TY - GEN
T1 - Detecting arrays for main effects
AU - Colbourn, Charles J.
AU - Syrotiuk, Violet R.
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - Determining correctness and performance for complex engineered systems necessitates testing the system to determine how its behaviour is impacted by many factors and interactions among them. Of particular concern is to determine which settings of the factors (main effects) impact the behaviour significantly. Detecting arrays for main effects are test suites that ensure that the impact of each main effect is witnessed even in the presence of d or fewer other significant main effects. Separation in detecting arrays dictates the presence of at least a specified number of such witnesses. A new parameter, corroboration, enables the fusion of levels while maintaining the presence of witnesses. Detecting arrays for main effects, having various values for the separation and corroboration, are constructed using error-correcting codes and separating hash families. The techniques are shown to yield explicit constructions with few tests for large numbers of factors.
AB - Determining correctness and performance for complex engineered systems necessitates testing the system to determine how its behaviour is impacted by many factors and interactions among them. Of particular concern is to determine which settings of the factors (main effects) impact the behaviour significantly. Detecting arrays for main effects are test suites that ensure that the impact of each main effect is witnessed even in the presence of d or fewer other significant main effects. Separation in detecting arrays dictates the presence of at least a specified number of such witnesses. A new parameter, corroboration, enables the fusion of levels while maintaining the presence of witnesses. Detecting arrays for main effects, having various values for the separation and corroboration, are constructed using error-correcting codes and separating hash families. The techniques are shown to yield explicit constructions with few tests for large numbers of factors.
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U2 - 10.1007/978-3-030-21363-3_10
DO - 10.1007/978-3-030-21363-3_10
M3 - Conference contribution
AN - SCOPUS:85068214461
SN - 9783030213626
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 112
EP - 123
BT - Algebraic Informatics - 8th International Conference, CAI 2019, Proceedings
A2 - Ćirić, Miroslav
A2 - Droste, Manfred
A2 - Pin, Jean-Éric
PB - Springer Verlag
T2 - 8th International Conference on Algebraic Informatics, CAI 2019
Y2 - 30 June 2019 through 4 July 2019
ER -