Zusammenfassung der Ressource
2.1 Algorithms
- Computational thinking
- the use of computers
to solve problems
- Algorithmic
Thinking
- identifying the steps
involved in solving a
problem
- Linear Search
- each item in the list
is checked in order
- The worst case
scenario is you
have to check
out all the
values
- The algorithm is simpler to use
- Binary search
- an ordered list is
divided into 2 with
each comparison
- The worst case
scenario that it only
checks half of the
value
- The algorithm is longer and more complex to
use
- Decomposition
- Breaking down a
large problem into
smaller
sub-problems
- they can be tested independently
- There is not always
one right answer.
- Abstraction
- Representing 'real world'
problems in a computer using
variables and symbols
- also removes
unnecessary
elements from
the problem
- Bubble sort
- moving through a list
repeatedly, swapping
elements that are in the
wrong order
- Merging Lists
- Split all
elements into
individual lists
- Compare the
first element in
both lists
- Put the smallest
into a new list
- Compare the next element of 1
list with the second element of
the 2nd list
- Put the smallest into a new list
- Repeat until
merged
- Insertion sort
- each items is taken
in turn, compared to
the items already in
a list and placed in a
correct position
- Ordered list
- Elements are
arranged in
sequence
- Flowchart
- They can be used
to represent an
algorithm
- Shows the data that is
input and output
- Shows the
processes that
take place
- Shows the decisions
and repetition that
takes place
- Pseudocode
- Means 'fake code'
- It's a partway between
English language and
programming code
- Dry run
- running through an algorithm with
sample data, running each step
manually
- Trace table
- a table that follows the
values of variables to check
for accuracy