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neurologyYou need to know

• The project is assessed through analysis worth 10 marks, design worth 15 marks, development worth 25 marks, and evaluation worth 20 marks.
• A problem is suitable for a computational solution when it can be represented using data and solved through defined inputs, processes, outputs and algorithms.
• A computational approach is justified when it offers relevant benefits such as automation, speed, accuracy, repeatability, data storage or handling complex decisions.
• Stakeholders are individuals or groups who affect, use or are affected by the solution, and their different needs can influence its requirements and interface.
• Research into the problem domain, stakeholders and similar solutions provides evidence for selecting suitable features, algorithms, data structures and interface conventions.
• The essential features are the functions that the solution must provide to address the identified problem and stakeholder needs.
• Limitations are constraints or weaknesses that restrict what the proposed solution can do, such as limited time, data, hardware, compatibility or project scope.
• Functional requirements specify what the solution must do, while non-functional requirements describe qualities or constraints such as usability, performance, reliability and security.
• Hardware and software requirements identify the equipment, operating environment, programming language, libraries and other resources needed to develop or run the solution.
• Success criteria must be specific and measurable so that evidence from testing can determine whether each requirement has been achieved.
• Decomposition divides a complex problem into smaller, manageable sub-problems that can be designed, implemented and tested separately.
• A complete design explains the overall structure of the solution and shows how its components and algorithms work together.
• Usability features include clear navigation, consistent layouts, readable output, suitable feedback, error messages and accessibility choices appropriate to the target users.
• Variables store individual values, data structures organise related data, and classes combine attributes and methods to represent entities within an object-oriented solution.
• Validation checks whether input data is sensible and acceptable, whereas verification checks whether data has been entered or transferred accurately.
• A test plan identifies the feature being tested, the test data, the expected result and the reason for the test, including normal, boundary and erroneous data where appropriate.
• Iterative development repeatedly designs, implements, tests and refines parts of the solution, using evidence from each iteration to guide the next.
• A prototype is an early or partial implementation used to investigate requirements, interfaces or technical approaches before completing the final solution.
• Robustness is the ability of a solution to handle invalid, unexpected or extreme inputs without crashing or producing uncontrolled behaviour.
• Evaluation uses development tests, final robustness tests and stakeholder feedback to judge success criteria, usability, maintainability and priorities for further development.

• Identify a problem's inputs, processes, outputs and algorithmic elements, then justify why a computational approach is appropriate.
• Identify relevant stakeholders and explain how the proposed functions and usability features address their specific needs.
• Research the problem and comparable solutions, then use referenced findings to justify chosen approaches, essential features and acknowledged limitations.
• Specify functional and non-functional requirements, appropriate hardware and software, and measurable success criteria linked to the problem analysis.
• Decompose the problem into coherent sub-problems and justify how their solutions will combine into a complete system.
• Design the solution using structured algorithms, interface plans, variables, data structures, classes and validation rules, justifying each significant choice.
• Construct a test plan containing normal, boundary and erroneous data, expected outcomes and reasons for tests during iterative and post-development testing.
• Develop the solution iteratively, annotating prototypes, code changes, test results, decisions and remedial actions so that progress is clearly evidenced.
• Perform final robustness and usability testing, recording actual outcomes and relevant stakeholder feedback as annotated evidence.
• Evaluate the finished solution against every success criterion using test evidence, then assess usability, maintainability, limitations and realistic opportunities for further development.