Supported HL focus. First assessment 2027 target; official PDF returns 403; older acquired brief is final assessment 2026. Remaining guide, assessment and practical requirements retain their recorded holds.
Prerequisites: read the stated quantities and units, use arithmetic and the model conditions below. Each lesson develops its own method before independent transfer.
These are original or explicitly fictional teaching examples, not actual measurements or completed assessed learner investigations.
1.2
Computing systems, networks and requirements
English
What would explain this observation?
A school booking system can calculate correctly and still fail if users lose access or records are disclosed. Success includes the system context.
Start with a prediction. State the quantities or features you would compare, then decide what evidence could distinguish two explanations.
Build the model
A computer system combines hardware, software, data and people. A network enables communication using protocols. Requirements should distinguish function from constraints such as availability, security and accessibility.
Separate authentication from authorization. Authentication checks identity; authorization determines permitted actions. A threat model connects a valuable asset, a possible attack and an appropriate control.
Use a fictitious school dataset to define users and permissions. Draw data flows, compare validation and verification, and specify tests for normal, boundary and invalid input. Do not use real credentials or student records in exercises.
Work from known quantities
State the known values and their units. Choose the relation because its assumptions fit this case, then rearrange before substitution.
Known: a file contains 12 megabytes, where this example defines one megabyte as one million bytes. Bits = bytes×8 = 12×1,000,000×8 = 96,000,000 bits. At 8,000,000 bits per second, ideal time = size/rate = 12 s, excluding overhead.
Example:
A 40 million bit file transfers at 5 million bits per second. Find ideal time. Use the same sequence: known quantities → model → relation → substitution → unit and interpretation.
Check the conclusion and its limits
Bandwidth is not actual end-to-end throughput. Encryption does not by itself ensure correct authorization or remove every security risk.
Return to the original observation. Explain what the result supports, which conditions it assumes, and one way to test a competing explanation.
Warn:
Encryption guarantees that every user has appropriate access permissions. This claim is false: Bandwidth is not actual end-to-end throughput. Encryption does not by itself ensure correct authorization or remove every security risk.
Key:
Computing systems, networks and requirements: Separate authentication from authorization. Authentication checks identity; authorization determines permitted actions. A threat model connects a valuable asset, a possible attack and an appropriate control.
Decimal MB means one million bytes; multiply by eight before dividing by bits per second. Zero data has zero ideal transmission duration. A nonpositive rate is rejected; actual overhead is outside this arithmetic model.
지원 HL 집중. 첫 평가 2027 목표; 공식 PDF는 403 반환; 기존 확보 요약은 최종 평가 2026임. 남은 가이드, 평가 및 실습 요구사항은 기록된 상태 유지됨.
사전 요구사항: 명시된 양과 단위를 읽고, 산술 및 아래 모델 조건을 사용하십시오. 각 수업은 독립적 이전 전에 자체 방법을 개발합니다.
이는 실제 측정값이나 완성된 평가된 학습자 조사가 아닌, 원작 또는 명시적으로 허구적인 교육 예시입니다.
2.2
네트워크: 지연 시간, 처리량 및 계층적 전달
이 관측을 설명할 수 있는 것은 무엇인가?
낮은 대역폭 링크에서도 작은 메시지는 늦게 도착할 수 있습니다. 용량과 지연거리는 서로 다른 특성을 측정합니다.
예측을 먼저 제시하십시오. 비교하고자 하는 양이나 특성을 명시한 뒤, 두 설명을 구별할 수 있는 증거가 무엇인지 결정하십시오.
모델을 구축하시오
패킷은 주소가 지정된 데이터를 네트워크를 통해 전달합니다. 계층적 모델은 애플리케이션 의미, 전송 Delivery 및 네트워크 라우팅과 같은 책임을 분리합니다. 대역폭은 용량을 설명하며, 스루풋은 달성된 데이터 전송 속도이며, 지연(latency) 은 지연 시간입니다.
throughput(스루풋): 유용한 데이터 전송의 달성 속도; latency(레이턴시): 통신에서 발생하는 지연 시간.
이를 검증할 수 있는 증거를 선택하시오
전송 시간은 데이터 크기와 속도에 따라 결정됩니다. 총 지연에는 전파, 처리 및 대기 Queueing도 포함될 수 있습니다. 암호화는 가정 조건 하에서 콘텐츠를 보호하지만, 혼잡이나 모든 메타데이터 노출을 제거하지는 않습니다.
문서화된 로컬 모델을 사용하여 메시지 경로를 추적하십시오. 페이로드 크기, 단위 및 측정한 시간을 기록하십시오. 학교 승인을 받은 네트워크와 합성(message) 메시지를 사용하되, 다른 사용자의 트래픽을 스캔하거나 intercepted하지 마십시오.
알려진 양으로부터 시작하시오
알려진 값과 그 단위를 명시하십시오. 이 사례에 가정이 부합하는 식을 선택한 후 대입하기前面으로 변형하십시오.
주어진 정보: 8 메가비트 파일이 2 메가비트/초 링크를 통과한다. 이상 전송 시간 = 크기/속도 = 8/2 = 4 초. 프로토콜 오버헤드, 다른 사용자 및 지연 시간(latency)으로 인해 실제 측정된 완료 시간이 더 느릴 수 있다.
예시:
12 메가비트 파일이 3 메가비트/초 링크를 통과합니다. 이상적인 전송 시간을 계산하십시오. 동일한 순서를 사용하십시오:已知 quantity → 모델 → 관계 → 치환 → 단위 및 해석.
결론과 그 한계를 확인하시오
오버헤드를 고려하기 전에 메가바이트는 메가비트 8개입니다. 더 빠른 argparse 링크가 낮은 지연 시간이나 안전한 endpoints를 보장하지는 않습니다.
원래 관찰로 돌아가십시오. 결과가 어떤 것을 지지하며, 어떤 조건을 전제로 하며, 경쟁 설명을 검증하는 방법 하나를 제시하십시오.
경고:
고대역폭 연결은 지연 시간을 0으로 보장합니다. 이 주장은 틀렸습니다: 오버헤드를 고려하기 전에 메가바이트는 메가비트 8개입니다. 더 빠른 argparse 링크가 낮은 지연 시간이나 안전한 endpoints를 보장하지는 않습니다.
핵심:
네트워크: 지연, 스루풋 및 계층적 Delivery: 전송 시간은 데이터 크기와 속도에 따라 결정됩니다. 총 지연에는 전파, 처리 및 대기 Queueing도 포함될 수 있습니다. 암호화는 가정 조건 하에서 콘텐츠를 보호하지만, 혼잡이나 모든 메타데이터 노출을 제거하지는 않습니다.
Supported HL focus. First assessment 2027 target; official PDF returns 403; older acquired brief is final assessment 2026. Remaining guide, assessment and practical requirements retain their recorded holds.
Prerequisites: read the stated quantities and units, use arithmetic and the model conditions below. Each lesson develops its own method before independent transfer.
These are original or explicitly fictional teaching examples, not actual measurements or completed assessed learner investigations.
3.2
Relational databases: a key and a relationship
English
What would explain this observation?
Duplicating a user address in every order can produce conflicting records when the address changes.
Start with a prediction. State the quantities or features you would compare, then decide what evidence could distinguish two explanations.
Build the model
A relational table contains rows and attributes. A primary key 主键 identifies a row; a foreign key 外键 links to a referenced key in another table. Normalization can reduce avoidable duplication and update anomalies while preserving meaningful relationships.
primary key: Attribute set uniquely identifying a table row; foreign key: Attribute set referencing a key in another table.
Choose evidence that can test it
A join combines rows according to a specified condition. The result count depends on relationship cardinality and filters. A foreign key constraint enforces a relationship rule; it does not automatically encrypt personal data.
Design a small synthetic user-order dataset with no real personal information. Declare keys, test duplicate and missing-reference inserts, then check a query result against a hand-worked expected table.
Work from known quantities
State the known values and their units. Choose the relation because its assumptions fit this case, then rearrange before substitution.
Known: four customers have respectively 2, 0, 3 and 1 orders. An inner join of customer to order returns 2+0+3+1 = 6 rows. A left join also retains the customer with no order as one null-matched row, giving 7 here.
Example:
Three customers have 1, 3 and 2 orders. How many rows does the customer-order inner join return? Use the same sequence: known quantities → model → relation → substitution → unit and interpretation.
Check the conclusion and its limits
A primary key need not be a person name. A join is not a simple concatenation of tables. Use parameterized queries for untrusted input rather than building SQL from raw strings.
Return to the original observation. Explain what the result supports, which conditions it assumes, and one way to test a competing explanation.
Warn:
A foreign key automatically encrypts every row. This claim is false: A primary key need not be a person name. A join is not a simple concatenation of tables. Use parameterized queries for untrusted input rather than building SQL from raw strings.
Key:
Relational databases: a key and a relationship: A join combines rows according to a specified condition. The result count depends on relationship cardinality and filters. A foreign key constraint enforces a relationship rule; it does not automatically encrypt personal data.
Runnable trace and boundary
import sqlite3
db = sqlite3.connect(":memory:")
db.executescript("""CREATE TABLE c(id INTEGER PRIMARY KEY);
CREATE TABLE o(id INTEGER PRIMARY KEY, cid INTEGER);
INSERT INTO c VALUES(1),(2),(3);
INSERT INTO o VALUES(10,1),(11,1),(12,3);""")
for kind in ["INNER", "LEFT"]:
sql = f"SELECT COUNT(*),COUNT(o.id) FROM c {kind} JOIN o ON c.id=o.cid"
print(kind, db.execute(sql).fetchone())
db.close()
Expected output:
INNER (3, 3)
LEFT (4, 3)
The left join retains customer 2 with null order fields. COUNT(*) includes that row, while COUNT(o.id) excludes null. Primary keys distinguish records; customer count is not order count. The interpolated join keyword comes from a fixed internal list, not user input.
Supported HL focus. First assessment 2027 target; official PDF returns 403; older acquired brief is final assessment 2026. Remaining guide, assessment and practical requirements retain their recorded holds.
Prerequisites: read the stated quantities and units, use arithmetic and the model conditions below. Each lesson develops its own method before independent transfer.
These are original or explicitly fictional teaching examples, not actual measurements or completed assessed learner investigations.
4.2
Data models and responsible machine learning
English
What would explain this observation?
A model can score well by learning a shortcut in the training data. Evaluation must test the intended task on appropriate unseen examples.
Start with a prediction. State the quantities or features you would compare, then decide what evidence could distinguish two explanations.
Build the model
A relational database uses tables, keys and relationships to organize data. Machine learning estimates patterns from data. Training and evaluation data serve different roles.
primary key 主键: An attribute set uniquely identifying a record; data leakage 数据泄漏: Use of information unavailable at the intended prediction time.
Choose evidence that can test it
A primary key uniquely identifies a record; a foreign key relates records. In prediction, leakage can expose information unavailable at the real decision time. Accuracy alone may hide an unbalanced target distribution.
Use fictional booking records to identify entities, attributes and relationships. For a learning exercise, use a public non-sensitive dataset, separate training and test data, and describe who may be affected by errors. The current 2027 CS objective scope awaits the acquired guide.
Work from known quantities
State the known values and their units. Choose the relation because its assumptions fit this case, then rearrange before substitution.
Known: a classifier makes 90 correct predictions among 100 cases. Accuracy = correct/total×100 = 90%. If 90 cases belong to one class, always predicting that class gives the same accuracy and can still fail every minority-class case.
Example:
A model makes 72 correct predictions out of 80. Find accuracy percentage. Use the same sequence: known quantities → model → relation → substitution → unit and interpretation.
Check the conclusion and its limits
High accuracy is not evidence of fairness or causal understanding. A database primary key is not simply whichever field looks important.
Return to the original observation. Explain what the result supports, which conditions it assumes, and one way to test a competing explanation.
Warn:
A classifier with 90% accuracy must treat every class equally well. This claim is false: High accuracy is not evidence of fairness or causal understanding. A database primary key is not simply whichever field looks important.
Key:
Data models and responsible machine learning: A primary key uniquely identifies a record; a foreign key relates records. In prediction, leakage can expose information unavailable at the real decision time. Accuracy alone may hide an unbalanced target distribution.
Accuracy divides correct predictions by all cases; positive recall divides true positives by actual positives. With no positive cases, recall is undefined rather than zero. The dataset is fictional, with no trained model or personal data.
지원 HL 집중. 첫 평가 2027 목표; 공식 PDF는 403 반환; 기존 확보 요약은 최종 평가 2026임. 남은 가이드, 평가 및 실습 요구사항은 기록된 상태 유지됨.
사전 요구사항: 명시된 양과 단위를 읽고, 산술 및 아래 모델 조건을 사용하십시오. 각 수업은 독립적 이전 전에 자체 방법을 개발합니다.
이는 실제 측정값이나 완성된 평가된 학습자 조사가 아닌, 원작 또는 명시적으로 허구적인 교육 예시입니다.
5.2
알고리즘, 추적 및 타당성 증거
이 관측을 설명할 수 있는 것은 무엇인가?
알고리즘은 한 예제에서는 작동하지만 경계에서 실패할 수 있습니다. 테스트는 happy path뿐만 아니라 사양(specification)에 기반하여 설계되어야 합니다.
예측을 먼저 제시하십시오. 비교하고자 하는 양이나 특성을 명시한 뒤, 두 설명을 구별할 수 있는 증거가 무엇인지 결정하십시오.
모델을 구축하시오
알고리즘은 작업에 대한 유한하고 모호하지 않은 절차입니다. 트race는 상태 변경을 기록합니다. 루프 불변식(loop invariant)은 각 반복에서 유지되는 성질을 기술하며 correctness를 정당화하는 데 도움이 됩니다.
알고리즘(algorithm): 명시된 과제를 해결하는 유한한 절차; 경계 테스트(boundary test): 허용된 입력 범위의 한계에서 수행되는 테스트.
이를 검증할 수 있는 증거를 선택하시오
입력 조건과 예상 출력을 명시하십시오. 경계 사례, 허용되는 경우의 빈 집합, 중복 및 유효하지 않은 값을 사용하십시오. 잘못된 알고리즘을 잘못된 구현 또는 불완전한 요구 사항과 구분하십시오.
작은 가상의 정렬된 목록에 대한 탐색을 추적하십시오. 인덱싱 관례를 명시하십시오. 이진 탐색의 경우 남은 구간이 줄어도록 범위를 업데이트하고, 정렬이 과제의 일부가 아닌 한 정렬되지 않은 입력은 거부하십시오.
알려진 양으로부터 시작하시오
알려진 값과 그 단위를 명시하십시오. 이 사례에 가정이 부합하는 식을 선택한 후 대입하기前面으로 변형하십시오.
알려진 사실: 8개 항목의 목록에 대한 일차 탐색은 찾는 항목이 마지막이거나 존재하지 않을 때 8번의 비교가 필요할 수 있습니다. 이 모델에서 목록 길이를 두 배로 늘리면最差情况의 비교 횟수도 두 배가 됩니다. 이진 탐색은 각 단계마다 구간을 약 절반으로 줄이지만 적절한 순서 구조가 필요합니다.
예시:
일차 탐색은 일치하는 14 항목 없이 모든 항목을 스캔합니다. 몇 번의 항목 비교가 발생합니까? 동일한 순서를 사용하십시오: 알려진 양 → 모델 → 관계 → 대입 → 단위 및 해석.
결론과 그 한계를 확인하시오
성공적인 샘플 테스트는 모든 유효한 입력에 대해 정확성을 증명하지 않습니다. 교재 소스가 없는 한 Cambridge 특유의 가상어법 구문을 IB 과정에 도입하지 마십시오.
원래 관찰로 돌아가십시오. 결과가 어떤 것을 지지하며, 어떤 조건을 전제로 하며, 경쟁 설명을 검증하는 방법 하나를 제시하십시오.
경고:
한 개의 성공적인 샘플 테스트가 모든 유효한 입력에 대해 알고리즘이 옳음을 증명합니다. 이 주장은 틀렸습니다: 성공적인 샘플 테스트는 모든 유효한 입력에 대해 정확성을 증명하지 않습니다. 교재 소스가 없는 한 Cambridge 특유의 가상어법 구문을 IB 과정에 도입하지 마십시오.
핵심:
알고리즘, 추적 및 정확성 증거: 입력 조건과 예상 출력을 명시하십시오. 경계 사례, 허용되는 경우의 빈 집합, 중복 및 유효하지 않은 값을 사용하십시오. 잘못된 알고리즘을 잘못된 구현 또는 불완전한 요구 사항과 구분하십시오.
가동성 추跡 및 경계
def first_index(values, target):
for index, value in enumerate(values):
if value == target:
return index
return -1
print(first_index([4, 7, 4], 4))
print(first_index([4, 7, 4], 9))
print(first_index([], 4))
기대 출력:
0
-1
-1
루프는 인덱스 0을 먼저 테스트하여 일치할 때 정지하고,列表 소진 후 −1만 반환. 중복인 경우 첫 번째 인덱스 반환. 빈列表는 루프 본문을 실행하지 않음.
Supported HL focus. First assessment 2027 target; official PDF returns 403; older acquired brief is final assessment 2026. Remaining guide, assessment and practical requirements retain their recorded holds.
Prerequisites: read the stated quantities and units, use arithmetic and the model conditions below. Each lesson develops its own method before independent transfer.
These are original or explicitly fictional teaching examples, not actual measurements or completed assessed learner investigations.
7.2
Objects: state, behaviour and an interface
English
What would explain this observation?
Two bank-account model objects can respond to the same deposit operation while holding different balances.
Start with a prediction. State the quantities or features you would compare, then decide what evidence could distinguish two explanations.
Build the model
A class defines a type with state and behaviour. An object is an instance 实例. Encapsulation 封装 controls access through an interface so operations can preserve invariants. Inheritance models an appropriate type relationship; composition models an object containing or using another object.
encapsulation: Controlling access to state through an interface; instance: An individual object of a class.
Choose evidence that can test it
A method call acts on a particular instance. State changes should satisfy preconditions and postconditions. Polymorphism lets code use a common interface with different implementations when the contract is respected.
Implement a small synthetic account or inventory model. Test two independent instances, rejected invalid operations and boundary values. Keep the model away from real financial accounts and credentials.
Work from known quantities
State the known values and their units. Choose the relation because its assumptions fit this case, then rearrange before substitution.
Known: object A starts at 40 units and receives 15; object B starts at 20 and receives 5. Final balances are 55 and 25. Their total is 80, but neither individual object balance is 80.
Example:
An instance starts at 12 units, adds 8 and removes 3. Find its final value. Use the same sequence: known quantities → model → relation → substitution → unit and interpretation.
Check the conclusion and its limits
A class is not the same thing as one instance. Inheritance is not automatically better than composition. Merely hiding a field does not prove that all operations preserve valid state.
Return to the original observation. Explain what the result supports, which conditions it assumes, and one way to test a competing explanation.
Warn:
Two instances of a class must always share one balance. This claim is false: A class is not the same thing as one instance. Inheritance is not automatically better than composition. Merely hiding a field does not prove that all operations preserve valid state.
Key:
Objects: state, behaviour and an interface: A method call acts on a particular instance. State changes should satisfy preconditions and postconditions. Polymorphism lets code use a common interface with different implementations when the contract is respected.
Runnable trace and boundary
class Account:
def __init__(self, balance):
self.balance = balance
def withdraw(self, amount):
if amount < 0 or amount > self.balance:
return False
self.balance -= amount
return True
a, b = Account(15), Account(20)
print(a.withdraw(30), a.balance, b.balance)
print(a.withdraw(15), a.balance, b.balance)
Expected output:
False 15 20
True 0 20
Rejection returns before mutation. With nonnegative initial balances, validated withdrawals preserve balance≥0. This small teaching class exposes attributes; a production design must control all mutation paths, not assume the method alone enforces encapsulation.
Supported HL focus. First assessment 2027 target; official PDF returns 403; older acquired brief is final assessment 2026. Remaining guide, assessment and practical requirements retain their recorded holds.
Prerequisites: read the stated quantities and units, use arithmetic and the model conditions below. Each lesson develops its own method before independent transfer.
These are original or explicitly fictional teaching examples, not actual measurements or completed assessed learner investigations.
8.2
Abstract data types: an operation contract
English
What would explain this observation?
A waiting-line simulation needs the oldest pending item first. A stack 栈 gives the most recent item first, so the operation contract matters.
Start with a prediction. State the quantities or features you would compare, then decide what evidence could distinguish two explanations.
Build the model
An abstract data type specifies values and operations independently of a particular implementation. A stack is last in, first out; a queue 队列 is first in, first out. A collection interface needs defined behaviour for empty and invalid operations.
stack: A last-in-first-out abstract data type; queue: A first-in-first-out abstract data type.
Choose evidence that can test it
Choose the structure for the required access pattern. Complexity depends on implementation and assumptions: removing the first item from a shifting array differs from advancing a head pointer in a queue.
Trace operation sequences by hand, then compare a program with the expected states. Test empty, singleton and repeated operations. State overflow behaviour if capacity is fixed.
Work from known quantities
State the known values and their units. Choose the relation because its assumptions fit this case, then rearrange before substitution.
Known: enqueue A, B and C, then dequeue twice. A and B leave; C remains. After enqueue D there are two pending items, C then D. The same pushes on a stack would remove C then B.
Example:
A queue starts empty, receives 7 items and removes 4. Find the number remaining. Use the same sequence: known quantities → model → relation → substitution → unit and interpretation.
Check the conclusion and its limits
An ADT is not a specific memory layout. A queue does not sort by priority unless its contract defines a priority queue.
Return to the original observation. Explain what the result supports, which conditions it assumes, and one way to test a competing explanation.
Warn:
Every queue automatically sorts items by priority. This claim is false: An ADT is not a specific memory layout. A queue does not sort by priority unless its contract defines a priority queue.
Key:
Abstract data types: an operation contract: Choose the structure for the required access pattern. Complexity depends on implementation and assumptions: removing the first item from a shifting array differs from advancing a head pointer in a queue.
Runnable trace and boundary
from collections import deque
queue = deque()
queue.extend(["A", "B"])
print(queue.popleft())
queue.append("C")
print(queue.popleft())
print(list(queue))
queue.clear()
print(queue.popleft() if queue else "EMPTY")
Expected output:
A
B
['C']
EMPTY
Removing from the left implements FIFO. The explicit empty guard defines the boundary result; deque.popleft without it would raise IndexError. A stack instead removes from the right.
Supported HL focus. First assessment 2027 target; official PDF returns 403; older acquired brief is final assessment 2026. Remaining guide, assessment and practical requirements retain their recorded holds.
Prerequisites: read the stated quantities and units, use arithmetic and the model conditions below. Each lesson develops its own method before independent transfer.
These are original or explicitly fictional teaching examples, not actual measurements or completed assessed learner investigations.
9.2
Computing case analysis: evaluate a proposed system
English
What would explain this observation?
A proposed school booking system looks efficient, but its recommendation depends on users, constraints and evidence. A plausible technical term alone is not a justified decision.
Start with a prediction. State the quantities or features you would compare, then decide what evidence could distinguish two explanations.
Build the model
A case study places computational choices within a stated scenario. Identify stakeholders, requirements, available evidence and constraints before recommending an architecture or algorithm. Distinguish a scenario fact from an assumption and a prediction. Trade-offs can involve performance, reliability, accessibility, privacy, maintenance and cost.
throughput 吞吐量: Completed work per unit time under a stated workload; acceptance test 验收测试: A test of whether a specified user requirement is met.
Choose evidence that can test it
A recommendation should connect a requirement to a mechanism and an observable test. For example, a concurrency problem requires a strategy that prevents conflicting updates, plus tests demonstrating the invariant. A claim about faster response requires comparable workload measurements rather than only a complexity label. Evaluate alternatives under the same stated conditions.
Use an original school-approved scenario and synthetic data. Build a matrix of claim, supporting scenario evidence, technical explanation, limitation and acceptance test. Mark missing facts explicitly and show how the recommendation would change if an assumption failed. This prepares case-based reasoning without reproducing an unavailable IB assessment case study or inventing its examination rubric.
Work from known quantities
State the known values and their units. Choose the relation because its assumptions fit this case, then rearrange before substitution.
Known: a fictional prototype processes 120 successful requests during a 30-second observation. Throughput is 120/30=4 successful requests/s. A second prototype processes 150 in 30 seconds, or 5/s. The second has 25% greater recorded throughput, but no conclusion about latency, failure rate or performance under a larger workload follows without those measurements.
Example:
A fictional system successfully processes 210 requests in 30 s. Calculate throughput. Use the same sequence: known quantities → model → relation → substitution → unit and interpretation.
Check the conclusion and its limits
Throughput is not response time. A strong recommendation states the conditions in which it is expected to work and the evidence that could disconfirm it. Current official CS case-study requirements must be checked against the applicable assessment version.
Return to the original observation. Explain what the result supports, which conditions it assumes, and one way to test a competing explanation.
Warn:
Higher observed throughput automatically proves lower response time for every request. This claim is false: Throughput is not response time. A strong recommendation states the conditions in which it is expected to work and the evidence that could disconfirm it. Current official CS case-study requirements must be checked against the applicable assessment version.
Key:
Computing case analysis: evaluate a proposed system: A recommendation should connect a requirement to a mechanism and an observable test. For example, a concurrency problem requires a strategy that prevents conflicting updates, plus tests demonstrating the invariant. A claim about faster response requires comparable workload measurements rather than only a complexity label. Evaluate alternatives under the same stated conditions.
Runnable trace and boundary
for successful, attempted, seconds in [(240, 300, 30), (270, 300, 30)]:
if seconds <= 0 or attempted <= 0:
raise ValueError("Positive exposure required")
throughput = successful / seconds
failure_fraction = (attempted - successful) / attempted
print(throughput, failure_fraction)
Expected output:
8.0 0.2
9.0 0.1
Success throughput and failure fraction use different denominators. Zero time or zero attempts cannot support those rates. These fictional summaries do not supply latency, cost or representative-load evidence.
