Identifying performance bottlenecks in Testing Fundamentals - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

What is the primary cause of a CPU bottleneck in software performance?

Imagine your computer is like a kitchen. The CPU is the chef who prepares meals. What usually causes the chef to slow down the whole kitchen?

A The kitchen has too many ovens but not enough chefs

B The chef has too many tasks to do at once and can't keep up

C The ingredients are delivered late to the kitchen

D The kitchen is too big and chefs have to walk too far

💡 Hint

Think about what limits the chef's speed directly.

A CPU bottleneck happens when the processor has more work than it can handle at once, slowing down the entire system.

❓ Predict Output

intermediate

What is the output of this Python code simulating a slow function call?

Consider this code that simulates a slow function by sleeping. What will be printed?

Testing Fundamentals

import time
start = time.time()
for _ in range(3):
    time.sleep(0.5)
end = time.time()
print(round(end - start, 1))

A 3.0

B 0.5

C 1.5

D 1.0

💡 Hint

Each sleep lasts 0.5 seconds and runs 3 times.

The loop sleeps 0.5 seconds three times, totaling about 1.5 seconds.

❓ assertion

advanced

Which assertion correctly checks that a function runs under 2 seconds?

You want to test that process_data() finishes in less than 2 seconds. Which assertion is correct?

Testing Fundamentals

import time
start = time.time()
process_data()
end = time.time()
# Which assertion below is correct?

A assert (end - start) < 2

B assert (start - end) < 2

C assert (end + start) < 2

D assert (end * start) < 2

💡 Hint

Think about how to measure elapsed time.

Elapsed time is end minus start. It should be less than 2 seconds.

🔧 Debug

advanced

Identify the performance bottleneck in this code snippet

Look at this Python code that processes a list. What causes the slowdown?

Testing Fundamentals

data = list(range(100000))
result = []
for i in data:
    if i % 2 == 0:
        result.append(i)
    else:
        result.append(i*2)
print(len(result))

A The print statement slows down the program

B Using modulo operator (%) causes errors

C The range function is slow for large numbers

D Using a for-loop with append instead of list comprehension

💡 Hint

Think about how Python handles list building efficiently.

Using a for-loop with append is slower than list comprehension for large lists.

❓ framework

expert

Which tool is best suited to identify database query bottlenecks in a web app?

You want to find slow database queries causing delays in your web application. Which tool helps best?

A A profiler that tracks SQL query execution times

B A unit testing framework for UI components

C A code linter that checks syntax errors

D A version control system like Git

💡 Hint

Focus on tools that measure performance, not code correctness.

A profiler that tracks SQL query times helps find slow queries causing bottlenecks.