GITNUX MARKETDATA REPORT 2023
Must-Know Code Coverage Metrics
Highlights: The Most Important Code Coverage Metrics
- 1. Statement Coverage
- 2. Branch Coverage
- 3. Function Coverage
- 4. Condition Coverage
- 5. Path Coverage
- 6. Line Coverage
- 7. Class Coverage
- 8. Decision Coverage
- 9. Loop Coverage
- 10. Entry/Exit Coverage
- 11. Multicondition Coverage
- 12. Integration Coverage
Table of Contents
Code Coverage Metrics: Our Guide
Dive into our updated report on must-know code coverage metrics, a fundamental resource for software developers and testers across the globe. Keeping an eye on these metrics is integral to ensuring the effectiveness, reliability, and overall quality of your software. Unearth the latest insights and trends to enhance your code quality and boost your software’s performance.
Measures the percentage of code statements executed during testing. It helps identify parts of the code that were not executed and can reveal gaps in test scenarios.
Evaluates the percentage of branches (e.g, if-else statements) executed during testing, ensuring both true and false conditions are tested.
Assesses the percentage of program functions or methods that have been called during testing. It helps identify untested portions of the codebase and incomplete test suites.
Quantifies the percentage of logical conditions within a program that have been evaluated during testing, ensuring all possible outcomes of each condition are tested.
Calculates the percentage of unique paths through the code that have been executed during testing. It takes into account all possible sequences of function calls, loops, and branches.
Analyzes the percentage of lines of code executed during testing. It provides a high-level view of code coverage and helps identify untested or under-tested code.
Measures the percentage of classes that have been instantiated and exercised during testing. This metric is particularly relevant for object-oriented programming languages.
It examines the percentage of decision points (e.g., if statements, case statements) in the code that have been tested, focusing on the decisions made within the application logic.
Evaluates the percentage of loops (for, while, do-while) executed during testing. It ensures all iterations and exit conditions of loops are considered in test scenarios.
Assesses the percentage of entry and exit points in a program that have been tested, ensuring that all possible routes into and out of the application logic are exercised.
Measures the percentage of evaluated combinations of logical conditions during testing, highlighting untested or partially tested compound decisions.
Quantifies the percentage of tested interactions between software components, highlighting potential communication issues.
Frequently Asked Questions
What is a code coverage metric?
What are the different types of code coverage metrics?
How do code coverage metrics improve software quality?
Can having 100% code coverage guarantee a bug-free software?
What tools are commonly used to measure code coverage metrics?
How we write these articles
We have not conducted any studies ourselves. Our article provides a summary of all the statistics and studies available at the time of writing. We are solely presenting a summary, not expressing our own opinion. We have collected all statistics within our internal database. In some cases, we use Artificial Intelligence for formulating the statistics. The articles are updated regularly. See our Editorial Guidelines.