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its instructions are arranged in a sequence so that they solve a problem or complete a task."},{"text":"A program is a set of instructions for solving a problem or completing a task.","correct":false,"explanation":"A program is an implementation of instructions, not the general problem-solving procedure itself. The correct terms describe an algorithm and its ordered method."},{"text":"A variable is a named data value for solving a problem or completing a task.","correct":false,"explanation":"A variable stores data and cannot itself describe a complete solution procedure. The correct answer identifies the ordered method used to solve the problem."},{"text":"A flowchart is a diagram of symbols for solving a problem or completing a task.","correct":false,"explanation":"A flowchart represents a procedure visually, but it is not the general term for the procedure itself. The correct answer refers to the stepwise method."}]},{"id":"442d7a41-472f-4a04-a0a7-53bd7d229404","cardType":"basic","points":2,"front":"Why can two correct algorithms have different efficiency?","back":"One may do less work to get the result.","mcqOptions":[{"text":"One may do less work to get the result.","correct":true,"explanation":"Efficiency depends on the resources needed to obtain the result. If one correct method performs fewer operations, it generally takes less time or uses fewer resources."},{"text":"One may be easier to understand to get the result.","correct":false,"explanation":"Being easier to understand concerns readability, not efficiency. Two methods can be equally clear while differing in the amount of work required."},{"text":"One may have a different name to get the result.","correct":false,"explanation":"A different name does not change the operations performed or the resources used. Efficiency differs when the algorithms require different amounts of work."},{"text":"One may use a different input to get the result.","correct":false,"explanation":"The input value is supplied to both algorithms and does not by itself explain their different efficiency. The important difference is the work each method performs."}]},{"id":"fadd279d-dd3b-43fd-bd3d-6ebe8b4fde7a","cardType":"basic","points":1,"front":"What question about an algorithm is asked after “does it work”?","back":"How quickly it works.","mcqOptions":[{"text":"How quickly it works.","correct":true,"explanation":"After establishing that an algorithm produces the correct result, its efficiency can be assessed by considering the time it takes to complete."},{"text":"How much memory it uses.","correct":false,"explanation":"Memory use is a separate efficiency consideration, but the standard follow-up to whether an algorithm works asks about its speed or running time."},{"text":"What data type it uses.","correct":false,"explanation":"The data type describes the kind of data processed, not how efficiently the algorithm performs. The relevant question concerns the time needed to work."},{"text":"Where it stores data.","correct":false,"explanation":"Storage location is an implementation detail and does not directly answer the efficiency question. The intended consideration is how rapidly the algorithm completes."}]},{"id":"1d9535d5-4182-4e7a-a087-6f7901fd5c8b","cardType":"cloze","points":null,"front":"A linear search checks items [ ] from the [ ] of a list.","back":"A linear search checks items one by one from the start of a list.","mcqOptions":[{"text":"A linear search checks items one by one from the start of a list.","correct":true,"explanation":"A linear search examines entries sequentially, beginning with the first item and continuing until the target is found or the list ends."},{"text":"A linear search checks items many at once from the start of a list.","correct":false,"explanation":"Checking several entries simultaneously describes a parallel approach, not a standard linear search. Linear search examines each relevant item individually from the beginning."},{"text":"A linear search checks items one by one from the end of a list.","correct":false,"explanation":"Linear search does not normally begin at the final item. It starts at the beginning and checks entries sequentially, one at a time."},{"text":"A linear search checks items one by one from the middle of a list.","correct":false,"explanation":"Starting in the middle is characteristic of binary search. Linear search begins at the start and checks items sequentially rather than choosing a midpoint."}]},{"id":"3551ee3a-05bd-4cc6-a931-c424fe95af9e","cardType":"cloze","points":null,"front":"A binary search works on a [ ] list by checking the [ ].","back":"A binary search works on a sorted list by checking the middle value.","mcqOptions":[{"text":"A binary search works on a sorted list by checking the middle value.","correct":true,"explanation":"Binary search relies on sorted order. It checks the middle value, then discards the half that cannot contain the target and repeats the process."},{"text":"A binary search works on an unsorted list by checking the middle value.","correct":false,"explanation":"Without sorted order, discarding half the list could remove the target. Binary search therefore requires a sorted list before checking its middle value."},{"text":"A binary search works on a sorted list by checking the first value.","correct":false,"explanation":"Checking the first value is the starting behaviour of a linear search. Binary search instead uses the sorted list’s middle value to eliminate half the possibilities."},{"text":"A binary search works on a reversed list by checking the largest value.","correct":false,"explanation":"A reversed list is not in the required ascending or descending order for the usual method. Binary search needs sorted order and begins with the middle value."}]},{"id":"1e7d1bdc-d466-486f-b249-c60c7cbd7f23","cardType":"basic","points":1,"front":"What condition lets binary search safely discard half the list?","back":"The list is sorted.","mcqOptions":[{"text":"The list is sorted.","correct":true,"explanation":"Sorted order tells binary search which half may still contain the target. It can then discard the other half without risking the correct answer."},{"text":"The list is unsorted.","correct":false,"explanation":"An unsorted list provides no reliable ordering information, so discarding half could remove the target. Binary search requires the list to be sorted."},{"text":"The target is at the start.","correct":false,"explanation":"The target’s position is not known in advance, so being at the start is not the condition that justifies discarding half the list."},{"text":"The list has an even number of items.","correct":false,"explanation":"The number of items does not provide ordering information. Binary search may work with either an even or odd list length, provided the list is sorted."}]},{"id":"1b4c8194-4023-4508-8414-f19307959e07","cardType":"basic","points":1,"front":"In a search algorithm, what operation is useful to count for efficiency?","back":"Comparisons.","mcqOptions":[{"text":"Comparisons.","correct":true,"explanation":"A comparison checks a searched value against the target or another value. Counting these operations gives a useful, machine-independent measure of search efficiency."},{"text":"Assignments.","correct":false,"explanation":"Assignments show when values are stored or changed, but they are not the key operation used to judge how many search decisions are made."},{"text":"Iterations.","correct":false,"explanation":"Iterations count repetitions, which can sometimes help analyse efficiency, but search algorithms are conventionally compared by counting their value comparisons."},{"text":"Memory locations.","correct":false,"explanation":"Memory locations describe where data is stored rather than how many checks the search performs. Comparisons provide the relevant operation count."}]},{"id":"b5dbd5b0-4186-4fe7-ab15-bbf0d7eb84eb","cardType":"cloze","points":null,"front":"For time efficiency, compare [ ] rather than real [ ].","back":"For time efficiency, compare work done rather than real seconds.","mcqOptions":[{"text":"For time efficiency, compare work done rather than real seconds.","correct":true,"explanation":"Real elapsed seconds vary with hardware, workload and implementation. Counting the work performed provides a fairer comparison of an algorithm’s time efficiency."},{"text":"For time efficiency, compare memory used rather than real seconds.","correct":false,"explanation":"Memory used measures space efficiency, not time efficiency. The appropriate comparison counts the work performed rather than relying on measured elapsed seconds."},{"text":"For time efficiency, compare lines of code rather than real seconds.","correct":false,"explanation":"Lines of code do not reliably represent execution work because one line may perform many operations or none repeatedly. Counting work is the better measure."},{"text":"For time efficiency, compare input values rather than real seconds.","correct":false,"explanation":"Input values identify particular data, not the amount of processing required. Time efficiency is compared using algorithmic work rather than measured seconds."}]},{"id":"8007a664-0fe3-4be2-9d9a-acfaa6ed7194","cardType":"basic","points":2,"front":"Why are real seconds a poor way to compare algorithms?","back":"They depend on computer, language or hardware.","mcqOptions":[{"text":"They depend on computer, language or hardware.","correct":true,"explanation":"Elapsed time depends on the computer’s processor, the programming language and the hardware, so it does not measure the algorithm alone reliably."},{"text":"They depend on algorithm, input or output.","correct":false,"explanation":"Counting instructions is not the standard reason for avoiding real seconds; timing varies with the system used. Computer-independent efficiency instead considers input size and operation growth."},{"text":"They depend on output, memory or storage.","correct":false,"explanation":"The number of results does not normally determine measured seconds, while different computers and languages can produce different timings for the same algorithm."},{"text":"They depend on name, purpose or result.","correct":false,"explanation":"Real seconds are not made unreliable by the algorithm’s name or purpose. The important variation comes from the computer, language and hardware running it."}]},{"id":"b236c785-8ca8-4e12-a8b1-48e63ec15fe0","cardType":"basic","points":1,"front":"Linear search for 19 in 14, 3, 27, 8, 19 takes how many comparisons?","back":"5 comparisons.","mcqOptions":[{"text":"5 comparisons.","correct":true,"explanation":"The target 19 is the fifth item, so linear search compares it with 14, 3, 27, 8 and finally 19: five comparisons."},{"text":"4 comparisons.","correct":false,"explanation":"Four comparisons only reach the value 8. Because 19 is the fifth item, the search needs one further comparison to find it."},{"text":"6 comparisons.","correct":false,"explanation":"Six comparisons would require another item after the target. Linear search stops immediately when the fifth comparison finds 19."},{"text":"3 comparisons.","correct":false,"explanation":"Three comparisons stop at 27, which is not the target. The search must continue through 8 before comparing with 19 in position five."}]},{"id":"ccfaad90-a7b3-4682-8a57-45966047f673","cardType":"cloze","points":null,"front":"Input size is the amount of [ ] given to an algorithm, such as the number of [ ].","back":"Input size is the amount of data given to an algorithm, such as the number of list items.","mcqOptions":[{"text":"Input size is the amount of data given to an algorithm, such as the number of list items.","correct":true,"explanation":"Input size describes how much data the algorithm receives. For a list, a useful measure is the number of list items, because this affects the work required."},{"text":"Input size is the amount of program code given to an algorithm, such as the number of list items.","correct":false,"explanation":"The algorithm’s instructions are its code, not its input. Input size measures supplied data, such as the number of list items being processed."},{"text":"Input size is the amount of data given to an algorithm, such as the number of variables.","correct":false,"explanation":"Variables are storage locations used during execution, rather than the input itself. Input size concerns supplied data, commonly counted as list items."},{"text":"Input size is the amount of memory given to an algorithm, such as the number of list items.","correct":false,"explanation":"Memory is a resource used by a program, not the data supplied as input. For a list, input size is measured by counting its items."}]},{"id":"de898def-c43b-49c2-aad5-82b862440ffc","cardType":"basic","points":2,"front":"If a linear-search list doubles in size, what happens to possible checks?","back":"They roughly double.","mcqOptions":[{"text":"They roughly double.","correct":true,"explanation":"Linear search may inspect items one at a time, so doubling the number of items approximately doubles the maximum number of checks."},{"text":"They stay the same.","correct":false,"explanation":"The number of possible checks depends on the list length, so it does not stay fixed when the list doubles in size."},{"text":"They roughly quadruple.","correct":false,"explanation":"Quadrupling the checks confuses linear growth with a quadratic relationship. Linear search grows in proportion to the number of items."},{"text":"They roughly halve.","correct":false,"explanation":"A larger list cannot generally require fewer checks in a linear search. Doubling its size increases, rather than halves, the possible work."}]},{"id":"34326282-905a-410a-af00-69a0a707630e","cardType":"basic","points":2,"front":"If a target is not present, what must linear search do before stopping?","back":"Check every item.","mcqOptions":[{"text":"Check every item.","correct":true,"explanation":"If the target is absent, linear search has no earlier match to stop at, so it must compare the target with every item before concluding it is missing."},{"text":"Check half the items.","correct":false,"explanation":"Checking only half the items could miss the target in the unchecked half. An unsuccessful linear search must examine every item before stopping."},{"text":"Check the first item.","correct":false,"explanation":"Checking the first item alone cannot establish that an absent target is nowhere else in the list. All items must be searched."},{"text":"Check the last item.","correct":false,"explanation":"The final item is not sufficient evidence that earlier items were checked. Linear search must inspect the entire list when no match exists."}]},{"id":"1aefaf08-4275-46a8-acc5-a59b7789ed12","cardType":"basic","points":1,"front":"Worst-case linear search on 64 values may check how many values?","back":"64 values.","mcqOptions":[{"text":"64 values.","correct":true,"explanation":"In the worst case, the target is the last value or is absent, so linear search may compare against all 64 values."},{"text":"32 values.","correct":false,"explanation":"Thirty-two checks represent half the list, but an unsuccessful search or a target at the end may require checking all 64 values."},{"text":"63 values.","correct":false,"explanation":"The number 63 is one less than the list size and can result from an off-by-one error. The last value may also need checking."},{"text":"1 value.","correct":false,"explanation":"A single check applies only when the target is first. Worst-case linear search examines every value, not just one."}]},{"id":"3a831d3f-f67b-414a-88b3-ceed0cbd58ad","cardType":"basic","points":1,"front":"What happens to the search area after each binary-search comparison?","back":"It is halved.","mcqOptions":[{"text":"It is halved.","correct":true,"explanation":"Binary search compares with the middle and eliminates the half that cannot contain the target, leaving a search area that is approximately half as large."},{"text":"It is reduced by one item.","correct":false,"explanation":"Removing only one item describes a slow sequential process, not binary search. Binary search discards an entire half after each comparison."},{"text":"It is quartered.","correct":false,"explanation":"Binary search does not normally reduce the remaining area to one quarter at each step. One comparison eliminates roughly one half."},{"text":"It is doubled.","correct":false,"explanation":"The search area becomes smaller after a comparison, not larger. The discarded half is excluded because the sorted order rules it out."}]},{"id":"28e07c69-1ee0-481c-9a7a-c89e9da2b59f","cardType":"basic","points":1,"front":"For a fair efficiency comparison, what should be the same about the input?","back":"Use the same input data or input size.","mcqOptions":[{"text":"Use the same input data or input size.","correct":true,"explanation":"Using the same input data or the same input size ensures the algorithms face comparable work, making the efficiency comparison fair."},{"text":"Use different input data or input size.","correct":false,"explanation":"Different input sizes can require different amounts of work, so comparing them may make one algorithm appear faster unfairly. The input should be matched."},{"text":"Use the same output data or output size.","correct":false,"explanation":"Outputs are produced after processing and do not define the workload presented to the algorithm. Fair testing matches the input data or its size."},{"text":"Use the same hardware or programming language.","correct":false,"explanation":"Hardware and language can affect real timings, but matching them alone does not ensure equal workloads. The input data or size must also be the same."}]},{"id":"ed8ef2d7-bc50-48f4-845c-bb14cc594353","cardType":"basic","points":1,"front":"For a fair comparison, what must both algorithms produce?","back":"The same expected output.","mcqOptions":[{"text":"The same expected output.","correct":true,"explanation":"Both algorithms must solve the same problem and give the same expected result; otherwise, a faster algorithm might simply be producing a different or less useful answer."},{"text":"The same input data.","correct":false,"explanation":"The input should normally be the same, but matching inputs alone does not guarantee a fair comparison if the algorithms produce different results. The required condition is the same expected output."},{"text":"The same running time.","correct":false,"explanation":"Algorithms can have different running times, so equal speed cannot be required for comparison. A fair test requires both to produce the same expected output."},{"text":"The same program code.","correct":false,"explanation":"Using the same programming language may help control the test, but it does not ensure the algorithms solve the same task. Both must produce the same expected output."}]},{"id":"8ddf916a-a147-4876-8c7e-e678fc5f45b6","cardType":"basic","points":2,"front":"What can go wrong if binary search is used on an unsorted list?","back":"It may discard the half containing the target.","mcqOptions":[{"text":"It may discard the half containing the target.","correct":true,"explanation":"Binary search relies on the list being ordered. On an unsorted list, the comparison gives no reliable information about which half contains the target, so the correct half may be removed."},{"text":"It may check every item in the list.","correct":false,"explanation":"Binary search does not necessarily inspect every item; that is closer to linear search. The actual danger is that an unsorted list can cause it to discard the half containing the target."},{"text":"It may sort the list automatically.","correct":false,"explanation":"Binary search does not sort the list as part of its search process. Without prior sorting, it may discard the half containing the target based on an invalid comparison."},{"text":"It may compare only the first item.","correct":false,"explanation":"Checking only the first item is not the characteristic failure of binary search. The problem is that unsorted data can make it discard the half containing the target."}]},{"id":"ad1206e1-5cbe-4105-ad59-5604d9e811a0","cardType":"basic","points":2,"front":"Why might sorting first for one binary search not be worth it?","back":"Sorting takes time too.","mcqOptions":[{"text":"Sorting takes time too.","correct":true,"explanation":"For a single search, the time spent sorting may be greater than the time saved by binary search. The sorting overhead can therefore make the overall process less efficient."},{"text":"Binary search takes time too.","correct":false,"explanation":"Binary search also takes time, but sorting first is still worthwhile when many searches reuse the ordered list. For one search, the key issue is that sorting takes time too."},{"text":"The list needs memory too.","correct":false,"explanation":"A list does not become sorted merely because it is searched once. The relevant drawback is the extra time required to sort before carrying out the single binary search."},{"text":"The list becomes shorter too.","correct":false,"explanation":"Binary search can work on a list of any suitable size, so list size is not the main reason sorting may be wasteful. Sorting itself takes time before the one search."}]},{"id":"f2175caf-adc6-46c0-b650-68e90951f5df","cardType":"cloze","points":null,"front":"A sorting algorithm puts data into a [ ], such as [ ].","back":"A sorting algorithm puts data into a particular order, such as alphabetical order.","mcqOptions":[{"text":"A sorting algorithm puts data into a particular order, such as alphabetical order.","correct":true,"explanation":"Sorting means arranging data according to a defined order. Alphabetical order is one example, alongside other valid orders such as numerical order or chronological order."},{"text":"A sorting algorithm puts data into a particular order, such as random order.","correct":false,"explanation":"Sorting does not normally arrange data randomly. It puts values into a particular order, and alphabetical order is a valid example of that organised arrangement."},{"text":"A sorting algorithm puts data into the original order, such as alphabetical order.","correct":false,"explanation":"Sorting changes or confirms the arrangement according to a defined rule; it is not defined by preserving the original order. Alphabetical order is a suitable example of a particular order."},{"text":"A sorting algorithm puts data into a random order, such as alphabetical order.","correct":false,"explanation":"A random arrangement is not a sorting result, even if the example mentions alphabetical order. Sorting puts data into a particular order rather than an arbitrary arrangement."}]},{"id":"fc8eb816-ff65-41e5-aa11-669626b5d455","cardType":"basic","points":2,"front":"When comparing sorting algorithms on the same input, what makes one more time efficient?","back":"It uses fewer comparisons or passes.","mcqOptions":[{"text":"It uses fewer comparisons or passes.","correct":true,"explanation":"An algorithm that needs fewer comparisons or passes performs less repeated work on the same input. This generally makes it more time efficient, assuming the comparison conditions are otherwise fair."},{"text":"It uses more comparisons or passes.","correct":false,"explanation":"More comparisons or passes mean the algorithm performs more work on the same input, so it is generally less time efficient. Fewer comparisons or passes indicate better time efficiency."},{"text":"It uses the same comparisons or passes.","correct":false,"explanation":"The same number of comparisons or passes would not make one algorithm more efficient on that basis. The more efficient algorithm uses fewer comparisons or passes."},{"text":"It uses fewer lines of code.","correct":false,"explanation":"Shorter source code does not necessarily perform fewer operations when running. Time efficiency is assessed by work such as comparisons or passes, not code length alone."}]},{"id":"f7b94d80-4f5f-4c20-8622-cc7791f56771","cardType":"basic","points":2,"front":"Why is shorter code not automatically more efficient?","back":"Efficiency is about work done when running, not lines of code.","mcqOptions":[{"text":"Efficiency is about work done when running, not lines of code.","correct":true,"explanation":"Time efficiency measures the operations an algorithm performs while executing, such as comparisons and assignments. Source-code length does not directly show how much runtime work is required."},{"text":"Efficiency is about lines of code written, not work done when running.","correct":false,"explanation":"Lines of code describe the program's written size, not necessarily its runtime work. A short program can contain an inefficient loop, while efficiency concerns work done when running."},{"text":"Efficiency is about speed of writing code, not work done when running.","correct":false,"explanation":"Typing speed affects how quickly code is created, not how efficiently the algorithm executes. Algorithmic efficiency concerns the work done when running, rather than development time."},{"text":"Efficiency is about number of comments, not work done when running.","correct":false,"explanation":"The number of comments helps explain code but does not determine its execution time. Efficiency depends on work done when running, not on documentation length."}]}]}],"examCountdown":{"examDate":"2027-05-10","paperLabel":"Paper 1"},"heading":"Efficiency of algorithms","title":"Efficiency of algorithms Flashcards","topbar":{"backHref":"/gcse/computer-science/aqa/flashcards"},"topicSidebar":"$L37"}]}],"topicId":"727f8dc2-68db-5a0a-9b5f-3946a97b43a1","walled":"$L38"}],"$L39","$L3a"]