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What is Black Box Testing?
- Test the correctness of the functionality with the help of Inputs and Outputs.
- User doesn’t require the knowledge of software code.
- Black box testing is also called as Functionality Testing.
- Testers make sure that software is working as per the requirements.
It attempts to find errors in the following categories:
- Incorrect or missing functions.
- Interface errors.
- Errors in data structures or external data base access.
- Behavior or performance based errors.
- Initialization or termination errors.
Read – Approaches used in Black Box Testing
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Fault : It is a condition that causes the software to fail to perform its required function.
Error : Refers to difference between Actual Output and Expected output.
Failure : It is the inability of a system or component to perform required function according to its specification.
IEEE Definitions
- Failure: External behavior is incorrect
- Fault: Discrepancy in code that causes a failure.
- Error: Human mistake that caused fault
Note:
- Error is terminology of Developer.
- Bug is terminology of Tester
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Definitions of Software Testing –
- It is the process of Creating, Implementing and Evaluating tests.
- Testing measures software quality
- Testing can find faults. When they are removed, software quality is improved.
- Testing is executing a program with an indent of finding Error/Fault and Failure.
- IEEE Terminology : An examination of the behavior of the program by executing on sample data sets.
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1. To discover defects.
2. To avoid user detecting problems
3. To prove that the software has no faults
4. To learn about the reliability of the software.
5. To avoid being sued by customers
6. To ensure that product works as user expected.
7. To stay in business
8. To detect defects early, which helps in reducing the cost of defect fixing?
Read – Why start testing early?
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What are various ways of calculating defect density?
The formula itself is simple: Density = Total Defects Found / Size
if we see defect density at granular level say Codesize of a particular functionality X in a application Y along with number of files, then we may draw some good observations like –
Taking an example here:- Lets say we have an application ABC, which have three functionality/modules A, B and C.
Code files for A =10 and KLOC=5k
Code files for B =5 and KLOC=1k
Code files for C =1 and KLOC=25k
Bugs found in A=40, B=50, and C=5
Defect density = Total number of defects/LOC (lines of code)
Defect density = Total number of defects/Size of the project
Size of Project can be Function points, feature points, use cases, KLOC etc
Defect Density can be used to:
1) Predict the remaining defects when compared to the expected defect density,
2) Determine if the amount of testing is sufficient.
3) Establish a database of standard defect densities.
What are you going to do with the defect density information you collect?Depending on what you want / expect to discover, you could pilot some different measurements on different parts of the code base and see which versions of the metric were most measurable.
Must Read: Use of Relative Code Churn Measures to Predict System Defect Density.
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