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Section 2.13 Glossary
Glossary Glossary
algorithm.
a generic, step-by-step list of instructions for solving a problem.
average case.
refers to when an algorithm performs between its worst and best case given a certain data set or circumstance.
best case.
refers to when an algorithm performs especially good given a certain data set or circumstance.
Big-O notation.
another term for order of magnitude; written as
\(O(f(n))\)
brute force.
technique that tries to exhaust all possibilities of a problem.
contains.
A hash operation used to check if a table contains a specific element.
contiguous.
dynamic size.
able to change size automatically.
exponential.
function represented as a number being raised to a power that increases like
\(f(n)= 2^{n}\)
get_item.
A hash operation used to retrieve the information associated with a hash key.
hash table.
a collection consisting of key-value pairs with an associated hash function that maps the key to the associated value.
linear.
function that grows in a one to one relationship with its input like
\(f(n) = n\)
logarithmic.
functions that are the inverse of exponential functions usually presented as
\(f(n) = logn\)
order of magnitude.
function describing the part
\(T(n)\) that increases the fastest as the value of n increases (a function describing an algorithm’s steps as the size of the problem increases).
quadratic.
function describing a relationship who’s highest order is a number squared. For instance:
simplified:
\(f(n) = x^{2}\)
complex:
\(ax^{2} + bx + c\)
set_item.
A hash operation used to add an item to your table.
vector.
sequence container storing data of a single type that is stored in a dynamically allocated array which can change in size.
worst case.
refers to when an algorithm performs especially poorly given a certain data set or circumstance.
Checkpoint 2.13.1 .
Checkpoint 2.13.2 .
Checkpoint 2.13.3 .
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