Software testing is usually described in two large categories: exploratory testing and automated testing. Exploratory testing is about investigation and discovery. Automated testing is about repeatable verification and regression protection. Both are well established, well documented, and widely practiced.
In real projects, however, the workflow is rarely that clean.
After implementing a new endpoint or modifying existing functionality, teams do not immediately start by building a long-term automated regression suite. First, they try to understand how the system actually behaves. They vary inputs, test boundary conditions, send invalid data, alter payload structures, observe status codes, and look for unstable behavior. Increasingly, this is not done purely manually. Teams use fuzzers, mutation tools, schema-driven generators, and AI-assisted test generation to execute hundreds of variations in minutes.
The purpose of this activity is not regression protection. The generated tests are often temporary and disposable. Their value lies in the information they reveal quickly: weak validation, inconsistent error handling, unexpected 500 responses, protocol inconsistencies, or fragile assumptions in the backend.
