% test for correct size for iter = 1:10 vectorLength = randi([1 100]); result = fcn(vectorLength); assert(isequal([vectorLength, 1], size(result))); end

% get large sample vectorLength = 10000; result = fcn(vectorLength); % built empirical cumulative distribution function xEmpirical = 0:10; % x-axis counts = accumarray(result+1, 1); density = counts ./ sum(counts); yEmpirical = cumsum(density); % y-axis % build theoretical cumulative distribution function xTheoretical = xEmpirical; % x-axis for k = xTheoretical yTheoretical(k+1, 1) = betainc(exp(-1), 10-k, k+1); % y-axis end % compute statistics on diff between empirical and theoretical errorList = abs(yEmpirical - yTheoretical); errorMax = max(errorList); errorSum = sum(errorList); errorStd = std(errorList); % if fcn is correct, this should pass at least 99.9% of the time assert(errorMax < .018); assert(errorSum > .0045); assert(errorStd > .0004);