pseudocode

I need to go from milliseconds to a tuple of (hour, minutes, seconds, milliseconds) representing the same amount of time. E.g.: 10799999ms = 2h 59m 59s 999ms The following pseudo-code is the only thing I could come up with: # The division operator below returns the result as a rounded down integer function to_tuple(x): h = x / (60*60*1000) x = x - h*(60*60*1000) m = x / (60*1000) x = x - m*(60*1000) s = x / 1000 x = x - s*1000 return (h,m,s,x) I'm sure it must be possible to do it smarter/more elegant/faster/more compact. Here is how I would do it in Java: int seconds = (int) (milliseconds /

Jump Game: Given an array, start from the first element and reach the last by jumping. The jump length can be at most the value at the current position in the array. The optimum result is when you reach the goal in minimum number of jumps. What is an algorithm for finding the optimum result? An example: given array A = {2,3,1,1,4} the possible ways to reach the end (index list) are 0,2,3,4 (jump 2 to index 2, then jump 1 to index 3 then 1 to index 4) 0,1,4 (jump 1 to index 1, then jump 3 to index 4) Since second solution has only 2 jumps it is the optimum result. Overview Given your array a

I have been looking for an algorithm to perform a transitive reduction on a graph, but without success. There's nothing in my algorithms bible (Introduction To Algorithms by Cormen et al) and whilst I've seen plenty of transitive closure pseudocode, I haven't been able to track down anything for a reduction. The closest I've got is that there is one in "Algorithmische Graphentheorie" by Volker Turau (ISBN:978-3-486-59057-9), but unfortunately I don't have access to this book! Wikipedia is unhelpful and Google is yet to turn up anything. :^( Does anyone know of an algorithm for performing a

I have a database of bus/train/... stops and the arrival/departure times on each date and so on. I'm looking for a way to do a search for the fastest(shortest/cheapest/least transitions) trip between two locations. I would like to have arbitrary locations in the future, using OpenStreetMap data to do walking between stops and from stops to start/end, however for the time being I just want to find path between two stops in the database. The problem is I can't seem to find much info about this subject, for example this Wikipedia page has a lot of text with absolutely no useful information in it.

Program A() { x, y, z: integer; procedure B() { y: integer; y=0; x=z+1; z=y+2; } procedure C() { z: integer; procedure D() { x: integer; x = z + 1; y = x + 1; call B(); } z = 5; call D(); } x = 10; y = 11; z = 12; call C(); print x, y, z; } From my understanding, the result of this program when run using static scoping is: x=13, y=7, and z=2. However, when it is run using dynamic scoping , the result is: x=10, y=7, and z=12. These results are the ones that our professor gave us. However, I cannot understand for the life of me how he has reached these results. Could someone possibly walk

I am trying to test the likelihood that a particular clustering of data has occurred by chance. A robust way to do this is Monte Carlo simulation, in which the associations between data and groups are randomly reassigned a large number of times (e.g. 10,000), and a metric of clustering is used to compare the actual data with the simulations to determine a p value. I've got most of this working, with pointers mapping the grouping to the data elements, so I plan to randomly reassign pointers to data. THE QUESTION: what is a fast way to sample without replacement, so that every pointer is