Enhancing Software Quality with Black Box Testing Techniques

In the development process of the software application, the software testing phase plays a vital role in evaluating the quality standards of the software application against the specified requirements. Testing results whether the actual output is expected or not. Also, it helps to determine the quality percentage of the software. In actuality, software testing can be carried out in two ways:

  1.  Manual testing
  2.  Automation testing

In manual testing, the testing of the application is accomplished via human efforts and without using any automation tool. We have different methodologies/types to carry out manual testing. For example – Smoke Testing, Sanity Testing, Regression Testing etc.

On the other hand, automation testing is achieved using different automation tools and frameworks. For example – HP ALM, Selenium Webdriver, QTP etc. As in manual testing, we implement test cases, in the same way in automation testing we implement test scripts using different suitable languages like Java, JavaScript, Python, Ruby etc.

Related read: Step By Step Software Testing Process To Achieve Top Product Quality

In this blog, we are certainly going to explore more about black box testing and its techniques. Let’s first understand the concept of black box testing.

What is Black Box Testing?

Black box testing is one of the manual testing types. The main motive of black box testing is to confirm whether the functionality of the software is working as per the business requirement before delivering it to the end user. In black box testing, the tester is not aware of the internal code structure of the software. To perform black box testing, there is no need to have any prior programming knowledge. It is also known as “Closed box” testing.

Types of black box testing:

  1. Functional testing
  2. Non-Functional testing

Functional Testing and Its Types

In functional testing, the tester follows a structured approach to verify the actual functionality of the application against the requirements.
Below listed are a few types of functional testing:

✅ Smoke testing
✅ Sanity testing
✅Regression testing
✅ Unit testing
✅ Integration testing
✅ System testing
✅ Acceptance testing

Non-Functional Testing Types

In non-functional testing, the software’s behaviour and stability are tested in different conditions. It does not involve functional testing.
Below listed are a few types of non-functional testing:

  • Performance testing
    • Load testing
    • Stress testing
    • Spike testing
    • Volume testing
  • Usability testing
  • Compatibility testing
  • Security testing
  • Scalability testing

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Black Box Testing Techniques

Let’s start with the black box testing techniques and their uses in testing. There are several techniques used in black box testing. The advantages of using these techniques are to lessen the number of test cases using correct test input and also to cover each and every edge case scenario. Black box testing techniques are mostly used in all testing types or levels. Below given are the techniques of black box testing:

1. Equivalence Class Partitioning (ECP):

The word partition itself explains the meaning. For any given set of input ranges, equivalent partitions are created to reduce the test input data. With the selection of random input from the given partition, it can evaluate the result for the entire partition. If a defect is found for a selected partition input, then it is highly possible to have a similar defect for the same partition.

For example – An input range is given as 30 to 40

Here, partitions are created for the given set of input ranges. Instead of testing the whole range value one by one, we can distribute the set of ranges into partitions and can test any random input from the partition and verify the test result.

Equivalence Class Partitioning
Fig. Equivalence Class Partitioning
  • Can test one value from less than 30
  • Can test one value from the valid partition 30 o 40
  • Can test one value above 40

2. Boundary Value Analysis (BVA):

The only difference we can see here is that in ECP, any random input is tested from the partition. But, in BVA mostly the boundary values are tested, as there are higher chances of having defects at boundary regions. There might be a question, what does a boundary value mean? Boundary values are the less than and greater than values for the given input.

In BVA, partitions are made similar to ECP. Let’s learn BVA with an example.

Assume we have a range from 12 to 16 to check the normal haemoglobin range.
For the above example, the boundary values are 11, 12, 13, 15, 16 and 17.

Boundary Value Analysis
Fig. Boundary Value Analysis

3. Error Guessing:

It is also called the “experience-based testing” technique. An experienced tester uses this technique based on his/her past experience to guess the defect-prone areas in the software product. In this technique, there are no specific instructions that are followed to validate the software. Based on the experience of the tester, most critical test cases are written to cover maximum test coverage. The main purpose of this technique is to cover all the generic edge cases of a software product.

Example – If we have a textbox to enter a name, then validate whether it is accepting digits, space, empty values or special characters.

4. Decision Table Testing:

This technique is used to test the product based on a variety of input combinations. The decision table is represented in tabular format, where we have the product input combinations versus the output in the table. Maximum test coverage can be achieved using this technique, as each and every scenario is captured in the table. Verifying the decision table helps the tester identify the missed use case. Also, the tabular format helps to understand the requirements and test cases easily. It is also called the “Cause-Effect Table”, as causes and effects are placed in tabular format.

Let’s learn decision table testing with an example to have a better understanding.
Example – Decision table for login window covering multiple scenarios (conditions).

Decision Table Testing
Fig. Decision Table Testing

Looking at the above table, we can say all the possible test scenarios are covered for the login page.

5. State Transition Testing:

State transition testing is defined as “Testing the system behaviour with positive and negative input values”. Let’s discuss more in depth regarding state transition testing technique.

The word state here determines the current phase of the system, and the transition is defined as the process of changing the state of the system. This technique is used to test the system states and its transition based on a variety of input conditions passed. We can use this technique to test complex systems. The systems that carry multiple states based on the input provided can be tested using the “State transition testing technique”. Test cases can be easily defined with the help of a state transition diagram.

State Transition Testing
Fig. State Transition Testing

Here is an example of a state transition testing technique for unlocking mobile phones.
To unlock your mobile phone using a password, we are provided with a specific number of attempts. For example, let’s say we have 3 attempts to unlock the phone.

The current state of the phone is locked. When we try to unlock, a transition takes place and with the correct password the phone gets unlocked and the home screen is visible, which is another state. When an incorrect password is provided for the first time, it will throw an error message. And, when we cross the limit of the attempts, the phone gets locked for 30 seconds. This is another state.

state transition testing technique for unlocking mobile phones
Fig. State Transition Testing Technique for Unlocking Mobile Phones

With the help of the above diagram, it will be easier to understand the example.

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Conclusion

In conclusion, it is evident that black box testing techniques offer a robust approach to conducting comprehensive end-to-end testing. These techniques not only enable thorough examination of software functionality but also bring efficiency to the testing process by minimizing the volume of test inputs required while maximizing the extent of test coverage. This methodology finds particular relevance in software applications that necessitate testing across a broad spectrum of inputs or conditions, especially those defined within a specific range.

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