1. Programming Fundamentals
• Variable – Named storage for data that can change.
• Constant – Data value that cannot change after assignment.
• Data Types – Integer, real/float, Boolean, character, string, array.
• Operators – Arithmetic (+, -, *, /), relational (==, !=, >, <), logical
(AND, OR, NOT).
• Assignment – Storing a value in a variable using =.
• Expression – Combination of variables, constants, and operators that
evaluates to a value.
• Statement – A single instruction executed by the program.
• Control Structures –
• Sequence: statements executed one after another.
• Selection: decision making (if, else if, else, switch).
• Iteration: loops (for, while, do while).
2. Subroutines and Functions
• Procedure – A subprogram that performs tasks but does not return a
value.
• Function – A subprogram that returns a value.
• Parameters/Arguments – Data passed into subroutines.
• Return Value – Output returned from a function.
• Local Variable – Variable declared inside a subroutine; scope limited
to that subroutine.
• Global Variable – Variable accessible anywhere in the program.
• Recursion – A function calling itself with a base case to terminate.
3. Data Structures
• Array – Fixed-size collection of elements of the same data type,
indexed from zero or one.
• List – Ordered collection of items; may be dynamic.
• Stack – Last In First Out (LIFO) structure; supports push/pop
operations.
• Queue – First In First Out (FIFO) structure; supports enqueue/dequeue.
• Linked List – Nodes linked with pointers; dynamic size, easy
insertion/deletion.
• Tree – Hierarchical structure with nodes; root, child, parent, leaf
nodes.
• Graph – Set of nodes (vertices) connected by edges; can be
directed/undirected.
• Hash Table – Uses hashing function to map keys to values for efficient
lookup.
4. Searching and Sorting Algorithms
• Linear Search – Checks each item sequentially; O(n) complexity.
• Binary Search – Repeatedly divides sorted list in half; O(log n)
complexity.
• Bubble Sort – Repeatedly swaps adjacent elements; O(n²) complexity.
• Insertion Sort – Builds sorted list one item at a time; O(n²) worst
case.
• Merge Sort – Divide and conquer; splits list and merges sorted halves;
O(n log n).
• Algorithm Efficiency – Big-O notation describes time/space complexity.
5. File Handling
• File – A collection of data stored on secondary storage.
• Sequential Access – Reading/writing data in order from start to finish.
• Random Access – Accessing data directly at a specific position.
• Binary File – Stores data in binary format (not human-readable).
• Text File – Stores data as readable characters.
• Variable – Named storage for data that can change.
• Constant – Data value that cannot change after assignment.
• Data Types – Integer, real/float, Boolean, character, string, array.
• Operators – Arithmetic (+, -, *, /), relational (==, !=, >, <), logical
(AND, OR, NOT).
• Assignment – Storing a value in a variable using =.
• Expression – Combination of variables, constants, and operators that
evaluates to a value.
• Statement – A single instruction executed by the program.
• Control Structures –
• Sequence: statements executed one after another.
• Selection: decision making (if, else if, else, switch).
• Iteration: loops (for, while, do while).
2. Subroutines and Functions
• Procedure – A subprogram that performs tasks but does not return a
value.
• Function – A subprogram that returns a value.
• Parameters/Arguments – Data passed into subroutines.
• Return Value – Output returned from a function.
• Local Variable – Variable declared inside a subroutine; scope limited
to that subroutine.
• Global Variable – Variable accessible anywhere in the program.
• Recursion – A function calling itself with a base case to terminate.
3. Data Structures
• Array – Fixed-size collection of elements of the same data type,
indexed from zero or one.
• List – Ordered collection of items; may be dynamic.
• Stack – Last In First Out (LIFO) structure; supports push/pop
operations.
• Queue – First In First Out (FIFO) structure; supports enqueue/dequeue.
• Linked List – Nodes linked with pointers; dynamic size, easy
insertion/deletion.
• Tree – Hierarchical structure with nodes; root, child, parent, leaf
nodes.
• Graph – Set of nodes (vertices) connected by edges; can be
directed/undirected.
• Hash Table – Uses hashing function to map keys to values for efficient
lookup.
4. Searching and Sorting Algorithms
• Linear Search – Checks each item sequentially; O(n) complexity.
• Binary Search – Repeatedly divides sorted list in half; O(log n)
complexity.
• Bubble Sort – Repeatedly swaps adjacent elements; O(n²) complexity.
• Insertion Sort – Builds sorted list one item at a time; O(n²) worst
case.
• Merge Sort – Divide and conquer; splits list and merges sorted halves;
O(n log n).
• Algorithm Efficiency – Big-O notation describes time/space complexity.
5. File Handling
• File – A collection of data stored on secondary storage.
• Sequential Access – Reading/writing data in order from start to finish.
• Random Access – Accessing data directly at a specific position.
• Binary File – Stores data in binary format (not human-readable).
• Text File – Stores data as readable characters.
