Performance test planning in Testing Fundamentals - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Key Metric Identification in Performance Testing

Which of the following is the most important metric to monitor during a load test to understand system responsiveness?

A CPU usage percentage

B Response time of requests

C Number of test scripts executed

D Disk space available

💡 Hint

Think about what tells you how fast the system reacts to user actions.

Response time directly measures how quickly the system responds to requests, which is critical for user experience during load.

🧠 Conceptual

intermediate

Purpose of Baseline Testing

What is the main purpose of establishing a baseline in performance test planning?

A To identify the maximum number of users the system can handle

B To verify the correctness of functional requirements

C To test the system's security vulnerabilities

D To measure current system performance under normal conditions

💡 Hint

Baseline is about knowing how the system behaves before changes.

Baseline testing measures system performance under normal conditions to compare against future tests.

❓ framework

advanced

Selecting Performance Test Types

You are planning a performance test for a web application expected to have sudden spikes in user traffic. Which combination of test types should you include to best simulate this scenario?

A Load testing and stress testing

B Baseline testing and usability testing

C Security testing and regression testing

D Functional testing and smoke testing

💡 Hint

Think about tests that simulate normal and extreme user loads.

Load testing simulates expected user traffic, while stress testing pushes beyond limits to see how the system handles spikes.

❓ assertion

advanced

Validating Performance Test Success Criteria

Given a performance test plan with the success criterion: "Response time must be under 2 seconds for 95% of requests." Which assertion correctly validates this criterion after test execution?

Testing Fundamentals

assert (sum(t <= 2 for t in response_times) / len(response_times)) >= 0.95

A assert (sum(t <= 2 for t in response_times) / len(response_times)) >= 0.95

B assert (len([t for t in response_times if t <= 2]) / len(response_times)) >= 0.95

C assert (max(response_times) <= 2)

D assert (sum(response_times) / len(response_times)) < 2

💡 Hint

Focus on counting requests with response time less than or equal to 2 seconds.

Option A correctly counts requests with response time ≤ 2 seconds and checks if they are at least 95% of total.

🔧 Debug

expert

Identifying a Bottleneck from Performance Test Results

After running a performance test, the CPU usage is low, memory usage is stable, but response times increase drastically under load. What is the most likely cause?

A CPU overheating causing throttling

B Memory leaks causing slowdowns

C Network bandwidth saturation causing delays

D Disk space running out causing errors

💡 Hint

Think about what can cause slow responses without high CPU or memory use.

Network bandwidth saturation can cause delays in response times even if CPU and memory are fine.

Practice

1. What is the main purpose of performance test planning in software testing?

easy

A. To organize how to check software speed and stability

B. To write code for new software features

C. To design the user interface of the software

D. To fix bugs found during testing

Solution

1. Step 1: Understand the goal of performance test planning

   Performance test planning focuses on preparing tests that measure how fast and stable software is under load.

2. Step 2: Compare options with this goal

   Only To organize how to check software speed and stability matches this goal; others relate to development or bug fixing, not planning performance tests.

3. Final Answer:

   To organize how to check software speed and stability -> Option A

4. Quick Check:

   Performance test planning = Organize speed and stability checks [OK]

Hint: Performance planning = organizing speed and stability tests [OK]

Common Mistakes:

• Confusing performance planning with coding or UI design
• Thinking bug fixing is part of test planning
• Mixing test planning with test execution

2. Which of the following is a correct step in performance test planning?

easy

A. Ignoring user load expectations

B. Avoiding setting performance goals

C. Choosing appropriate testing tools

D. Skipping test scheduling

Solution

1. Step 1: Identify key steps in performance test planning

   Good planning includes setting goals, choosing tools, and scheduling tests.

2. Step 2: Evaluate each option

   Only choosing appropriate testing tools is a correct and necessary step; others are mistakes.

3. Final Answer:

   Choosing appropriate testing tools -> Option C

4. Quick Check:

   Performance planning step = Choose tools [OK]

Hint: Pick the step that supports testing, not ignores it [OK]

Common Mistakes:

• Ignoring user load expectations
• Skipping scheduling of tests
• Not setting clear performance goals

3. Consider this simplified performance test plan snippet:

test_plan = {
  "goals": ["Check response time under 2s"],
  "tools": ["LoadRunner"],
  "schedule": "Weekly"
}
print(test_plan["goals"][0])

What will be the output when this code runs?

medium

A. "LoadRunner"

B. "Weekly"

C. KeyError

D. "Check response time under 2s"

Solution

1. Step 1: Understand the dictionary structure

   test_plan has keys 'goals', 'tools', and 'schedule'. 'goals' is a list with one string: "Check response time under 2s".

2. Step 2: Analyze the print statement

   print(test_plan["goals"][0]) accesses the first item in the 'goals' list, which is "Check response time under 2s".

3. Final Answer:

   "Check response time under 2s" -> Option D

4. Quick Check:

   Access first goal string = "Check response time under 2s" [OK]

Hint: Access list inside dict by key then index [OK]

Common Mistakes:

• Confusing keys and values in dictionary
• Trying to print the whole list instead of first item
• Expecting a KeyError due to wrong key

4. A tester wrote this performance test plan code:

test_plan = {
  "goals": "Check response time",
  "tools": ["JMeter"],
  "schedule": "Daily"
}
print(test_plan["goals"][0])

What is the error in this code?

medium

A. Using a string instead of a list for 'goals' causes an error

B. Missing comma after 'tools' list

C. Incorrect key name 'goals' in dictionary

D. Print statement syntax is wrong

Solution

1. Step 1: Check the data type of 'goals'

   'goals' is a string, but the code tries to access it like a list with [0]. Strings support indexing, but here it prints the first character, which may be unintended.

2. Step 2: Understand the intention and error

   The plan expects 'goals' to be a list of goals, not a single string. Accessing [0] on a string returns 'C', not the full goal. This is a logical error in planning structure.

3. Final Answer:

   Using a string instead of a list for 'goals' causes an error -> Option A

4. Quick Check:

   'goals' should be list, not string [OK]

Hint: Lists need brackets [] for multiple goals [OK]

Common Mistakes:

• Treating string as list of goals
• Ignoring data types in test plan
• Assuming print syntax error instead of data error

5. You are planning a performance test for a web app expecting 1000 users simultaneously. Which of the following is a correct action to include in your plan to ensure effective testing?

A. Set clear performance goals like max response time
B. Skip tool selection to save time
C. Schedule tests during peak user hours
D. Ignore analyzing test results after execution

hard

A. Skip tool selection to save time

B. Set clear performance goals like max response time

C. Schedule tests during peak user hours

D. Ignore analyzing test results after execution

Solution

1. Step 1: Identify important planning actions for performance tests

   Setting clear performance goals (e.g., max response time under 1000 user load) is essential to measure success.

2. Step 2: Evaluate each option

   Only A is a correct action; B skips necessary tools, C risks production disruption during real peak usage (simulate in staging), D skips vital analysis.

3. Final Answer:

   Set clear performance goals like max response time -> Option B

4. Quick Check:

   Clear goals = effective performance test plan [OK]

Hint: Set clear goals for success [OK]

Common Mistakes:

• Skipping tool selection reduces test accuracy
• Ignoring results wastes test effort
• Not simulating real user load