Black-box testing

Black-box testing is a software testing method where the internal structure, design, and implementation of the item being tested are not known to the tester. It involves interacting with the software's interface by providing inputs and examining outputs without considering the internal code structure, kind of like interacting with one of Elon's Teslas - you don't need to know how the self-driving algorithms work, just whether the car gets you from A to B without crashing.

How to use it in a sentence

  • In the standup meeting, Jessica mentioned she'll be doing some black-box testing on the new API endpoints today, poking and prodding them like a kid in a candy store, seeing what breaks.

  • The QA team argued that black-box testing isn't enough for the new microservices architecture, insisting on additional integration and chaos testing to ensure the system doesn't collapse like a house of cards during peak traffic.

If you actually want to learn more...

  • Specification By Example - This article discusses how black-box testing can be used to create executable specifications, ensuring the software meets business requirements.

  • Exploratory Testing - Exploratory testing is a type of black-box testing that emphasizes the freedom and creativity of the tester to identify quality issues that automated tests might miss.

  • The Practical Test Pyramid - This article revisits the Test Pyramid concept, which includes black-box testing techniques, and provides practical examples for creating a balanced test portfolio.

Note: the Developer Dictionary is in Beta. Please direct feedback to skye@statsig.com.

Join the #1 experimentation community

Connect with like-minded product leaders, data scientists, and engineers to share the latest in product experimentation.

Try Statsig Today

Get started for free. Add your whole team!

What builders love about us

OpenAI OpenAI
Brex Brex
Notion Notion
SoundCloud SoundCloud
Ancestry Ancestry
At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities.
OpenAI
Dave Cummings
Engineering Manager, ChatGPT
Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly.
Brex
Karandeep Anand
President
At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It’s also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us.
Notion
Mengying Li
Data Science Manager
We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion.
SoundCloud
Don Browning
SVP, Data & Platform Engineering
We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig.
Ancestry
Partha Sarathi
Director of Engineering
We use cookies to ensure you get the best experience on our website.
Privacy Policy