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The stage that identifies requirements and creates the data model is Analysis."},{"text":"Implementation.","correct":false,"explanation":"Implementation converts completed designs into working code rather than investigating the original problem. Requirements and the data model are established during Analysis."},{"text":"Testing.","correct":false,"explanation":"Testing checks whether an implemented system meets its requirements; it does not initially establish them. Turning the real-world problem into requirements and a data model is Analysis."}]},{"id":"12dc7916-d622-47db-a833-aaa5bfa011c4","cardType":"basic","points":1,"front":"Which stage plans data structures, algorithms, modules and the user interface?","back":"Design.","mcqOptions":[{"text":"Design.","correct":true,"explanation":"Design determines how the proposed system will meet its requirements by specifying its data structures, algorithms, modules and user interface before implementation begins."},{"text":"Analysis.","correct":false,"explanation":"Analysis determines what the system must do rather than planning its internal solution. Data structures, algorithms, modules and the interface are planned during Design."},{"text":"Implementation.","correct":false,"explanation":"Implementation translates existing plans into executable code; it should not be where the solution is first planned. These components are specified during Design."},{"text":"Testing.","correct":false,"explanation":"Testing evaluates the implemented system against expected results and requirements. The structures, algorithms, modules and interface used to build it are planned during Design."}]},{"id":"ad55747f-2730-41da-a2ce-e143a1b50ab2","cardType":"basic","points":1,"front":"During implementation, what are designed models and algorithms turned into?","back":"Data structures and executable code.","mcqOptions":[{"text":"Data structures and executable code.","correct":true,"explanation":"Implementation realises the design by representing the planned data model with suitable data structures and translating the designed algorithms into executable program code."},{"text":"Requirements and a data model.","correct":false,"explanation":"Requirements and a data model are outputs of analysis, not implementation. Implementation instead turns the designed models and algorithms into data structures and executable code."},{"text":"Module plans and interface designs.","correct":false,"explanation":"Module plans and interface designs belong to the design stage and are inputs to implementation. Implementation produces data structures and executable code from the completed designs."},{"text":"Test results and evaluation reports.","correct":false,"explanation":"Test results and evaluation reports are produced by testing and evaluation after code exists. Implementation converts models and algorithms into data structures and executable code."}]},{"id":"93f3d484-672f-4086-b487-ffee5d6a9cee","cardType":"basic","points":2,"front":"What is the main risk of starting coding before analysis and design?","back":"Software may run but not solve the right problem.","mcqOptions":[{"text":"Software may run but not solve the right problem.","correct":true,"explanation":"Without first establishing and modelling the genuine requirements, developers can produce technically functional software that addresses misunderstood needs and therefore fails its intended users."},{"text":"Software may run but use too much memory.","correct":false,"explanation":"Premature coding does not guarantee inefficient execution; the central danger is misunderstood requirements. Software may run but not solve the right problem."},{"text":"Software may run but have an unattractive interface.","correct":false,"explanation":"A poor interface is one possible design flaw, but it is not the main overall risk. Software may run but not solve the right problem because requirements were not established."},{"text":"Software may run but fail to compile correctly.","correct":false,"explanation":"Compilation depends on syntactic and semantic correctness, not primarily on prior analysis. The greater risk is that software may run but not solve the right problem."}]},{"id":"32d5b756-108e-4bc2-8f58-ea27b8f69977","cardType":"basic","points":1,"front":"Who must be interacted with to establish requirements?","back":"The intended users.","mcqOptions":[{"text":"The intended users.","correct":true,"explanation":"Intended users understand the tasks, needs and constraints the proposed system must address, so interacting with them helps analysts establish accurate and relevant requirements."},{"text":"The software developers.","correct":false,"explanation":"Developers provide technical expertise but may not understand the users’ real activities and needs. Analysts must interact with the intended users to establish requirements."},{"text":"The system testers.","correct":false,"explanation":"Testers assess whether software satisfies established requirements, but they are not necessarily the source of those requirements. Analysts must interact with the intended users."},{"text":"The rival companies.","correct":false,"explanation":"Competitors may inform market research but cannot define what this system’s users need. Requirements must be established through interaction with the intended users."}]},{"id":"b37f3861-c93d-48f9-a681-c7cc81c50e99","cardType":"cloze","points":null,"front":"A [ ] requirement says what the system must do; a [ ] requirement states qualities or constraints.","back":"A functional requirement says what the system must do; a non-functional requirement states qualities or constraints.","mcqOptions":[{"text":"A functional requirement says what the system must do; a non-functional requirement states qualities or constraints.","correct":true,"explanation":"Functional requirements describe behaviours, services or tasks the system must perform. Non-functional requirements specify constraints or quality characteristics such as security, reliability and response time."},{"text":"A non-functional requirement says what the system must do; a functional requirement states qualities or constraints.","correct":false,"explanation":"The categories have been reversed: behaviours the system must perform are functional requirements, while qualities and constraints are non-functional requirements."},{"text":"A technical requirement says what the system must do; a non-functional requirement states qualities or constraints.","correct":false,"explanation":"A technical requirement may describe a particular implementation constraint, but it is not the general category for system behaviour. Required behaviours are functional, while qualities or constraints are non-functional."},{"text":"A functional requirement says what the system must do; a operational requirement states qualities or constraints.","correct":false,"explanation":"Functional correctly identifies required system behaviour, but operational is not the standard contrasting category. Qualities and constraints are classified as non-functional requirements."}]},{"id":"b1ce1d28-ac5b-4cf8-9e36-027fe41d6500","cardType":"cloze","points":null,"front":"In a data model, an [ ] is a thing about which data is stored; an [ ] is its property.","back":"In a data model, an entity is a thing about which data is stored; an attribute is its property.","mcqOptions":[{"text":"In a data model, an entity is a thing about which data is stored; an attribute is its property.","correct":true,"explanation":"An entity represents a distinguishable real-world object or concept about which data is held. An attribute records a particular property or characteristic of that entity."},{"text":"In a data model, an attribute is a thing about which data is stored; an entity is its property.","correct":false,"explanation":"The terms have been reversed: an attribute is a property, not the thing being modelled. The thing is an entity, and its property is an attribute."},{"text":"In a data model, a relationship is a thing about which data is stored; an attribute is its property.","correct":false,"explanation":"A relationship describes an association between entities rather than a thing about which data is stored. That thing is an entity, while its property is an attribute."},{"text":"In a data model, an entity is a thing about which data is stored; a relationship is its property.","correct":false,"explanation":"Entity correctly names the thing being represented, but a relationship links entities rather than describing one of its properties. Such a property is an attribute."}]},{"id":"7d586319-9ab6-49e4-b137-22620ae65784","cardType":"cloze","points":null,"front":"[ ] represents only relevant features and ignores [ ].","back":"Abstraction represents only relevant features and ignores unnecessary detail.","mcqOptions":[{"text":"Abstraction represents only relevant features and ignores unnecessary detail.","correct":true,"explanation":"Abstraction reduces complexity by constructing a simplified representation containing the features relevant to the problem while deliberately omitting unnecessary detail."},{"text":"Decomposition represents only relevant features and ignores unnecessary detail.","correct":false,"explanation":"Decomposition divides a complex problem into smaller subproblems rather than creating a simplified representation. Abstraction represents relevant features and ignores unnecessary detail."},{"text":"Validation represents only relevant features and ignores unnecessary detail.","correct":false,"explanation":"Validation checks whether a system meets user needs rather than filtering a representation’s features. Abstraction is the process that retains relevance and ignores unnecessary detail."},{"text":"Abstraction represents only relevant features and ignores essential detail.","correct":false,"explanation":"Abstraction must retain essential features, so ignoring them would make the representation unsuitable. It simplifies a problem by ignoring unnecessary detail instead."}]},{"id":"ca723d1a-b921-42f0-9798-b3ea9032809f","cardType":"basic","points":2,"front":"How can a prototype help during analysis?","back":"Users can comment on a visible mock-up more easily than written requirements.","mcqOptions":[{"text":"Users can comment on a visible mock-up more easily than written requirements.","correct":true,"explanation":"A visible prototype gives users something concrete to inspect, making it easier to identify misunderstandings, omissions and unsuitable requirements during analysis."},{"text":"Developers can replace the written requirements immediately with completed program code.","correct":false,"explanation":"A prototype does not replace requirements with completed code. The benefit is that users can comment on a visible mock-up more easily than on written requirements."},{"text":"Analysts can avoid seeking user feedback once the initial requirements are recorded.","correct":false,"explanation":"Prototyping does not remove the need for user consultation. It improves consultation because users can respond more easily to a visible mock-up than to written requirements."},{"text":"Programmers can guarantee that implementation errors will not occur during development.","correct":false,"explanation":"A prototype is not intended to guarantee that implementation errors cannot occur. During analysis, its value is helping users comment on a visible representation of the proposed system."}]},{"id":"1a77026f-f526-4b97-bf1f-9d887c47c76b","cardType":"cloze","points":null,"front":"An [ ] approach develops software in small increments with frequent [ ] and revision.","back":"An agile approach develops software in small increments with frequent user feedback and revision.","mcqOptions":[{"text":"An agile approach develops software in small increments with frequent user feedback and revision.","correct":true,"explanation":"Agile development delivers software through small increments and repeatedly involves users. Their frequent feedback guides revisions as requirements and priorities evolve."},{"text":"An waterfall approach develops software in small increments with frequent user feedback and revision.","correct":false,"explanation":"The waterfall approach follows sequential stages rather than repeated small increments. The correct terms are agile and user feedback, reflecting iterative development shaped by users."},{"text":"An agile approach develops software in small increments with frequent hardware replacement and revision.","correct":false,"explanation":"Agile development relies on frequent user feedback, not hardware replacement, to review increments and revise the software in response to changing needs."},{"text":"An big bang approach develops software in small increments with frequent program termination and revision.","correct":false,"explanation":"The big bang approach lacks the controlled increments and feedback cycles described. An agile approach uses frequent user feedback to guide revision."}]},{"id":"5f8793e5-a6d8-44de-bfa3-a418c53de024","cardType":"basic","points":1,"front":"What does a specification provide a basis for?","back":"Testing and evaluation.","mcqOptions":[{"text":"Testing and evaluation.","correct":true,"explanation":"The specification states the required behaviour and performance, so completed software can be tested against it and evaluated for whether it meets its objectives."},{"text":"Recruitment and appraisal.","correct":false,"explanation":"Recruitment and staff appraisal are organisational activities, not purposes of a software specification. The specification provides measurable requirements for testing and evaluation."},{"text":"Versioning and backup.","correct":false,"explanation":"Version control and backup management protect development work but are not based on the specification. Its stated requirements provide the basis for testing and evaluation."},{"text":"Marketing and advertising.","correct":false,"explanation":"Marketing and product advertising may use general product information, but they are not the specification’s formal purpose. Its criteria underpin testing and evaluation."}]},{"id":"4450adcb-768f-471b-9ffd-1a31dbe969c7","cardType":"cloze","points":null,"front":"The [ ] says what real-world data matters; the [ ] says how it is represented in the program.","back":"The data model says what real-world data matters; the data structure says how it is represented in the program.","mcqOptions":[{"text":"The data model says what real-world data matters; the data structure says how it is represented in the program.","correct":true,"explanation":"The data model identifies relevant entities, attributes and relationships in the real world, while the data structure defines their concrete representation within software."},{"text":"The algorithm says what real-world data matters; the data structure says how it is represented in the program.","correct":false,"explanation":"An algorithm specifies processing steps, not which real-world data matters. The correct distinction is between the conceptual data model and its program-level data structure."},{"text":"The data model says what real-world data matters; the user interface says how it is represented in the program.","correct":false,"explanation":"A user interface controls interaction and presentation, not the internal representation of data. The data model identifies relevant data, while the data structure represents it in code."},{"text":"The test plan says what real-world data matters; the source code says how it is represented in the program.","correct":false,"explanation":"A test plan describes testing rather than relevant real-world data, and source code is broader than the specific representation. The correct terms are data model and data structure."}]},{"id":"32c6a7eb-31bc-464f-b8b3-398846fca08c","cardType":"basic","points":3,"front":"What should a module’s interface document?","back":"

Inputs
Outputs
Purpose

","mcqOptions":[{"text":"

Inputs
Outputs
Purpose

","correct":true,"explanation":"A module’s interface defines how other modules use it, so it must state the data accepted, the results produced and the module’s intended purpose."},{"text":"

Local variables
Internal algorithms
Debugging history

","correct":false,"explanation":"Local variables, internal algorithms and debugging history concern implementation rather than the public interface. The interface should document inputs, outputs and purpose."},{"text":"

Test results
Error logs
Revision dates

","correct":false,"explanation":"Test results, error logs and revision dates may appear in development records, but they do not define module use. An interface documents inputs, outputs and purpose."},{"text":"

Memory addresses
Compiler settings
Source formatting

","correct":false,"explanation":"Memory addresses, compiler settings and source formatting are low-level implementation details that callers should not need. The interface must document inputs, outputs and purpose."}]},{"id":"415fe0e3-20b5-4d27-9d53-023fd5fecaf6","cardType":"cloze","points":null,"front":"[ ] means finding and fixing errors in the [ ].","back":"Debugging means finding and fixing errors in the implementation.","mcqOptions":[{"text":"Debugging means finding and fixing errors in the implementation.","correct":true,"explanation":"Debugging is the process of locating, diagnosing and correcting faults in implemented program code so that its observed behaviour matches the intended behaviour."},{"text":"Testing means finding and fixing errors in the implementation.","correct":false,"explanation":"Testing can reveal failures but does not itself mean fixing them. Debugging is the activity that finds and corrects errors in the implementation."},{"text":"Debugging means finding and fixing errors in the requirements.","correct":false,"explanation":"Requirements may be reviewed and corrected, but debugging specifically concerns faults in implemented code. The correct terms are debugging and implementation."},{"text":"Evaluation means finding and fixing errors in the design.","correct":false,"explanation":"Evaluation judges whether a solution meets objectives; it is not the process of repairing a design. Debugging means finding and fixing errors in the implementation."}]},{"id":"ff9e5f8c-d2d1-4fdd-a593-d9df7265c733","cardType":"basic","points":2,"front":"In an iterative build, which features are on the critical path?","back":"Core dependent features needed before meaningful use or testing.","mcqOptions":[{"text":"Core dependent features needed before meaningful use or testing.","correct":true,"explanation":"Core dependent features form the critical path because later functionality, meaningful system use or effective testing cannot proceed until those features are complete."},{"text":"Optional cosmetic features added after meaningful use or testing.","correct":false,"explanation":"Independent cosmetic features can usually be postponed without blocking other work. The critical path contains core dependent features required before meaningful use or testing."},{"text":"Simple isolated features chosen for rapid coding or demonstration.","correct":false,"explanation":"Features chosen for quick implementation are not necessarily dependencies and therefore may not control the schedule. Core dependent features needed for use or testing form the critical path."},{"text":"Future enhancement features intended only for later software releases.","correct":false,"explanation":"Enhancements planned after release cannot block the current iterative build. The critical path instead contains core dependent features required before meaningful use or testing."}]},{"id":"c09ecb0d-d2f9-4a3b-bb00-ac5dc011703b","cardType":"basic","points":1,"front":"What must each test case include besides input data?","back":"An expected outcome.","mcqOptions":[{"text":"An expected outcome.","correct":true,"explanation":"An expected outcome states what the software should produce for the specified inputs, allowing the tester to compare predicted and actual behaviour objectively."},{"text":"An algorithm description.","correct":false,"explanation":"An algorithm description may help explain the solution but is not required in each test case. Every case needs an expected outcome for comparison with the actual result."},{"text":"An implementation deadline.","correct":false,"explanation":"A development deadline belongs to project planning rather than an individual test case. Each test case must state the expected outcome associated with its input data."},{"text":"An operator password.","correct":false,"explanation":"A programmer’s password is irrelevant to defining most tests and should not be exposed in test documentation. A test case requires an expected outcome."}]},{"id":"ade476de-710f-45bb-94f6-3b3d2cd08263","cardType":"basic","points":1,"front":"For a valid integer range $1 \\le q \\le 20$, what type of test data is 10?","back":"Normal data.","mcqOptions":[{"text":"Normal data.","correct":true,"explanation":"The value 10 lies within the valid range from 1 to 20 and is not at an endpoint, so it represents typical valid input and is classified as normal data."},{"text":"Boundary data","correct":false,"explanation":"Boundary data uses values at the limits of the valid range, such as 1 or 20. The value 10 is an ordinary valid value, so the correct classification is normal data."},{"text":"Erroneous data","correct":false,"explanation":"Erroneous data is invalid input, such as text or a number outside the permitted range. Since 10 is valid and internal to the range, it is normal data."},{"text":"Invalid data","correct":false,"explanation":"Invalid data fails the stated input conditions, whereas 10 satisfies 1 ≤ q ≤ 20. A valid non-boundary value like 10 is therefore classified as normal data."}]},{"id":"c7dbeb3c-3f06-44a7-8185-4593d0826266","cardType":"basic","points":1,"front":"For a valid integer range $1 \\le q \\le 20$, what type of test data are 1 and 20?","back":"Boundary data.","mcqOptions":[{"text":"Boundary data.","correct":true,"explanation":"The values 1 and 20 are exactly the lower and upper limits of the valid range, so they test its boundaries and are classified as boundary data."},{"text":"Normal data","correct":false,"explanation":"Normal data is a typical valid value away from the limits, such as 10. Values 1 and 20 test the endpoints of the range, so they are boundary data."},{"text":"Erroneous data","correct":false,"explanation":"Erroneous data is invalid, such as text or a value outside the range. Both 1 and 20 are valid endpoints, so the correct classification is boundary data."},{"text":"Extreme data","correct":false,"explanation":"Although the endpoints may feel extreme, the recognised testing category is boundary data. It specifically means valid values at the lower or upper limit of the permitted range."}]},{"id":"1e09336d-b0ad-43c9-9895-f7d4271a61ac","cardType":"basic","points":1,"front":"For a valid integer range $1 \\le q \\le 20$, what type of test data is ten or a blank entry?","back":"Erroneous data.","mcqOptions":[{"text":"Erroneous data.","correct":true,"explanation":"The text ten and a blank entry do not provide a valid integer for the required range, so they are invalid inputs classified as erroneous data."},{"text":"Normal data","correct":false,"explanation":"Normal data is a valid, typical integer within the permitted range. Text and blank input fail the requirement for an integer, so they are erroneous data."},{"text":"Boundary data","correct":false,"explanation":"Boundary data consists of valid values at the range limits, such as 1 and 20. Text and blank input are not valid endpoints, so they are erroneous data."},{"text":"Extreme data","correct":false,"explanation":"Extreme values are still numerical inputs, often near a limit. ten and a blank entry fail the input format entirely, making them erroneous data."}]},{"id":"26f4298e-c701-496a-ae6a-8eddf7199360","cardType":"basic","points":2,"front":"What does acceptance testing check with intended users?","back":"

Meets the specification
Works for real user needs

","mcqOptions":[{"text":"

Meets the specification
Works for real user needs

","correct":true,"explanation":"Acceptance testing is carried out with intended users to confirm both that the system satisfies its specification and that it supports the users’ genuine practical needs."},{"text":"

Passes all unit tests
Uses efficient algorithms

","correct":false,"explanation":"Unit tests and algorithm efficiency concern technical development checks rather than acceptance by intended users. Acceptance testing checks the specification and whether the system meets real user needs."},{"text":"

Compiles without errors
Uses the correct data types

","correct":false,"explanation":"Compilation and data types are implementation concerns normally checked during development. Intended users perform acceptance testing to judge specification compliance and usefulness for real needs."},{"text":"

Has well-structured code
Contains clear comments

","correct":false,"explanation":"Code structure and comments are internal quality considerations, not the main focus of acceptance testing. Intended users assess whether the system meets requirements and supports their needs."}]},{"id":"9f6786d3-d3eb-4b33-9b36-ac800555f908","cardType":"cloze","points":null,"front":"Testing can show that [ ], but it cannot prove a non-trivial system contains [ ].","back":"Testing can show that errors exist, but it cannot prove a non-trivial system contains no errors.","mcqOptions":[{"text":"Testing can show that errors exist, but it cannot prove a non-trivial system contains no errors.","correct":true,"explanation":"A failed test demonstrates that at least one error exists, but passing tests cover only tested cases. Therefore, testing cannot prove that a complex system has no remaining errors."},{"text":"Testing can show that no errors exist, but it cannot prove a non-trivial system contains errors exist.","correct":false,"explanation":"Passing tests cannot prove that no errors exist because untested inputs may still fail. Testing can demonstrate that errors exist, but not prove a non-trivial system contains none."},{"text":"Testing can show that requirements are met, but it cannot prove a non-trivial system contains no errors.","correct":false,"explanation":"Testing may provide evidence that particular requirements work, but the key guaranteed conclusion from a failed test is that errors exist. It still cannot prove a complex system has no errors."},{"text":"Testing can show that errors exist, but it cannot prove a non-trivial system contains all errors.","correct":false,"explanation":"Finding errors does not require finding every error, and the standard principle concerns proving the absence of errors. Testing can show errors exist, but cannot prove a non-trivial system contains no errors."}]},{"id":"2c168491-fa11-4a5e-b28d-a9ffcd72b2fc","cardType":"basic","points":1,"front":"Which evaluation criterion asks whether the system solves the original problem and meets requirements?","back":"Fitness for purpose.","mcqOptions":[{"text":"Fitness for purpose.","correct":true,"explanation":"Fitness for purpose evaluates whether the completed system solves the original problem and satisfies the requirements it was designed to meet."},{"text":"Robustness","correct":false,"explanation":"Robustness concerns coping with invalid, unexpected, or extreme input without failing. Judging whether the original problem and requirements have been addressed is fitness for purpose."},{"text":"Usability","correct":false,"explanation":"Usability considers how easily and effectively users can operate the system. The criterion concerned with solving the original problem and meeting requirements is fitness for purpose."},{"text":"Maintainability","correct":false,"explanation":"Maintainability measures how easily the system can be understood, corrected, or modified. Its success against the original problem and requirements is assessed through fitness for purpose."}]},{"id":"6114bbdb-25c3-42a4-80f5-20ead35e4256","cardType":"basic","points":1,"front":"Which evaluation criterion judges handling of invalid or unexpected input without failing?","back":"Robustness.","mcqOptions":[{"text":"Robustness.","correct":true,"explanation":"Robustness is the ability of a system to handle invalid, unexpected, or unusual input safely, without crashing or producing unacceptable behaviour."},{"text":"Fitness for purpose","correct":false,"explanation":"Fitness for purpose asks whether the system solves its intended problem and meets requirements. Handling invalid or unexpected input without failing is specifically a measure of robustness."},{"text":"Usability","correct":false,"explanation":"Usability focuses on how easily users can learn and operate the system. Its ability to cope with invalid or unexpected input without failing is assessed as robustness."},{"text":"Maintainability","correct":false,"explanation":"Maintainability concerns the ease of modifying, debugging, and extending software. Safe handling of invalid or unexpected input is a robustness criterion instead."}]},{"id":"fe89d59a-b23a-4065-8ef4-13cb75face2d","cardType":"basic","points":3,"front":"What evidence should strong evaluation use?","back":"

Requirements
Test results
User feedback

","mcqOptions":[{"text":"

Requirements
Test results
User feedback

","correct":true,"explanation":"Strong evaluation compares the system with its requirements, uses objective test results, and includes feedback from users to judge both technical performance and practical suitability."},{"text":"

Source code
Program comments
Variable names

","correct":false,"explanation":"These provide evidence about code quality, but they do not directly demonstrate that the system meets requirements or works for users. Strong evaluation uses requirements, test results, and user feedback."},{"text":"

Development costs
Chosen language
File size

","correct":false,"explanation":"Cost, programming language, and file size may be relevant project details, but they are insufficient evidence of success. Evaluation should be grounded in requirements, tests, and user feedback."},{"text":"

Design sketches
Developer opinions
Planned features

","correct":false,"explanation":"Design intentions and developer opinions are not reliable evidence of how the finished system performs. Strong evaluation examines requirements, actual test results, and feedback from intended users."}]}]}],"examCountdown":{"examDate":"2027-06-07","paperLabel":"Paper 1"},"heading":"Aspects of software development","title":"Aspects of software development Flashcards","topbar":{"backHref":"/a-level/computer-science/aqa/flashcards"},"topicSidebar":"$L37"}]}],"topicId":"dde4daac-2b64-5c2b-80b8-6c20f6efcad5","walled":"$L38"}],"$L39","$L3a"]