1. Given f(n(337n2+ 6nlog2n +1492) / (n+25), where f(n) is the instruction count and n is the size of the data set processed by the algorithm. Expressed the efficiency of the algorithms in terms of big-O notation. 2. An algorithm has the big-O efficiency of O(nlog2n), explain what it means in terms of growth rate.. Rank the efficiencies of following list of big-O expressions from more to less efficient: 0(n), 0(1), 0(m), O(log2n), (nlog2n), O((log2n)2), 3. The source code for the binary search function is provided below. Prove its big-O efficiency is O(logzn). int binar.searshlint a[], 4. n, nt key, dnfirst, inlast ) int middle; while (firstlast) middle- (first last) / 2; if (key a[middle]) return middle; first-middle 1; last-middle - 1,; else if (key > a[middle]) else