Digital Technology, Programming & Coding

An algorithm is a precise ordered method for solving a task. Decomposition breaks a large problem into smaller steps; abstraction retains the details needed for a particular purpose. A variable is a named place for a value. Assignment replaces its current value: total = total + price first evaluates the right side, then stores the result. This differs from an equation asserting two equal quantities. A dry-run trace records values after each step.

Integers represent whole numbers; real values represent quantities with fractions, subject to representation limits. Strings represent text and Booleans represent true or false. Python can infer types at runtime, whereas examination pseudocode may explicitly declare them. INPUT and OUTPUT describe receiving and presenting data; converting text to an integer can fail if the text is not a valid number. Validate data before relying on it, and do not silently treat invalid input as zero.

A flowchart connects start/end, input/output, processing and decision symbols. Pseudocode expresses the same logic without requiring a particular language. Follow the order, define each variable before using it, and keep the task finite when it is intended to terminate. The examples here use fictional numbers rather than personal information. These are selected IGCSE-style foundations; Python syntax and Cambridge examination notation are related learning tools, not interchangeable official mark schemes.

Selection chooses a branch according to a Boolean expression. IF temperature >= 30 selects a cooling message at 30 as well as above 30. AND requires both conditions to hold, OR requires at least one, and NOT reverses a Boolean result. An IF/ELSE chooses one branch; several independent IF statements can select several actions. State the intended boundaries explicitly because a one-character change can alter which cases are included.

Iteration repeats operations. A count-controlled loop runs a defined number of times; a condition-controlled loop repeats according to a condition. In Python, range(1, n + 1) includes the values one through n because the stopping value is excluded. A total accumulator starts at zero, while a counter tracks repetitions. Record the counter, current input and total after each iteration to make the behaviour visible rather than guessing from the source code.

Testing distinguishes normal, boundary and invalid data. For a demonstration accepting integers one to twenty, one and twenty are valid boundaries and zero is outside the allowed range. A loop should make progress toward termination. The practical trace on this page is bounded to twenty iterations and evaluates a fixed algorithm only; it is not an unrestricted interpreter. This makes results predictable without running pasted code or contacting another service.

A function groups a reusable operation and can return a result. Parameters receive arguments supplied by the caller; local variables belong to that invocation. For def area(width, height): return width * height, area(3, 4) returns twelve. Returning a value differs from printing it. Break a program into small responsibilities, such as validating input, calculating a result and presenting it, so each can be checked independently.

An array stores a sequence of elements accessed by index. Python lists can illustrate this idea, although their flexibility goes beyond a fixed-size examination array. Python indices begin at zero: [8, 3, 5][1] is three. Linear search examines elements in sequence until it finds the target or reaches the end. Binary search repeatedly narrows an ordered search interval, but requires appropriately sorted data; applying it to unsorted values is not a valid shortcut.

Bubble sort compares adjacent elements and swaps them if they are in the wrong order, repeating passes until sorted. A pass need not complete the whole sort. Use a trace table to record the actual intermediate states. At more advanced enrichment level, compare how work grows with input size rather than timing one tiny example and declaring a universal winner. Testing, readability and correct handling of empty or missing results matter as much as reaching a result once.

A relational table stores records as rows and fields as columns. A primary key identifies each record uniquely; a foreign key can link related tables. Data types and validation rules constrain what can be stored, but cannot prove a fact is true. Fictional inventory is a safe learning context: keep personal names, credentials and financial details out of classroom examples. A database query retrieves selected information rather than automatically changing all records.

SQL SELECT chooses columns, FROM names a table and WHERE filters rows. ORDER BY controls the result ordering and aggregate functions can summarise values. In a fictional inventory with items Pencil quantity 12 and Notebook quantity 3, SELECT item FROM stock WHERE quantity < 5 returns Notebook. Treat this as an explained query, not a connection to village data. Real database access needs authorisation, parameterised input and carefully limited permissions.

Boolean logic can be described with AND, OR and NOT gates and truth tables. For an alarm enabled AND door_open, only the case where both inputs are true activates the alarm. Networks carry data, web services process requests and automated systems act on outputs, creating privacy and security responsibilities. Validate input, restrict access, keep software updated and evaluate AI outputs critically. These applications connect IGCSE topics to wider technology; professional security and advanced computer science require deeper study beyond this introductory course.