The test generation problem for combinatorial testing can be represented as the construction of a matrix that has certain properties; typically this matrix is a covering array. Covering arrays have a small number of tests, in comparison with an exhaustive approach, and provide a level of interaction coverage among the parameters involved. This paper presents a repository that contains binary covering arrays involving many levels of interaction. Also, it discusses the importance of covering array repositories in the construction of better covering arrays. In most of the cases, the size of the covering arrays included in the repository reported here are the best upper bounds known, moreover, the files containing the matrices of these covering arrays are available to be downloaded. The final purpose of our Binary Covering Arrays Repository (BCAR) is to provide software testing practitioners the best-known binary test-suites.

A density-based greedy algorithm for higher strength covering arrays

2009 ◽  
Vol 19 (1) ◽  
pp. 37-53 ◽  
Author(s):  
Renée C. Bryce ◽  
Charles J. Colbourn
Keyword(s):  
Greedy Algorithm ◽  
Covering Arrays

Covering arrays from m-sequences and character sums

2016 ◽  
Vol 85 (3) ◽  
pp. 437-456 ◽  
Author(s):  
Georgios Tzanakis ◽  
Lucia Moura ◽  
Daniel Panario ◽  
Brett Stevens
Keyword(s):  
Character Sums ◽  
Covering Arrays ◽  
M Sequences

Chapter 21. Combinatorial Designs by SAT Solvers1

2021 ◽  
Author(s):  
Hantao Zhang
Keyword(s):  
Design Theory ◽  
High Performance ◽  
General Purpose ◽  
Combinatorial Designs ◽  
Covering Arrays ◽  
Open Problems ◽  
Ramsey Numbers ◽  
Sat Solvers ◽  
Open Design ◽  
New Ideas

The theory of combinatorial designs has always been a rich source of structured, parametrized families of SAT instances. On one hand, design theory provides interesting problems for testing various SAT solvers; on the other hand, high-performance SAT solvers provide an alternative tool for attacking open problems in design theory, simply by encoding problems as propositional formulas, and then searching for their models using off-the-shelf general purpose SAT solvers. This chapter presents several case studies of using SAT solvers to solve hard design theory problems, including quasigroup problems, Ramsey numbers, Van der Waerden numbers, covering arrays, Steiner systems, and Mendelsohn designs. It is shown that over a hundred of previously-open design theory problems were solved by SAT solvers, thus demonstrating the significant power of modern SAT solvers. Moreover, the chapter provides a list of 30 open design theory problems for the developers of SAT solvers to test their new ideas and weapons.

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