SACE Stage 2 Digital Technologies cheat sheet

Decomposition splits a complex problem into smaller sub-problems that can be solved and tested independently.

Pattern recognition identifies recurring structures so a general solution replaces many specific ones.

Abstraction removes detail irrelevant to the current problem, keeping only features needed to solve it.

An algorithm is a finite, ordered, unambiguous sequence of steps that terminates with a result.

Three core control structures: sequence (steps in order), selection (if/else branching), iteration (loops).

Pseudocode and flowcharts document logic before coding; flowchart symbols: oval = start/end, diamond = decision, parallelogram = input/output, rectangle = process.

Trace tables record variable values after each step to verify an algorithm and locate logic errors.

Linear search is O(n) and works on unsorted data; binary search is O(log n) but requires sorted data.

Big-O describes growth of run time or space as input size n grows; O(1) < O(log n) < O(n) < O(n log n) < O(n^2).

The software development life cycle: requirements analysis, design, implementation, testing, deployment, maintenance.

Waterfall is sequential with fixed requirements; Agile uses short iterations and continuous stakeholder feedback.

Functional requirements state what the system must do; non-functional requirements state qualities such as performance, security and usability.

A data dictionary defines each field's name, data type, format, size, validation rule and default value.

Validation checks input against rules (range, type, length, presence); verification confirms data was transferred or entered accurately.

Test data types: valid (accepted), invalid (correctly rejected), boundary (at the edge of an allowed range) and extreme (far outside the range).

Black-box testing checks outputs against inputs without seeing code; white-box testing exercises internal paths and branches.

Version control tracks changes, supports rollback and allows parallel branches to be merged.

Usability heuristics include consistency, clear error messages, user control and undo, and minimising memory load on the user.

Data are raw symbols; information is data processed into a context that gives it meaning for a decision.

One byte = 8 bits; 1 KB = 1024 bytes, 1 MB = 1024 KB, 1 GB = 1024 MB, 1 TB = 1024 GB.

A relational table stores records (rows) of fields (columns); a primary key uniquely identifies a record and a foreign key references another table's primary key.

Normalisation reduces redundancy: 1NF removes repeating groups, 2NF removes partial dependencies, 3NF removes transitive dependencies.

SQL essentials: SELECT columns FROM table WHERE condition ORDER BY column; INSERT, UPDATE, DELETE modify rows; JOIN combines related tables.

A DBMS enforces integrity constraints such as entity integrity (no null primary key) and referential integrity (foreign keys must match).

Data quality dimensions: accuracy, completeness, timeliness, relevance, consistency and validity.

Quantitative data is numeric and analysable statistically; qualitative data is descriptive and analysed thematically.

Data visualisation choice: bar chart compares categories, line graph shows trends over time, pie chart shows parts of a whole, scatter plot shows correlation.

The fetch-decode-execute cycle: CPU fetches an instruction from memory, decodes it, executes it, then stores the result.

CPU performance depends on clock speed, number of cores, cache size and instruction pipelining.

Von Neumann architecture stores program and data in the same memory; Harvard architecture uses separate instruction and data memories.

RAM is volatile working memory; ROM is non-volatile; SSD and HDD are secondary storage; cache is fastest and smallest.

A network protocol is an agreed set of rules for exchange; TCP guarantees ordered delivery while UDP is faster but unreliable.

An IP address identifies a device on a network; DNS translates domain names into IP addresses.

Encryption protects confidentiality in transit; hashing is one-way and used for integrity checks and password storage.

Threats include malware, phishing, denial-of-service and social engineering; controls include firewalls, authentication, backups and patching.

Digital impacts: automation changes employment, e-waste and data centres raise environmental costs, and data collection raises privacy and consent issues.