2.2.2 Computational methods
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2.2.2 A) Features that make a problem solvable by computational methods
Solved within a finite realistic time typicaly consists of inputs. ouputs and calcualtuions. depends on processing power speed and memory
2.2.2 B) Problem recongnition What is needed
Stakeholders requirements definition of problem and requirments analaysising strength and weekeness with current way problem being solved considering type of data inputs and outputs stored data and amount of data
2.2.2 C) Problem decomposition aim Adv
problem continously broken down into smaller problem this continuies still each sub problem can be represented as self contained subroutines aim to reduce the complexity spillting into smaller section may allow use of precde modules or libaries makes project easier to manage allow for development in parallel easier and simplier to debug easier to indentify, locate and mitiage errors
2.2.2 D) Use of divide and conquer
Half problem every iteration soltuion to subproblem recomined to form final solution this greater simplifies computering problem logn difficult to trace and stack overflow
2.2.2 E) Use of abstraction
execessive details are removed to simplify a problem focus on core aspect more manageable projects
2.2.2 F) problem solving stratigies
• backtracking • data mining • heuristics • performance modelling • pipelining • visualisation to solve problems
2.2.2 F) problem solving stratigies backtracking
Use algorithm oftem recursiving if a path found to be invalid it will backtract to previous stage to find another path
2.2.2 F) problem solving stratigies data mining
Used to identify patterns or outliers in large sets of data used to spot trends or identify correlation between data assisting busniess and market decisions data privacy v
2.2.2 F) problem solving stratigies heuristics
Heuristic are a non optimal approach to problem solving which are used to find an approximate soltuion to a problem which solution is unreasonable time consuming or recousies intensive heurisitc is not perfectly accurate or complete it finds a good enough solution used for untraceable problems
2.2.2 F) problem solving stratigies performance modelling
PM elminates the need for true pm by provioding mathematic methods to test a varied of loads of different OS provides a cheaper less time consuming or safer method of testing applications useful for critical computers systems where its not safe to do real time runs before system can be implemeneted
2.2.2 F) problem solving stratigies pipelining
Pipelining is a process that allows for a project to be deliverd faster as modules are divided into individuals. different task can be designed in parallel
2.2.2 F) problem solving stratigies visualisation
Data can be presented in a way that is easier for user to understand. this makes it possible to indentify trends not otherwise obvious may be represented in tree’s charts graphs etc.