What is Black Box in Computer?

A “black box” is a system, device, or process that can be viewed in terms of its inputs and outputs without any knowledge of its internal workings. The term is used in various fields, including engineering, computing, and aviation, to describe a system that is understood through its functional behavior rather than its implementation details.

In computer science and software engineering, the term “black box” is used in various contexts. Here are the primary uses and explanations:

1. Black Box Testing:-
Black box testing is a software testing method where the tester focuses on the inputs and outputs of the software without considering its internal workings. The goal is to check whether the software meets its functional requirements.

Characteristics:

Inputs are fed into the system.
Outputs are tested to see if they match the expected results.
The internal code, architecture, or programming structure is not examined.
Example:

When testing a login form, different usernames and passwords are entered, and the results (success or failure of login) are observed.
2. Black Box Models:
This refers to systems or software components whose internal workings are unknown to the users or developers. Only the relationship between inputs and outputs is known.

Characteristics:

The internal processes are unknown.
The focus is on the input and output behavior.
Example:

An AI model that produces results based on complex calculations but whose internal decision-making process is opaque to the users.
3. Devices and Components:
Sometimes, computer hardware or software components are referred to as “black boxes” if they are complex and difficult for users to understand.

Example:
A computer’s GPU (Graphics Processing Unit) handles complex calculations and can be considered a black box to users, as its internal workings are complicated.
Conclusion:
In computer science, a “black box” refers to a system or device whose internal workings are unknown or irrelevant to the user. Instead, the focus is on the external behavior (inputs and outputs). The main purpose is to concentrate on the system’s functionality without needing to understand its internal structure.