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 -