General Algorithms (Edexcel A Level Further Maths: Decision Maths 1)

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Introduction to Algorithms

What is an algorithm?

  • An algorithm is a set of precise instructions, that if strictly followed, will result in the solution to a problem
    • Algorithms are particularly useful for programming computers
      • computers can process huge amounts of data and perform millions of calculations in very short time frames
    • Robots would be programmed to follow an algorithm in order to complete a task
      • e.g.  a robot vacuum cleaner or lawn mower
    • Algorithms can be performed by human beings too!
      • e.g.  the recipe and cooking instructions for a cake, the instructions to build a Lego set

What does an algorithm look like?

  • Algorithms may be presented in a variety of ways
    • A list of instructions, in order, written in words/text
    • Pseudocode - this is a mixture of text and very basic computer commands/code
      •  let statements, if statements and loops are common but easy enough to follow without any knowledge of a formal computer programming language
    • Flow charts are a visual way of presenting the steps of an algorithm
      • they clearly show the order of instructions and any parts of an algorithm that may need repetition

What else do I need to know about algorithms?

  • Some algorithms do not always provide an optimal (best) solution
    • but will give a solution that is sufficient for the purpose
  • For example, a band touring the UK may use an algorithm to find the shortest route between the different cities/venues to minimise their travelling expenses
    • if the algorithm is inaccurate by say, 200 miles, it is not going to make much difference overall - the band will be travelling thousands of miles in total so 200 miles is relatively little
  • In modern, complicated real-life situations a compromise between the speed and efficiency of an algorithm and the accuracy of the solution it provides is often needed
  • When using an algorithm with a small amount of data - as exam questions will do due to time restraints - it is tempting to use common sense, intuition and basic mathematical skills to 'see' the solution
    • to show understanding of how an algorithm works it is crucial to stay in 'robot mode'
      • i.e.  follow the algorithm precisely and accurately without taking any 'shortcuts' (however obvious they may seem)

Examiner Tip

  • Showing that you have followed an algorithm precisely includes
    • knowing, or using checks built into the algorithm to know, that an algorithm is complete
    • stating (or 'printing') any 'output' at the end if that is what an algorithm instruction requires
      • do not 'assume' the output is the last number in your working

Flow Charts

What is a flow chart?

  • A flow chart is a diagrammatic way of listing the instructions to an algorithm
  • Flow charts lend themselves to algorithms that have
    • conditional instructions
      • e.g.  Is a greater than b?  If the answer is yes, the flow chart directs the user to one instruction but if the answer is no, the flow chart directs the user to a different instruction
    • repetitive parts or stages

What do the different shaped boxes in a flow chart mean?

  • Each command in a flow chart is written inside a shape - the actual shape will depend on the type of command 
    • Ovals are used to represent the start and the end
    • Rectangles are used to represent instructions
    • Diamonds are used to represent questions

vgxxM1YG_flow-shapes

  • Alternative names are sometimes used for these boxes
    • The start and end are sometimes called termination
    • Question boxes are sometimes called decision boxes
    • The word 'print' may be used instead of 'output' for the final answer/result

How do I work with a flow chart?

  • Following a flow chart is generally intuitive but make sure you follow the instructions carefully
    • write down any values when instructed to
      • this will often involve completing a table of values
      • if there is a specific instruction to 'output' the final answer, make sure it is separate to the table
  • Some questions may ask for a description of what the flow chart/algorithm produces

Examiner Tip

  • If a question provides a table that is to be filled in with values that change, also bear in mind that some values may not change
    • In such instances, only the first entry for a value may end up being entered
      • Not every cell in every row/column will necessarily need completing
      • Follow the instructions from the flow chart ('robot mode'!)

Worked example

An algorithm is presented as a flow chart, shown below.

flow-chart-we-qu

a)
Describe what the algorithm achieves.

The final instructions give us a clear idea of what is going on in this case!

The algorithm works out if the input value n is a square number or not

b)
For the input n equals 23, use the flow chart to perform the algorithm.
Complete the table.

n k p Is p greater than n? Is p equals n?
         
         
         
         
         
         
         
         
Output:  

The first instruction is to input n, so fill 23 under n in the first row of the table
The next two instructions are to let k equals 1 and to let p equals k squared, so also in the first row we can fill in 1 and 1 for k and p 

n k p Is p greater than n? Is p equals n?
23 1 1    
         
         

The next instruction is the first question, is p greater than n; the answer is no
For the answer no, the flow chart directs us to another question, is p equals n; the answer is no and so we can complete the top row of the table

n k p Is p greater than n? Is p equals n?
23 1 1 NO NO
         
         

The flow chart now updates the value of k; indicate this on the second row of the table
The flow chart then takes us back round the loop of finding and testing the value of p
n does not get updated so only appears in the first row of the table

n k p Is p greater than n? Is p equals n?
23 1 1 NO NO
  2 4 NO NO
         


Continuing to precisely follow the flow chart the table can be completed
The output needs stating at the end as per the flow chart instructions
Note how the question "is p equals n?" does not get considered as the algorithm outputs and stops following the answer 'yes' to the question "is p greater than n?"

n k p Is p greater than n? Is p equals n?
23 1 1 NO NO
  2 4 NO NO
  3 9 NO NO
  4 16 NO NO
  5 25 YES  
         
         
         
Output: 23 is not a square number

Pseudocode & Text-based Algorithms

What is pseudocode?

  • Pseudocode is a way of writing an algorithm that is a mixture of words and computer programming language
  • Pseudocode does not follow any conventions that a formal computer programming language (such as Python) would
    • knowledge or experience of computer programming is not expected

What commands are used in pseudocode?

  • Commands given in pseudocode are intuitive to follow
    • Examples include
      • 'Input ...' - the value(s)/data that the algorithm needs to be told
      • 'Let ..." - assign or update a value to a variable
      • 'If ...' - a conditional statement, the outcome of which will lead to different parts of the algorithm
      • 'Int ...' - the integer part of a value
      • 'While ...' - whilst the condition that follows is true, keep doing
      • 'Output ...' or 'Print ...' - usually at the end of an algorithm this instruction essentially means 'write down the final answer' !

How do I work with an algorithm in pseudocode? 

  • To show an algorithm in pseudocode has been followed precisely, the result of each command is usually jotted down
    • this may be in the form of a table 
    • some values may be changed or updated during the algorithm
  • Ignore any commands that do not apply
    • e.g.  in an if statement
  • Zeller's algorithm is given in pseudocode below
    • This finds the day of the week for any date in the Gregorian calendar (1582 onwards)
      • This version of the algorithm assumes that days will be inputted as 1-31, months 1-12 (rather than words) and years are four digits
    • The algorithm may give inaccurate results or 'crash' if unexpected values are input
      • Try using the algorithm to find the day of the week 30th February 2024 falls on
      • No such date exists, but 29th February 2024 is a Thursday - does the algorithm give the answer Friday?

Y0vDfHD4_zeller

    • Zeller's algorithm is most commonly used to find which day of the week on which a person was born using their date of birth
    • There are many variations of Zeller's algorithm, some are more complicated than others!

What are text-based algorithms?

  • Text-based algorithms refer to instructions that are given in sentences
    • Each instruction may be labelled with 1, 2, 3, and so on
    • Just like in many of our Save My Exams Revision Notes!
      • Step 1 ..., Step 2 ..., etc
  • The following text-based algorithm is for a very basic single player dice game
    • The aim of the game is to minimise the number of rolls of the dice needed to reach 'Stop'

QfVompti_text-alg-dice

Order of an Algorithm

What is the order of an algorithm?

  • The order of an algorithm refers to its complexity
    • The complexity of an algorithm will depend on
      • the number of steps/instructions involved
      • the amount of 'input' data
    • A well constructed algorithm will be both accurate and efficient
  • The order of an algorithm is usually determined by the maximum number of steps an algorithm involves
    • For example, an algorithm that finds a particular item in a list would, at most, search every item on that list
      • the number of steps involved is a function of the number of items on the list
      • the algorithm would be of linear order
    • Quadratic order would mean the number of steps involved is a function of the square of the size of the input data
    • Cubic order would be a function of the cube of the size of the input data

How is the order of an algorithm described?

  • The order of an algorithm is described by a mathematical function
      • square roots, logarithms, exponentials, etc
      • linear, quadratic and cubic are the most common
  • Two different algorithms may both be of quadratic order but still take differing amount of times to complete
    • this is because the exact form of the quadratic functions may differ
    • e.g.  For an input of size n, one of the algorithms may have the number of steps 1 half n open parentheses n plus 1 close parentheses but the other 1 half n open parentheses n minus 1 close parentheses
      • both are quadratic functions but for the same value of n space open parentheses n not equal to 0 close parentheses they take different values

How do I find the order of an algorithm?

  • In simple cases the order of an algorithm can be determined by considering the maximum number of steps involved
    • the order is determined by considering the worst case scenario
    • an algorithm finding an item in a list would, at most, search every item in the list
      • the algorithm is therefore of linear order
  • In many cases - particularly where the order is not easily determined, it will be given
  • The order of an algorithm can be used to find an approximate time of completion
    • The time will only be an approximation as
      • only the order (not the exact function) is being used
      • the order is determined by the maximum number of steps involved (the worst case scenario)

How do I find (an estimate for) the time an algorithm will take to complete using its order?

  • The time it takes an algorithm to complete is estimated using proportionality
    • Doubling the size of the input data to an algorithm of linear order would increase the approximate time of completion 2 times
    • Doubling for quadratic order would increase the approximate time of completion bold 2 to the power of bold 2 bold equals bold 4 times
    • Doubling for cubic order would increase the approximate time of completion bold 2 to the power of bold 3 bold equals bold 8 times
  • The same use of proportion applies to less common orders too
    • for an algorithm of order square root of n, doubling the size of the input data would increase the approximate time of completion square root of bold 2 times
    • e.g.  if an algorithm takes 5 seconds to process an input of size 20, then the algorithm will take approximately 5 cross times square root of 4 equals 5 cross times 2 equals 10 seconds to process an input of size 80
  • Depending on the nature of an algorithm, the use of the letter n may take different meanings
    • the 'input size' n may refer to the number of data items or it could be the actual size of the input
      • e.g.  in a sorting algorithm n may be the number of items to be sorted but in an algorithm to determine if a number is prime, n may be the number being tested
    • when referring to the order of an algorithm, n may be the scale by which the input size has increased
      • e.g.  in an algorithm of quadratic order, increasing the input size by n, will approximately increase the time the algorithm takes to complete by n squared

Examiner Tip

  • The words order and complexity are often used interchangeably
    • quadratic order and quadratic complexity are the same thing

Worked example

An algorithm for sorting a list of n values into ascending order has order n ln space n.
A computer running the algorithm takes 0.12 seconds to apply the algorithm to a list of 3000 values.

Estimate the time it would take the computer to apply the algorithm to a list of 60 000 values.

It takes 0.12 seconds for an algorithm of order 3000 space ln space open parentheses 3000 close parentheses

Divide the time by the order and then multiply it by the order of an algorithm for a list with 60 000 items

fraction numerator 0.12 over denominator 3000 space ln space open parentheses 3000 close parentheses end fraction cross times 60000 space ln space open parentheses 60000 close parentheses equals 3.298 space...

An estimate of the time the computer would take to apply the algorithm to 60 000 values is 3.30 seconds ( 3 s.f.)

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Paul

Author: Paul

Expertise: Maths

Paul has taught mathematics for 20 years and has been an examiner for Edexcel for over a decade. GCSE, A level, pure, mechanics, statistics, discrete – if it’s in a Maths exam, Paul will know about it. Paul is a passionate fan of clear and colourful notes with fascinating diagrams – one of the many reasons he is excited to be a member of the SME team.