VJC Chapter 17 Data Validation and Verification

VJC/H2Computing/9569 Chapter 17 Data Validation and Verification Contents 1 Data validation and verification 1.1 Types of input error 1.2 Validation of data entry 1.2.1 Check digit 1.2.2 Method of calculating check digits 1.3 Verification of data entry 1.4 Workflow for data validation 2 Program testing 2.1 Syntax errors 2.2 Logical errors 2.3 Runtime errors 2.3.1 Exception Handling 2.4 Test data Annex 1 Datetime Annex 2 Timedelta Annex 3 Regular expression Syllabus Learning Outcomes 2.4 Data Validation and Program Testing Use data validation techniques and design test cases 2.4.1 Explain the difference between data validation and data verification. 2.4.2 Understand data validation techniques such as: – range check – format check – length check – presence check – check digit. 2.4.3 Identify, explain and correct syntax, logic, and runtime errors. 2.4.4 Design appropriate test cases using normal, abnormal and extreme data for testing and debugging programs. 1

VJC/H2Computing/9569 1 Data validation and verification Data integrity, which is the accuracy or validity of data, can never be guaranteed. However, the chances are improved if appropriate measures are taken when data originally enters a system or when it is transmitted from one system to another. 1.1 Types of input error Users keying in data could make transcription errors, a single incorrect character being entered, such as a wrong password or an invalid email address. For eg, a correct postal code 449035 could be wrongly entered as 449036 or the name Stanley might be wrongly entered as Stamley instead. Another type of input error is transposition error , where two digits are accidentally swapped. For eg, a correct NRIC S83123 45 B is wrongly entered as S83123 54 B . 1.2 Validation of data entry Data validation is a process of ensuring that the input data supplied to a system satisfies a set of rules such that it is sensible, complete, and within acceptable boundaries. Its purpose is to avoid data errors. It does not guarantee that data is accurate. For example, if the entry of a name is expected but the wrong name is entered, it will still be recognised as a name and therefore accepted as valid. Data validation techniques include: ● range check – Checks that a value falls within the specified range, e.g. The marks of the A level H2 Computing Paper 1 must fall within the specified range of 0 to