Summary GCSE OCR J277 Computer Science Paper 2 revision notes - BY CSandRS
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Course
Computing
Institution
GCSE
FOR PAPER 2, I have seperate revision notes for paper 1 and a coding guide.
Every J277 specification point covered. I recommend to copy and paste each topic into ANKI (flashcard app) and memorise them.
For context I attained grade 9 in 2024 for CS.
ALGORITHMS
COMPUTAIONAL THINKING
COMPUTATIONAL THINKING: The process used to
solve complex problems. Formulating a problem in
such a way that a computer can carry it out
ABSTRACTION: Identifying the key parts and hiding
details that aren’t necessary, so only the important
parts are focused on.
-Simplifies a problem, makes it easier to
understand and create a solution
DECOMPOSITION: Breaking complex problems
down into smaller manageable parts which are
easier to solve
- Once each sub-problem is small and simple
enough, it can be tackled individually
SEARCHING AND SORTING ALGORITHMS
-Makes problems easier to solve
-Different people can work on different parts - SEARCHING ALGS:
reducing development time 1) LINEAR SEARCH: Start from the beginning of the
-Modules/components developed in one program data set.
can easily be used in another - Each item is checked in turn to see if it matches
ALGORITHMIC THINKING: Solving problems by the search criterion
defining the steps and sequence needed - Program terminates when it is found
ALGORITHM: A sequence of steps that can be A) - Simpler to code than binary
followed to complete a task - Can be used on any type of list, ordered or
DESIGNING ALGORITHMS unordered
INPUT: Anything which needs to be supplied to the D) Very inefficient/slow on larger lists
program 2) BINARY SEARCH: Calculate the midpoint (round
PROCESS: The data is then processed in some way up/down) then check if it matches SC.
OUTPUT: The end result after processing -If it doesn’t then eliminate it and the impossible
STRUCTURE DIAGRAMS: A graphical method of half
decomposing problems, with each layer breaking A) More efficient than linear - generally takes fewer
down the layer above it into smaller sub-problems comparisons
Advantages: 1) Modules can be written -Suitable for large lists
independently D) Requires list to be ordered
2) Modules can be tested individually SORTING ALGS:
3) Reused elsewhere 1) BUBBLE SORT: It compares each item with the
FLOWCHART: A graphical representation of an next and swaps them if they are out of order
algorithm using shapes to denote each step and - Passes are made and the algorithm ends when no
arrows to show the direction of flow of data swaps have been made in a particular pass
TRACE TABLE: A tool used to follow each line of the A) Easy to code, good for small data sets
algorithm through, step by step; it shows the - Efficient way to check if the list has already been
contents of each variable and how they change ordered
-It is used to spot logic errors -Doesn’t use much memory as all the sorting is
done in the original list
D) Very inefficient especially for larger lists
, 2) INSERTION SORT: Splits the list into 2 parts: 3) ITERATION: code is repeated (looped) until a
sorted & unsorted. specified condition is met
-Initially only the first value is sorted. Then you a) Count-controlled iteration: Code repeats a
compare the second value with the first one and defined amount of times (FOR)
swap if needed b) Condition-controlled iteration: checks the
-continue comparing the value and putting it in its condition each time and decides whether to repeat
correct place in the sorted part the loop again. (WHILE, DO UNTIL)
A) Easily coded, copes well with small lists ARITHMETIC & BOOLEAN OPERATORS
-Doesn’t require additional memory as everything ARITHMETIC OPERATIONS: used to carry out basic
is done on the original list mathematical operations on numerical values
D) Slows down as the list gets bigger COMPARISON OPERATORS: used to evaluate
expressions to a Boolean True or False condition
3) MERGE SORT: Uses a ‘divide and conquer’ COMPARISON Arithmetic operators
approach to split data into individual lists then OPERATORS
merge them back into order == Equal to + Addition
STAGE 1 (DIVIDE): The list is successively divided in != Not equal to – Subtraction
< Less than * Multiplication
half forming two sublists till each sublist is length 1
<= Less than/equal to / Division
STAGE 2 (CONQUER): Each pair of sublists is
> Greater than MOD / % Modulus
repeatedly merged to produce new sorted sublists >= Greater than/equal DIV / // Quotient
till only one remains. to
A) Very efficient and quicker for larger lists ^ / ** Exponentiation (to
- Consistent running times the power)
D) Slower than other algorithms for smaller lists MODULAS: returns the remainder after the division
- Uses more memory, to create sublists DIV: returns the whole number after the division
PROGRAMMING FUNDAMENTALS BOOLEAN OPERATOR: allows multiple conditions
VARIABLE: A name used to identify a memory to be evaluated
location used to store a value that can change AND - requires both conditions to be True
while the program is running OR - Requires one or both conditions to be True
CONSTANT: A name used to identify a memory NOT - Reverses the True or False outcome from the
location used to store a value that cannot change condition
while the program is running ORDER OF OPERATIONS: Brackets, NOT, AND, OR
ASSIGNMENT: Giving a constant/variable a value DATA TYPES
PROGRAMMING CONSTRUCTS INTEGER: Whole numbers
1) SEQUENCE: The execution of one line of code, REAL/FLOAT: Numbers with a decimal
one after another, in order. BOOLEAN: Used to store True or False
2) SELECTION: When a program branches CHARACTER: single item from a character set
depending on a condition, used to make a decision (letter, number, symbol)
based on Boolean values. STRING: A sequence of characters
a) IF/ELSEIF CASTING: The conversion from one data type to
b) SWITCH/CASE another
-Join strings together/do maths with numbers input
Using correct data type makes code more:
1) Memory efficient 2) robust 3) Predictable
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