Structured approach

Improving the clarity and maintainability of programs using three basic structures:

1. Sequence
2. Selection
3. Iteration

Designing algorithm

Flow diagrams and pseudocode are two methods that are used for designing algorithms

A useful strategy to test an algorithm is to draw a trace table

Thinking concurrently

Parallel computing requires multiple processors each executing different instructions simultaneously to speed up computations

Pros/cons

• Can render 3D objects quicker
• Browsers can display several pages with processors doing different tasks
• Difficult to coordinate the processors and tasks might be faster using one processor

Concurrent processing happens when multiple processes are running with each having a slice of processor time

Pros/cons

• Increased program throughput
• Less time wasted by processor
• Large amounts of users can cause heavy computation programs to take longer to complete

Computable problems

A problem is computable if an algorithm can solve every instance in a finite number of steps

Methods of problem solving

1. Enumeration (trying every possible solution)
2. Simulation (Designing a model of a real system to understand its behaviour and evaluate strategies)
3. Theoretical approach
4. Creative solution

Strategies for problem solving

Top-down design

Splitting into smaller tasks

Divide and conquer

Reduces the size of the problem with every iteration

Problem abstraction

Removing details of a problem until it is represented in a way that it is possible to solve

Automation

Building and putting into action models to solve problems

Take a physical world scenario and make a mathematical model then automate which reveals more about the physical world scenario

Visualisation

The way a problem is presented is often important for finding solutions

Backtracking

To find a solution you might have to make a series of decisions but you might have issues like:

• Not having enough information
• Each decision leads to a new set of choices
• One or more of the sequences may be a solution

Backtracking is used to try different sequences until you find the solution

Data mining

Digging through big data sets to discover hidden connections and predict future trends

Intractable problems

A problem where an algorithm exists for their solution but takes an unreasonably long time

Heuristic methods

Solving a simpler/restricted version of the problem

Performance modelling

Simulating different user and system loads

Pipelining

Splitting tasks into smaller parts and overlapping the processing of each task