Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Lære Challenge: Simulate Test Coverage Tracking | Advanced QA Automation Techniques
Python for QA Engineers

bookChallenge: Simulate Test Coverage Tracking

Understanding and monitoring test coverage is a crucial aspect of quality assurance, as it helps you identify which parts of the codebase have been exercised by your tests and which have not. By simulating test coverage tracking, you can gain practical insights into how coverage tools operate and why they are valuable for continuous QA improvement. In this challenge, you will create a Python script that maintains a set of function names as they are "called" during test execution, then reports which functions from a predefined list were covered and which were not. This hands-on exercise reinforces the importance of thorough testing and the value of coverage metrics in real-world QA workflows.

Opgave

Swipe to start coding

Write a Python function to simulate test coverage tracking for a list of functions. You are provided with a list of all function names that should be tested, and a list of function names that were actually called during test execution.

  • Identify which function names from functions_to_test are present in tested_functions.
  • Identify which function names from functions_to_test are not present in tested_functions.
  • Prepare a string listing the covered functions, separated by commas, in sorted order.
  • Prepare a string listing the untested functions, separated by commas, in sorted order.
  • Print the covered functions with the label "Tested functions:".
  • Print the untested functions with the label "Untested functions:".

Løsning

Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 3. Kapitel 7
single

single

Spørg AI

expand

Spørg AI

ChatGPT

Spørg om hvad som helst eller prøv et af de foreslåede spørgsmål for at starte vores chat

close

bookChallenge: Simulate Test Coverage Tracking

Stryg for at vise menuen

Understanding and monitoring test coverage is a crucial aspect of quality assurance, as it helps you identify which parts of the codebase have been exercised by your tests and which have not. By simulating test coverage tracking, you can gain practical insights into how coverage tools operate and why they are valuable for continuous QA improvement. In this challenge, you will create a Python script that maintains a set of function names as they are "called" during test execution, then reports which functions from a predefined list were covered and which were not. This hands-on exercise reinforces the importance of thorough testing and the value of coverage metrics in real-world QA workflows.

Opgave

Swipe to start coding

Write a Python function to simulate test coverage tracking for a list of functions. You are provided with a list of all function names that should be tested, and a list of function names that were actually called during test execution.

  • Identify which function names from functions_to_test are present in tested_functions.
  • Identify which function names from functions_to_test are not present in tested_functions.
  • Prepare a string listing the covered functions, separated by commas, in sorted order.
  • Prepare a string listing the untested functions, separated by commas, in sorted order.
  • Print the covered functions with the label "Tested functions:".
  • Print the untested functions with the label "Untested functions:".

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 3. Kapitel 7
single

single

some-alt