TY - GEN
T1 - Generation of tests against a greedy algorithm for the knapsack problem using an evolutionary algorithm
AU - Mironovich, Vladimir
AU - Buzdalov, Maxim
PY - 2014
Y1 - 2014
N2 - Generation of tests for programming challenge tasks can be difficult when it is needed to cover wrong solutions (i.e. greedy algorithms) that use certain tricks (i.e. random shuffling of input data) to decrease the number of tests with wrong answers. In this paper, generation of tests for the knapsack problem is considered. Several tests that make a certain class of incorrect solutions fail with high probability are generated using an evolutionary algorithm.
AB - Generation of tests for programming challenge tasks can be difficult when it is needed to cover wrong solutions (i.e. greedy algorithms) that use certain tricks (i.e. random shuffling of input data) to decrease the number of tests with wrong answers. In this paper, generation of tests for the knapsack problem is considered. Several tests that make a certain class of incorrect solutions fail with high probability are generated using an evolutionary algorithm.
KW - Algorithm verification
KW - Evolutionary algorithms
KW - Greedy algorithm
KW - Knapsack problem
KW - Randomized algorithm
KW - Test generation
UR - http://www.scopus.com/inward/record.url?scp=84938085475&partnerID=8YFLogxK
M3 - Conference Proceeding (Non-Journal item)
AN - SCOPUS:84938085475
VL - 2014-January
T3 - Mendel
SP - 77
EP - 82
BT - 20th International Conference on Soft Computing
T2 - 20th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Fractals, Bayesian Methods, MENDEL 2014
Y2 - 25 June 2014 through 27 June 2014
ER -