- Software testers have to identify every distinct route through API labyrinths.
The first challenge of API testing is identifying different routes that data can flow through complex chains of API calls. You’ll then need to identify which routes to traverse in testing. Also, the selection process must retain test coverage.
- Expected results are hard to define.
When you’re trying to formulate expected results manually, it destabilizes the reliability of API testing. Testers have to second guess how APIs should respond to many possible requests. In many cases, testers just run a test and make their best guess as to whether it’s passed. There’s no way to know confidently whether the right API test result was achieved.
- Test data compromises API testing speed and rigor.
You must also source the data combinations for your API tests. Many combinations are needed for adequate coverage, but they can’t usually be found in existing data sources. As a result, test data often undermines the agility and rigor of API testing.
- Manually formulated test are too slow for the typical level of API complexity.
You have to hand crank data for your tests when they use data drawn from production. This manual process is too slow to create API tests of sufficient coverage because of the many possible routes through API chains that can be tested.
- Environmental constraints compromise API testing rigor, reliability and speed.
APIs interact with many different components and you need access to each, whether in-house or third-party systems, to fire off requests and check responses. Components are frequently constrained or unavailable, which leads to API testing bottlenecks.
- Versioning exacerbates the challenges of manual API test design, test data bottlenecks, and environmental constraints.
Rigorous API testing has to test against multiple versions of a request. As APIs change, connected applications continue to send old versions of a given request. You have to test against these versions, adjusting their tests, data and environments. However, they lack automated version control, leading to significant and wasteful duplicate effort.