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+CS 325, Algorithms, Fall 2019
+HW3 - K closest numbers; Two Pointers
+
+Due Monday Oct 14, 11:59pm. (same submission instructions as HW1-2).
+No late submission will be accepted.
+
+Need to submit: report.txt, closest_unsorted.py, closest_sorted.py, xyz.py.
+closest_sorted.py will be graded for correctness (1%).
+
+To submit:
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/submit hw3 report.txt {closest*,xyz}.py
+(You can submit each file separately, or submit them together.)
+
+To see your best results so far:
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/query hw3
+
+
+1. Given an array A of n numbers, a query x, and a number k,
+   find the k numbers in A that are closest (in value) to x.
+   For example:
+
+   find([4,1,3,2,7,4], 5.2, 2)	returns   [4,4]
+   find([4,1,3,2,7,4], 6.5, 3)	returns   [4,7,4]
+   find([5,3,4,1,6,3], 3.5, 2)	returns   [3,4]
+
+
+   Filename: closest_unsorted.py
+   Must run in O(n) time. 
+   The elements in the returned list must be in the original order.
+   In case two numbers are equally close to x, choose the earlier one.
+
+
+2. [WILL BE GRADED]
+   Now what if the input array is sorted? Can you do it faster?
+
+   find([1,2,3,4,4,7], 5.2, 2) returns   [4,4]
+   find([1,2,3,4,4,7], 6.5, 3) returns   [4,4,7]
+
+   Filename: closest_sorted.py
+   Must run in O(logn + k) time.
+   The elements in the returned list must be in the original order.
+
+   Note: in case two numbers are equally close to x, choose the smaller one:
+   find([1,2,3,4,4,6,6], 5, 3) returns   [4,4,6]
+   find([1,2,3,4,4,5,6], 4, 5) returns   [2,3,4,4,5]
+
+   Hint: you can use Python's bisect.bisect for binary search.
+
+
+3. For a given array A of n *distinct* numbers, find all triples (x,y,z) 
+   s.t. x + y = z. (x, y, z are distinct numbers)
+
+   e.g.,
+   
+   find([1, 4, 2, 3, 5]) returns [(1,3,4), (1,2,3), (1,4,5), (2,3,5)]
+
+   Note that:
+   1) no duplicates in the input array
+   2) you can choose any arbitrary order for triples in the returned list.
+
+   Filename: xyz.py
+   Must run in O(n^2) time.
+
+   Hint: you can use any built-in sort in Python.
+
+
+Debriefing (required!): --------------------------
+
+0. What's your name?
+1. Approximately how many hours did you spend on this assignment?
+2. Would you rate it as easy, moderate, or difficult?
+3. Did you work on it mostly alone, or mostly with other people?
+   Note you are encouraged to discuss with your classmates, 
+   but each students should submit his/her own code.
+4. How deeply do you feel you understand the material it covers (0%-100%)? 
+
+5. Which part(s) of the course you like the most so far?
+6. Which part(s) of the course you dislike the most so far?
+
+This section is intended to help us calibrate the homework assignments. 
+Your answers to this section will *not* affect your grade; however, skipping it
+will certainly do.
+