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of steps. A sequence that can continue indefinitely does not satisfy the standard definition of an algorithm."},{"text":"may run indefinitely","correct":false,"explanation":"This confuses an algorithm with a non-terminating process. An algorithm always terminates, meaning it completes after a finite number of steps."},{"text":"always gives the correct result","correct":false,"explanation":"An algorithm can be logically flawed and produce an incorrect result while still terminating. The defining requirement here is that it always terminates."},{"text":"must be written in code","correct":false,"explanation":"This confuses an algorithm with its implementation as a program. An algorithm may be expressed in pseudocode or diagrams, but it must always terminate."}]},{"id":"05abf4df-c5de-420a-8814-71af0a22facd","cardType":"basic","points":2,"front":"List the four standard constructs used to build algorithms.","back":"

Sequence
Assignment
Selection
Iteration

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

Sequence
Assignment
Selection
Iteration

","correct":true,"explanation":"Algorithms are constructed using sequence to order instructions, assignment to store values, selection to choose paths, and iteration to repeat instructions."},{"text":"

Sequence
Assignment
Selection
Recursion

","correct":false,"explanation":"Recursion is a programming technique rather than one of the four standard constructs. Iteration is the missing construct, alongside sequence, assignment and selection."},{"text":"

Sequence
Input
Selection
Iteration

","correct":false,"explanation":"Input is an operation an algorithm may perform, not one of the four standard constructs. Assignment is required alongside sequence, selection and iteration."},{"text":"

Sequence
Assignment
Compilation
Iteration

","correct":false,"explanation":"Compilation translates source code and is not an algorithmic construct. Selection is the missing construct, completing sequence, assignment, selection and iteration."}]},{"id":"0f2b38b0-66bc-40c3-8f0c-fda214ececa8","cardType":"basic","points":2,"front":"What is the fundamental difference between an algorithm and a program?","back":"An algorithm is the general method; a program is the implementation in a specific language.","mcqOptions":[{"text":"An algorithm is the general method; a program is the implementation in a specific language.","correct":true,"explanation":"An algorithm describes a language-independent method for solving a problem, while a program expresses and implements that method using a particular programming language."},{"text":"An algorithm is the specific implementation; a program is the general method independent of language.","correct":false,"explanation":"This reverses the two concepts. The algorithm is the general, language-independent method, while the program is its implementation in a specific language."},{"text":"An algorithm is the executable file; a program is the pseudocode used to design it.","correct":false,"explanation":"This confuses development representations and compiled output. An algorithm is the general method, while a program implements that method in a particular language."},{"text":"An algorithm stores the input data; a program describes the method used to process it.","correct":false,"explanation":"An algorithm does not store input data; it specifies a general method. A program is the language-specific implementation that carries out that method."}]},{"id":"cace4a5f-39a4-474a-be24-cadd0392749c","cardType":"basic","points":2,"front":"Why is a train map considered a representational abstraction?","back":"It removes unnecessary details (exact distance/curves) to keep essential features (stations/connections).","mcqOptions":[{"text":"It removes unnecessary details (exact distance/curves) to keep essential features (stations/connections).","correct":true,"explanation":"A train map simplifies geographical shape and scale because passengers mainly need to know which stations exist and how the routes connect."},{"text":"It removes essential features (stations/connections) to keep unnecessary details (exact distance/curves).","correct":false,"explanation":"This reverses the purpose of abstraction. A useful train map retains stations and connections while removing unnecessary geographical details such as exact distances and curves."},{"text":"It preserves exact geography (distance/curves) to show realistic routes (shape/scale).","correct":false,"explanation":"Preserving exact geography would reduce simplification rather than create representational abstraction. Train maps remove exact distances and curves while retaining stations and connections."},{"text":"It removes all spatial information (position/direction) to keep only station names (labels/text).","correct":false,"explanation":"Train maps still retain useful spatial and relational information, particularly route connections. They remove unnecessary exact geography, not every detail except station names."}]},{"id":"8800d50a-c555-4907-8381-126d01d756c1","cardType":"cloze","points":null,"front":"Abstraction by [ ] (or categorisation) involves grouping things into an is a kind of hierarchy.","back":"Abstraction by generalisation (or categorisation) involves grouping things into an is a kind of hierarchy.","mcqOptions":[{"text":"generalisation","correct":true,"explanation":"Generalisation groups entities according to shared characteristics and arranges them into categories, producing an “is a kind of” hierarchy from specific to general types."},{"text":"decomposition","correct":false,"explanation":"Decomposition breaks a complex problem or system into smaller parts rather than grouping related entities. Generalisation creates an “is a kind of” hierarchy."},{"text":"information hiding","correct":false,"explanation":"Information hiding conceals implementation details behind an interface rather than categorising entities. Generalisation is the abstraction that groups things into an “is a kind of” hierarchy."},{"text":"representation","correct":false,"explanation":"Representational abstraction removes unnecessary detail from how something is modelled. Generalisation instead groups things by shared characteristics into an “is a kind of” hierarchy."}]},{"id":"4dcc0c8e-e210-49d9-8d89-95023e34095f","cardType":"cloze","points":null,"front":"Abstraction by generalisation (or categorisation) involves grouping things into an [ ] hierarchy.","back":"Abstraction by generalisation (or categorisation) involves grouping things into an is a kind of hierarchy.","mcqOptions":[{"text":"is a kind of","correct":true,"explanation":"Generalisation organises more specific entities beneath broader categories, so each subclass or specialised type “is a kind of” its parent type."},{"text":"is part of","correct":false,"explanation":"“Is part of” describes aggregation or composition, where one entity forms a component of another. Generalisation uses an “is a kind of” relationship."},{"text":"has a","correct":false,"explanation":"“Has a” describes an association or composition between entities, not categorisation. A generalisation hierarchy links specific and general types using “is a kind of”."},{"text":"is an instance of","correct":false,"explanation":"“Is an instance of” relates an individual object to its class. Generalisation instead relates one type to a broader type through “is a kind of”."}]},{"id":"24b1cd8e-ae11-4f22-aceb-4a9ed430d448","cardType":"basic","points":2,"front":"How does information hiding benefit a programmer using an object?","back":"It allows the internal implementation to change without affecting how the object is used.","mcqOptions":[{"text":"It allows the internal implementation to change without affecting how the object is used.","correct":true,"explanation":"Users interact with the object through its public interface, so hidden internal code or data structures can change without requiring changes to calling code."},{"text":"It allows the public interface to change without affecting how the object is used.","correct":false,"explanation":"Changing the public interface can break code that uses the object. Information hiding protects users from changes to the internal implementation, not the interface."},{"text":"It allows the internal data to be accessed directly without using the object’s methods.","correct":false,"explanation":"Direct access to internal data contradicts information hiding and can create unwanted dependencies. Access is controlled through an interface so implementation details may change safely."},{"text":"It requires the internal implementation to remain identical whenever the object is used.","correct":false,"explanation":"Information hiding provides flexibility rather than preventing change. The internal implementation may change because users depend only on the object’s stable public interface."}]},{"id":"fd7754fa-b78a-41df-998c-ae8ca355f080","cardType":"cloze","points":null,"front":"Procedural abstraction represents a computational method as a [ ] to hide the particular values used in any one computation.","back":"Procedural abstraction represents a computational method as a named procedure to hide the particular values used in any one computation.","mcqOptions":[{"text":"named procedure","correct":true,"explanation":"A named procedure captures the general computational method and accepts different values through parameters, hiding the details of any one particular computation."},{"text":"named variable","correct":false,"explanation":"A named variable represents stored data rather than a computational method. Procedural abstraction packages the method as a named procedure that can operate on different values."},{"text":"global constant","correct":false,"explanation":"A global constant stores one fixed value and does not represent reusable computation. Procedural abstraction uses a named procedure to apply a method to varying values."},{"text":"specific expression","correct":false,"explanation":"A specific expression represents one calculation rather than abstracting a reusable method. Procedural abstraction gives the general computational method a named procedure."}]},{"id":"39edc324-44e1-4d20-bf28-91331a180a92","cardType":"cloze","points":null,"front":"Procedural abstraction represents a computational method as a named procedure to hide the particular [ ] used in any one computation.","back":"Procedural abstraction represents a computational method as a named procedure to hide the particular values used in any one computation.","mcqOptions":[{"text":"values","correct":true,"explanation":"Parameters allow a named procedure to operate with different values, hiding the particular data used in each computation while preserving the same general computational method."},{"text":"operations","correct":false,"explanation":"Operations form part of the computational method rather than the specific details hidden between individual computations. Procedural abstraction hides the particular values by passing them as parameters."},{"text":"algorithms","correct":false,"explanation":"An algorithm describes the general computational method, which the procedure represents rather than hides. The particular values used in each computation are hidden through parameterisation."},{"text":"instructions","correct":false,"explanation":"Instructions define the procedure’s method and remain part of its implementation. Procedural abstraction instead hides the particular values supplied during any one computation."}]},{"id":"c34ab16e-aa3d-4d27-82ea-76b7d545051c","cardType":"basic","points":2,"front":"What is the primary focus of functional abstraction?","back":"The relationship between inputs and outputs, disregarding the specific method used.","mcqOptions":[{"text":"The relationship between inputs and outputs, disregarding the specific method used.","correct":true,"explanation":"Functional abstraction describes what result is produced for given inputs without exposing the implementation details of how the function calculates that result."},{"text":"The relationship between data and storage, disregarding the specific structure used.","correct":false,"explanation":"Separating data use from its internal storage structure describes data abstraction. Functional abstraction focuses on the relationship between inputs and outputs while disregarding the method used."},{"text":"The relationship between procedures and parameters, disregarding the specific values used.","correct":false,"explanation":"Hiding the particular values supplied to a named procedure describes procedural abstraction. Functional abstraction instead considers the relationship between inputs and outputs, independent of the method."},{"text":"The relationship between problems and models, disregarding the specific details used.","correct":false,"explanation":"Removing unnecessary details to create a model describes general abstraction. Functional abstraction specifically focuses on how inputs relate to outputs while ignoring the method used."}]},{"id":"4c929b25-3c71-4b4d-b0e8-fe0d1313ecd9","cardType":"basic","points":2,"front":"How does data abstraction treat a complex data object like a stack?","back":"It separates how data is used (operations) from how it is constructed (internal array/pointers).","mcqOptions":[{"text":"It separates how data is used (operations) from how it is constructed (internal array/pointers).","correct":true,"explanation":"Data abstraction exposes permitted operations, such as push and pop, while concealing whether the stack is internally implemented using an array, pointers or another structure."},{"text":"It separates how data is entered (inputs) from how it is displayed (screen formatting).","correct":false,"explanation":"Input and display concerns do not define data abstraction. A stack abstraction separates how data is used through operations from how it is constructed internally."},{"text":"It separates how data is processed (algorithm) from how it is compiled (machine instructions).","correct":false,"explanation":"The distinction between algorithms and compiled instructions concerns levels of program representation. Data abstraction separates available operations from the internal array or pointer construction."},{"text":"It separates how data is stored (memory) from how it is transmitted (network packets).","correct":false,"explanation":"Storage and transmission are implementation concerns but not the defining separation for an abstract data type. Data abstraction separates operations from the object’s internal construction."}]},{"id":"174d8eab-9209-43fe-a449-3f4f70b24145","cardType":"basic","points":1,"front":"In the context of abstraction, what is problem reduction?","back":"Generalising a problem into a form that has already been solved (e.g., reducing a map to a graph).","mcqOptions":[{"text":"Generalising a problem into a form that has already been solved (e.g., reducing a map to a graph).","correct":true,"explanation":"Problem reduction converts a new problem into an established form with a known solution, allowing existing algorithms and techniques to be applied to it."},{"text":"Dividing a problem into sections that can be solved independently (e.g., splitting a program into procedures).","correct":false,"explanation":"Dividing a problem into smaller independent sections is decomposition. Problem reduction instead generalises it into a previously solved form, such as representing a map as a graph."},{"text":"Removing all details from a problem until it can be solved without data (e.g., replacing values with blanks).","correct":false,"explanation":"Abstraction removes irrelevant details, but it does not eliminate required data. Problem reduction transforms the problem into a form that has already been solved."},{"text":"Rewriting a problem so that it can be executed more quickly (e.g., replacing a loop with recursion).","correct":false,"explanation":"Changing code to improve execution speed is optimisation, and recursion may not be faster. Problem reduction generalises a problem into an already solved form."}]},{"id":"3e44f808-8fee-4fde-a9c8-f42282a2d951","cardType":"basic","points":2,"front":"State two benefits of using procedural decomposition.","back":"

Makes problems easier to test and debug
Allows sub-problems to be subdivided further for simplicity

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

Makes problems easier to test and debug
Allows sub-problems to be subdivided further for simplicity

","correct":true,"explanation":"Procedural decomposition creates manageable modules that can be tested and debugged separately. Any module that remains too complex can also be decomposed into smaller sub-problems."},{"text":"

Makes programs unnecessary to test and debug
Allows all sub-problems to be combined immediately for simplicity

","correct":false,"explanation":"Decomposition does not remove the need for testing, nor does it immediately recombine every task. It makes testing easier and allows sub-problems to be subdivided further."},{"text":"

Makes processors able to execute code faster
Allows source code to be compiled automatically for simplicity

","correct":false,"explanation":"Decomposition improves program organisation rather than guaranteeing faster execution or automatic compilation. Its benefits include easier testing and debugging and further subdivision of complex tasks."},{"text":"

Makes data easier to encrypt and compress
Allows variables to be stored permanently for simplicity

","correct":false,"explanation":"Encryption, compression and permanent storage are unrelated to procedural decomposition. Decomposition supports easier testing and debugging and permits sub-problems to be divided again."}]},{"id":"013f0863-1b9e-41a2-a82a-a607a96d67dd","cardType":"cloze","points":null,"front":"The process of combining smaller abstractions to build larger, more complex ones is known as [ ].","back":"The process of combining smaller abstractions to build larger, more complex ones is known as composition.","mcqOptions":[{"text":"composition","correct":true,"explanation":"Composition builds increasingly complex systems by combining smaller abstractions, allowing existing components to be reused as parts of a larger abstraction."},{"text":"decomposition","correct":false,"explanation":"Decomposition works in the opposite direction by breaking a complex problem into smaller sub-problems. Combining smaller abstractions to construct a larger one is composition."},{"text":"iteration","correct":false,"explanation":"Iteration repeatedly executes instructions or processes elements; it does not describe joining abstractions. Combining smaller abstractions into a larger abstraction is composition."},{"text":"encapsulation","correct":false,"explanation":"Encapsulation groups data with operations and restricts access to internal details. The process of combining smaller abstractions to build larger ones is composition."}]},{"id":"140e0b9b-205d-4ec6-9996-b1075d81ad70","cardType":"basic","points":3,"front":"What four elements are required to achieve automation?","back":"

Abstract models (data structures)
Algorithms
Program code
Execution

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

Abstract models (data structures)
Algorithms
Program code
Execution

","correct":true,"explanation":"Automation requires a model of the problem, an algorithmic solution, executable program code implementing that solution, and execution by a computer system."},{"text":"

Abstract interfaces (user screens)
Flowcharts
Test data
Documentation

","correct":false,"explanation":"Interfaces, flowcharts, test data and documentation may support development, but they do not complete automation. Automation requires abstract models, algorithms, program code and execution."},{"text":"

Abstract variables (named values)
Compilers
Machine hardware
Maintenance

","correct":false,"explanation":"Variables, compilers and hardware may be involved in implementation, while maintenance follows development. The four conceptual elements are models, algorithms, code and execution."},{"text":"

Abstract problems (user requirements)
Procedures
Source files
Testing

","correct":false,"explanation":"Requirements, procedures, files and testing are development artefacts or activities rather than the complete automation chain. The required elements are models, algorithms, code and execution."}]},{"id":"e1dee0c7-58c5-4996-85f5-9f6ec24da55a","cardType":"basic","points":2,"front":"What is the core argument for the correctness of a maximum-finding algorithm?","back":"The variable always stores the largest value seen so far, which eventually covers the entire list.","mcqOptions":[{"text":"The variable always stores the largest value seen so far, which eventually covers the entire list.","correct":true,"explanation":"This loop invariant holds after every comparison: the stored value is the maximum among all processed items. Once every item is processed, it is the list maximum."},{"text":"The variable always stores the first value in the list, which eventually moves to the final position.","correct":false,"explanation":"Initialising with the first value does not mean it remains unchanged or moves position. The variable must store the largest value seen so far throughout processing."},{"text":"The variable always stores the most recently checked value, which eventually becomes the largest value.","correct":false,"explanation":"Simply storing the latest item gives no guarantee that it is the largest. The algorithm’s correctness depends on retaining the largest value seen so far."},{"text":"The variable always stores the smallest value seen so far, which eventually covers the entire list.","correct":false,"explanation":"Tracking the smallest value proves a minimum-finding algorithm, not a maximum-finding one. For the maximum, the variable must retain the largest value seen so far."}]},{"id":"cb798626-8284-4951-9466-c95ba4f2a217","cardType":"basic","points":2,"front":"What are the time and space complexities of a standard linear search for a maximum value?","back":"

Time: $O(n)$
Space: $O(1)$

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

Time: $O(n)$
Space: $O(1)$

","correct":true,"explanation":"Every element must be examined to guarantee finding the maximum, so time grows linearly with $n$. Only the current maximum is stored, giving constant auxiliary space."},{"text":"

Time: $O(n^2)$
Space: $O(1)$

","correct":false,"explanation":"Quadratic time would imply repeated comparisons between many pairs of elements. A linear search makes one pass through the data, so its complexities are $O(n)$ time and $O(1)$ space."},{"text":"

Time: $O(\\log n)$
Space: $O(1)$

","correct":false,"explanation":"Logarithmic time is associated with repeatedly halving an ordered search space. Finding an arbitrary maximum requires examining every element, giving $O(n)$ time and $O(1)$ space."},{"text":"

Time: $O(n)$
Space: $O(n)$

","correct":false,"explanation":"Linear space would be needed if all elements were copied or stored separately. A standard maximum search retains only one current maximum, so space is $O(1)$ while time is $O(n)$."}]},{"id":"ca19148f-3ab8-41fb-ad1f-d14c2c6a1253","cardType":"cloze","points":null,"front":"When solving logic problems, removing [ ] is a key step before reasoning step-by-step.","back":"When solving logic problems, removing irrelevant details is a key step before reasoning step-by-step.","mcqOptions":[{"text":"irrelevant details","correct":true,"explanation":"Removing information that does not affect the outcome is an application of abstraction. It reduces complexity and allows the relevant facts and constraints to be considered systematically."},{"text":"essential constraints","correct":false,"explanation":"Removing essential constraints discards rules needed to solve and verify the problem. Abstraction instead removes irrelevant details so reasoning can focus on the information that affects the solution."},{"text":"possible solutions","correct":false,"explanation":"Possible solutions must be considered and tested rather than removed before reasoning begins. The key abstraction step is removing irrelevant details that do not influence the valid outcome."},{"text":"logical operators","correct":false,"explanation":"Logical operators express relationships required for reasoning, so removing them would damage the problem’s structure. Irrelevant details should be removed because they do not affect the solution."}]},{"id":"e39e5125-0d3f-486b-87f6-d273aa427a80","cardType":"basic","points":1,"front":"Why is it necessary to check a logic problem solution against every constraint?","back":"To ensure the solution is valid and satisfies all rules, rather than just being plausible.","mcqOptions":[{"text":"To ensure the solution is valid and satisfies all rules, rather than just being plausible.","correct":true,"explanation":"A candidate can appear reasonable while violating one overlooked condition. Checking it against every constraint confirms that it is genuinely valid and complies with all the problem’s rules."},{"text":"To ensure the solution is efficient and uses few steps, rather than just being plausible.","correct":false,"explanation":"Efficiency concerns the resources used to find a solution, not whether the result obeys the problem. Every constraint must be checked to ensure the solution is valid and satisfies all rules."},{"text":"To ensure the solution is unique and matches one rule, rather than just being plausible.","correct":false,"explanation":"Checking one rule cannot establish validity, and a problem may legitimately have multiple solutions. The candidate must be tested against every constraint to show that it satisfies all rules."},{"text":"To ensure the solution is simple and contains no variables, rather than just being plausible.","correct":false,"explanation":"Simplicity and the absence of variables do not determine whether a logical solution is acceptable. Validity comes from checking that the candidate satisfies every stated rule or constraint."}]},{"id":"4325ef55-e663-442e-9b93-67e4b971f626","cardType":"basic","points":3,"front":"Contrast procedural abstraction and functional abstraction.","back":"Procedural hides specific values used in a method; functional hides the method itself to focus on input-output behavior.","mcqOptions":[{"text":"Procedural hides specific values used in a method; functional hides the method itself to focus on input-output behavior.","correct":true,"explanation":"Procedural abstraction generalises a method by concealing particular values, while functional abstraction treats the operation as a black box whose inputs and outputs matter more than its internal method."},{"text":"Procedural hides the method itself to focus on input-output behavior; functional hides specific values used in a method.","correct":false,"explanation":"This reverses the two forms of abstraction. Procedural abstraction hides specific values used by a method, whereas functional abstraction conceals the method and presents its input-output behavior."},{"text":"Procedural hides input-output behavior in a method; functional exposes the method itself to show every processing step.","correct":false,"explanation":"Functional abstraction does not expose every processing step; it hides them behind an input-output interface. Procedural abstraction hides specific values used by a generalised method."},{"text":"Procedural hides the data types used in a method; functional hides the inputs and outputs of the method.","correct":false,"explanation":"Hiding data representation belongs to data abstraction, and functional abstraction retains the visible input-output relationship. Procedural abstraction hides specific values, while functional abstraction hides the internal method."}]},{"id":"f7710f6a-4267-4a0a-9387-1ccf8f763688","cardType":"basic","points":1,"front":"What is recorded in a trace table during hand-tracing?","back":"How variable values change as each instruction is manually followed.","mcqOptions":[{"text":"How variable values change as each instruction is manually followed.","correct":true,"explanation":"A trace table records variable values at successive points while an algorithm is executed by hand. This makes changes caused by each instruction visible and helps identify logic errors."},{"text":"How source code changes as each instruction is manually followed.","correct":false,"explanation":"Hand-tracing does not rewrite or alter the source code. A trace table records how variable values change as the existing instructions are followed in execution order."},{"text":"How processor speed changes as each instruction is manually followed.","correct":false,"explanation":"A trace table models the state of an algorithm, not hardware performance. It records changing variable values as each instruction is manually executed."},{"text":"How all possible outputs change as each instruction is manually followed.","correct":false,"explanation":"A single trace follows one chosen set of inputs rather than generating every possible output. It records how variable values change throughout that particular execution."}]},{"id":"b01a0451-5768-4f6e-8cf2-052bb05d9eff","cardType":"cloze","points":null,"front":"Data abstraction allows new data objects to be built from [ ] while hiding the representation details.","back":"Data abstraction allows new data objects to be built from existing types while hiding the representation details.","mcqOptions":[{"text":"existing types","correct":true,"explanation":"Data abstraction combines or uses existing types to define new data objects. Users interact with the object through its permitted operations without needing to know its internal representation."},{"text":"control structures","correct":false,"explanation":"Control structures determine execution order but are not the types from which abstract data objects are constructed. Data abstraction builds new objects from existing types while concealing their representation."},{"text":"processor instructions","correct":false,"explanation":"Processor instructions implement low-level computation rather than serving as components of abstract data objects. Such objects are built from existing types, with representation details hidden."},{"text":"output devices","correct":false,"explanation":"Output devices are hardware components and do not provide the type structure for constructing abstract data objects. New objects are built from existing types while their representation remains hidden."}]},{"id":"208d6550-296b-479a-9d89-94419024a7d8","cardType":"cloze","points":null,"front":"Data abstraction allows new data objects to be built from existing types while hiding the [ ] details.","back":"Data abstraction allows new data objects to be built from existing types while hiding the representation details.","mcqOptions":[{"text":"representation","correct":true,"explanation":"Data abstraction presents a usable interface while concealing how the data is stored or organised internally. These hidden representation details can change without affecting code that uses the abstraction correctly."},{"text":"validation","correct":false,"explanation":"Validation checks whether data meets specified rules; it is not the information concealed by data abstraction. Data abstraction hides representation details while exposing suitable operations."},{"text":"processing","correct":false,"explanation":"Processing describes operations performed on data, many of which form the abstraction’s visible interface. The hidden details concern the internal representation of the data object."},{"text":"communication","correct":false,"explanation":"Communication concerns transferring information between components or systems, not the internal structure concealed by data abstraction. The abstraction specifically hides representation details."}]}]}],"examCountdown":{"examDate":"2027-06-07","paperLabel":"Paper 1"},"heading":"Abstraction and automation","title":"Abstraction and automation Flashcards","topbar":{"backHref":"/a-level/computer-science/aqa/flashcards"},"topicSidebar":"$L38"}]}],"topicId":"d3b8e7c3-d8cc-5631-a3a9-6ae438295104","walled":"$L39"}],"$L3a","$L3b"]