COP4020 Homework Assignment 2
... 3. We can implement a binary tree data structure by using lists with three
elements: (value left-tree right-tree). For example, a tree with one node R (the
root) is represented by (R () ()). (The empty lists represent the (empty)
left and right child trees.) Given the tree:
An Introduction to F# – Sushant Bhatia
... What is Functional Programming?
A function is a rule that associates to each x
from some set X of values, a unique y from
another set Y of values. If f is the name of the
CS-2852 Data Structures
... • Recursion, n. see Recursion
• Some functional programming
languages don’t have loops (equivalent
to imperative looping constructs)
• A function “calls itself” – directly or not
CS-2852 Data Structures, Andrew J. Wozniewicz
COP4020 Homework Assignment 2
... 1. Which Scheme construct(s) will cause a Scheme program to depart from a purely
functional programming model?
2. Explain the difference between a functional and a special form in Scheme.
3. We can implement a binary tree data structure by using lists with three elements:
(value left-tree right-tree ...
Periodic table E
... A circle used to display data. The
angle of each sector is
proportional to the frequency
Different Data Structures
... Each internal node x also contains x.n+1 pointers x.c1, x.c2, … x.cx.n+1 to its
children. Leaf nodes have no children, and so their ci attributes are
The keys x.keyi separate the ranges of keys stored in each subtree: if ki is
any key stored in the subtree with root x.ci, then k1 <= x.key ...
Monday, March 23, 2009 - Lynbrook Computer Science
... its children
? must be smaller than S, larger than G and L.
Leaves 6 possibilities: M, N, O, P, Q, R
Two of those are already in heap: Q and N, so they can’t
be the ?
The answer thus is:
Nonlinear Data Structures
... show the relationships using a linear data structure like a list or a
stack. Instead, we needed something that looks more like a tree.
... • A method for adjusting random numbers produced
by a random number generator to reside within
ranges, such as 1 to 100
– Accomplished using the expression:
... • Preconditions, postconditions and assertions
• Automatic documentation
Association Rule Mining in Peer-to
... For each node to maintain an assumption
of the correct result
Update the result whenever new data
Nodes compute the result through local
negotiation with their immediate neighbor
... The score can be binary, discrete or
Input format is flexible and allows genes
to be in more than one group or cluster
Thus does not exclude biclustering or
In computer science, corecursion is a type of operation that is dual to recursion. Whereas recursion works analytically, starting on data further from a base case and breaking it down into smaller data and repeating until one reaches a base case, corecursion works synthetically, starting from a base case and building it up, iteratively producing data further removed from a base case. Put simply, corecursive algorithms use the data that they themselves produce, bit by bit, as they become available, and needed, to produce further bits of data. A similar but distinct concept is generative recursion which may lack a definite ""direction"" inherent in corecursion and recursion. Where recursion allows programs to operate on arbitrarily complex data, so long as they can be reduced to simple data (base cases), corecursion allows programs to produce arbitrarily complex and potentially infinite data structures, such as streams, so long as it can be produced from simple data (base cases). Where recursion may not terminate, never reaching a base state, corecursion starts from a base state, and thus produces subsequent steps deterministically, though it may proceed indefinitely (and thus not terminate under strict evaluation), or it may consume more than it produces and thus become non-productive. Many functions that are traditionally analyzed as recursive can alternatively, and arguably more naturally, be interpreted as corecursive functions that are terminated at a given stage, for example recurrence relations such as the factorial.Corecursion can produce both finite and infinite data structures as result, and may employ self-referential data structures. Corecursion is often used in conjunction with lazy evaluation, to only produce a finite subset of a potentially infinite structure (rather than trying to produce an entire infinite structure at once). Corecursion is a particularly important concept in functional programming, where corecursion and codata allow total languages to work with infinite data structures.