Why is boundary condition testing important?

Boundary conditions are where logic errors most frequently occur. Testing limits like Integer.MAX_VALUE, empty collections, or null strings ensures your application handles unexpected states gracefully.

What frameworks does this skill support?

This skill is specifically designed for modern Java development using JUnit 5 (Jupiter), JUnit 5 Parameterized Tests, and the AssertJ assertion library.

Can I use this for testing collections?

Absolutely. It provides patterns for testing empty collections, single-element collections, large datasets, and collections containing null values.

Does this skill help with floating point errors?

Yes, it includes specific patterns for AssertJ's isCloseTo and within methods to handle floating-point precision issues and special values like NaN or Infinity.

Does it support parameterized testing?

Yes, it leverages @ParameterizedTest and @ValueSource to help you test multiple boundary values efficiently without writing redundant test methods.

JUnit 5 Boundary Testing

Name: JUnit 5 Boundary Testing
Author: pur3v4d3r

bypur3v4d3r

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安全与测试

Implements systematic edge case and boundary condition testing patterns for Java applications using JUnit 5.

关于

This skill empowers developers to build more resilient Java applications by providing standardized patterns for identifying and testing critical edge cases. It offers implementation guides for testing numeric limits, string variations, collection boundaries, and complex date/time scenarios. By utilizing JUnit 5's parameterized testing features and AssertJ's fluid assertions, it ensures that your code remains stable at its operational limits, significantly reducing the risk of runtime exceptions, overflows, and logic errors in production environments.

主要功能

String boundary validation for null, empty, and whitespace inputs
High-precision floating-point comparison and special value templates
1 GitHub stars
Standardized numeric overflow and underflow testing patterns
Exhaustive collection testing for empty, single-item, and large states
Comprehensive date, time, and leap year edge case scenarios

使用场景

Improving test suite reliability through systematic edge case coverage
Hardening APIs against malformed or extreme input values
Verifying business logic accuracy at numerical and date limits

关于

主要功能

String boundary validation for null, empty, and whitespace inputs
High-precision floating-point comparison and special value templates
1 GitHub stars
Standardized numeric overflow and underflow testing patterns
Exhaustive collection testing for empty, single-item, and large states
Comprehensive date, time, and leap year edge case scenarios

使用场景

Improving test suite reliability through systematic edge case coverage
Hardening APIs against malformed or extreme input values
Verifying business logic accuracy at numerical and date limits