Study Notes
Testing is a crucial part of the development lifecycle, requiring a structured approach to identify valid and invalid inputs and their outputs. Test Data can be categorized into four groups: normal, abnormal, extreme, and boundary data.
- Normal Data — data that falls within the expected range of input values.
Example: 78, 59 - Abnormal Data — data that is incorrect or unexpected.
Example: 100000, "twenty" - Extreme Data — data at the upper or lower limits of the expected range.
Example: 100, 0 - Boundary Data — data at the edge of the acceptable range, including just outside it.
Example: 101, -1, 0, 100 - Trace Tables — tables used to perform a dry-run of an algorithm, recording outputs and variable values at each stage.
Example: Used to identify errors in a flowchart or pseudocode
Exam Tips
Key Definitions to Remember
- Normal Data: Data within the expected range
- Abnormal Data: Incorrect or unexpected data
- Extreme Data: Data at the limits of the expected range
- Boundary Data: Data at the edge of the acceptable range
- Trace Tables: Tables used to track variable values and outputs during a dry-run
Common Confusions
- Confusing boundary data with extreme data
- Misunderstanding the purpose of trace tables
Typical Exam Questions
- What is normal data? Data within the expected range of input values.
- How can trace tables help in testing? They help identify errors by showing variable values and outputs at each stage.
- What is the difference between abnormal and boundary data? Abnormal data is incorrect or unexpected, while boundary data is at the edge of the acceptable range.
What Examiners Usually Test
- Understanding of different types of test data
- Ability to use trace tables to identify errors