greedy

What is Greedy Token Parsing in PHP? I was reading a PHP coding guide which said the following... "Always use single quoted strings unless you need variables parsed, and in cases where you do need variables parsed, use braces to prevent greedy token parsing . You may also use double-quoted strings if the string contains single quotes, so you do not have to use escape characters." Is this using curly braces around my variables some sort of security process to rule out hacking? (E.g. {$var}) Is greedy token parsing some sort of attack that hackers can use, like SQL injection or XSS (Cross Site

You know who knows who among n people that you would like to have come to a party. Assume "knows" is symmetric: If I know you, you know me. You make further requirements that you want each person to have at least 5 new people to meet at the party, and also, so nobody feels too isolated, each person should already know at least 5 people at the party. Your original list may not satisfy these extra two conditions, so you may need to eliminate some people from the invitation list (or maybe you cannot have a party at all with these restrictions). Find a largest possible subset of the n people that

I recently had this problem on a test: given a set of points m (all on the x-axis) and a set n of lines with endpoints [ l, r ] (again on the x-axis), find the minimum subset of n such that all points are covered by a line. Prove that your solution always finds the minimum subset. The algorithm I wrote for it was something to the effect of: (say lines are stored as arrays with the left endpoint in position 0 and the right in position 1) algorithm coverPoints(set[] m, set[][] n): chosenLines = [] while m is not empty: minX = min(m) bestLine = n[0] for i=1 to length of n: if n[i][0] <= minX and

What is the use of greedy algorithms? An real example? Minimum Spanning Tree - Prim 's algorithm and Kruskal's algorithm Shortest Path Calculation - Dijkstra's algorithm More: (Fractional Knapsack Problem, Huffman Coding, Optimal Merging, Topological Sort). Some problems are such that a greedy solution will actually be optimal, and sometimes they're engineered that way. A fun example is that many countries' coin values are such that a greedy approach to returning change (i.e. always returning the largest-possible coin until you're done) works. Anything where an optimal solution would be

Given a M * N grid and location of two players p1 and p2 on grid. There are n balls placed on different positions on the grid. Let the location of these balls be B(1), B(2), B(3) ..., B(n) . We need to calculate the minumum manhattan distance required to pick all the balls. Balls should be picked in ascending order i.e if B(i) is picked before B(j) if i < j . Consider the following sample case: p1 = (1, 1) p2 = (3, 4) Lets consider location of balls as B(1) = (1, 1), B(2) = (2, 1), B(3) = (3, 1), B(4) = (5, 5) Output will be 5 because p1 will first choose B(1), B(2), B(3) and p1 will choose B