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Description

Coverage.py serves as a powerful utility for assessing the code coverage of Python applications. It tracks the execution of your program, recording which segments of the code have been activated, and subsequently reviews the source to pinpoint areas that could have been executed yet remained inactive. This measurement of coverage is primarily utilized to evaluate the efficacy of testing efforts. It provides insights into which portions of your code are being tested and which are left untested. To collect data, you can use the command `coverage run` to execute your test suite. Regardless of how you typically run your tests, you can incorporate coverage by executing your test runner with the coverage tool. If the command for your test runner begins with "python," simply substitute the initial "python" with "coverage run." To restrict coverage evaluation to only the code within the current directory and to identify files that have not been executed at all, include the source parameter in your coverage command. By default, Coverage.py measures line coverage, but it is also capable of assessing branch coverage. Additionally, it provides information on which specific tests executed particular lines of code, enhancing your understanding of test effectiveness. This comprehensive approach to coverage analysis can significantly improve the quality and reliability of your codebase.

Description

Testing serves to reveal the presence of defects, but it cannot confirm their absence, and the challenge of exhaustive testing escalates quickly, even in relatively simple systems. Key principles for any testing team revolve around thorough testing and efficiency, yet the question remains: how can both be accomplished? How can teams maximize coverage while minimizing the number of tests? Often, teams that scrutinize the actual coverage achieved by their current tests find unexpected and significant coverage gaps. The selection of test cases plays a crucial role; it can mean the difference between (a) running numerous tests that are unlikely to detect issues and fail to boost confidence in the system, and (b) executing a targeted, well-structured set of tests that are more likely to identify the majority of bugs, thereby greatly enhancing the assurance of software quality. Moreover, you will have the capability to create automation scripts and run your tests without needing prior test automation knowledge, which further streamlines the testing process. This approach not only saves time but also ensures that the most critical areas of your software are being thoroughly examined.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS)
C
Codecov
Django
HTML
JSON
MEDITECH Expanse
Mako
Python
SQLite
Sinequa
Tidelift
XML
pytest
pytest-cov

Integrations

Amazon Web Services (AWS)
C
Codecov
Django
HTML
JSON
MEDITECH Expanse
Mako
Python
SQLite
Sinequa
Tidelift
XML
pytest
pytest-cov

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Coverage.py

Country

United States

Website

coverage.readthedocs.io/en/7.0.0/

Vendor Details

Company Name

Encore Software Services

Founded

1998

Country

United States

Website

www.encoress.com/products-solutions/optima/

Product Features

Product Features

Automated Testing

Hierarchical View
Move & Copy
Parameterized Testing
Requirements-Based Testing
Security Testing
Supports Parallel Execution
Test Script Reviews
Unicode Compliance

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