Orthogonal Array Testing in Software Engineering | Orthogonal Array Testing Example

Welcome to this post on Orthogonal Array Testing in software engineering. Orthogonal array testing is black box testing. When you have a large number of input combinations, orthogonal array testing gives very few test cases. View the below tutorial or read on...

What is Orthogonal Array? It is a table. The columns (a.k.a. factors) represent the independent variables. The rows (a.k.a. experiments or runs) represent the variables' combinations. The orthogonal array testing example below is for a web page with three sections - TOP, LEFT and RIGHT. Note that the orthogonal array has only 4 test cases to run for 8 input combinations.

What is Orthogonal Array Testing? The Orthogonal Array Technique has the following steps:

1. Identify the independent variables. Put them as column headers in the table.
   
2. For each independent variable, identify the number of possible values.
3. Search an Orthogonal Array with the smallest number of rows in orthogonal array design of experiments. I have explained this step here.
   
4. Put the independent variable values in the Orthogonal Array cells. If any cells are still blank, repeat the values in them.
5. Test each row in the table.
   

In the example below, there are 3 independent variables (put as column headers). Variable A has 2 possible values, A1 and A2. Variable B has 3 possible values, B1, B2 and B3. Variable C has 3 possible values, C1, C2 and C3. The input combinations are therefore 2 * 3 * 3, which is 18. The smallest number of rows can be found in this orthogonal array. Using the above orthogonal array technique, the table should look like below. Instead of testing 18 input combinations, orthogonal array gives only 9 test cases to run.

Note: 1) Since variable A has only 2 values, they are used to complete the first column.
2) Since there are only 3 variables, the 4th column is not used.

Want to learn the above Orthogonal Array Testing examples in detail? Please view my Orthogonal Array Testing tutorial. 

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Mutation Testing in Software Testing | Mutation Analysis | White Box Testing

After being occupied with some commitments for about two months, I finally got time to write the next article 😊. This post is on Mutation Testing, a white box testing, to test program code. Mutation testing is also useful for test automation code, databases, software models and other artifacts in software engineering. View the below tutorial or read on...

What is Mutation Testing in software testing? Basically, in Mutation Testing, you make a change (a mutation) to your program and run your tests with test data. Mutation Testing finds if your existing tests and test data are useful or not. Using Mutation Testing, you could know which sections of your program are tested poorly. Also, you could identify your tests that never find any mutants (changed copies of your program). In the example below, the program on the left is the original program and the program on the right is it's mutant.

Mutation Testing process (Mutation Analysis)

1) You test your original program with all your tests and test data. If any test fails, you need to fix your program or that test or it's test data. 

2) Once your program passes all the tests, you create mutants by using any mutation operator (e.g delete a statement, duplicate a statement, exchange operators etc.) and test your mutants. Each test run on any mutant should ideally fail, because a mutant is a changed copy of your program. 

3) If a test run on any mutant passes, you should find out the reason (e.g. the mutated code is not run or the mutant is functionally "equivalent" to your program). In order to find more mutants, you need to update your existing tests (or test data) and/ or write new tests (with test data). Also, if you update your test set or test data, you need to repeat the above process from step 1).

Want to learn Mutation Testing more? Like Mutation Analysis in detail, Mutation Score and Mutation Testing assumptions? Then, please view the complete Mutation Testing tutorial. Thank you.

Data Flow Testing in Software Testing | White Box Testing

This post is on Data Flow Testing. What is data flow testing? Data flow testing in software testing is white box testing. Data flow testing is also a structured testing methodology, based on your program's internal structure. Data flow testing focuses on variables' definition and use. A variable is a memory location that can store a value. A variable's value can be used in a condition or a calculation. Now, in a program, it is possible for the developer to use a variable that doesn't exist or update a variable's value by error. In data flow testing, you examine the variables in your program. View my Data Flow Testing tutorial for more details or read on.

Data flow testing strategies in software testing include:

1) Define Use Testing - DU Testing has some rules and metrics. It tests the paths of the Control Flow Graph (view my Path Testing tutorial to learn about Control Flow Graph) that have a variable defined or used.

2) Program Slices - Program slices strategy divides the program into executable sections, for a variable. You could then test a single program slice independently, for that variable.

Let us see the data flow testing example. This example program computes the Sum of some numbers. Here is the Control Flow Graph when the variable n gets a value of 0 (in Node 4).

If the variable n has a non-zero value, a different path is taken in the Control Flow Graph. The reason is that the while loop is also run. Here is the Control Flow Graph when the variable n gets a value of say, 100, the first time (in Node 4) and 0 the second time (in Node 8).

Let us now learn about Define Use Testing. A particular node in the Control Flow Graph can be either a Define Node or Use Node. A variable is given a value in a Define Node. Examples of Define Nodes are Node 2 (the variable i is given a value), Node 3 (the variable sum is given a value), Node 4 (the variable n is given a value) or Node 8 (again, the variable n is given a value). A variable's value is used in a Use Node. Examples of Use Nodes are Node 6 (the value of variable sum is used; also the value of variable n is used) or Node 7 (the value of variable i is used in the computation) or Node 10 (the value of variable i is used; also the value of variable sum is used in the print statement). Learn about P-use (Predicate Use) and C-use (Computation Use) here. In Define Use Testing, you should identify the Define Use nodes for each variable. I have explained how to find the Define nodes and Use nodes for variables i, n and sum here. In Define Use Testing, you should identify some paths according to your chosen Define Use Testing Metrics and test those paths to find bugs.

 

Moving on to Program Slices. This data flow testing strategy is useful when your program is large in size. You could identify a program slice (a set of statements) for a single variable, up to any statement in your program. I have explained how to identify program slices for variables i, n and sum here.

Using both Define Use Testing and Program Slices data flow testing techniques, here are four Define Use Paths (pink table below) to test for variable n. In Data Flow Testing, you could test these paths. Similarly, you could identify the paths to test for variable i and variable sum and test them too.

Want to learn Data Flow Testing in detail? Learn Data Flow Testing Metrics? Then please view the complete Data Flow Testing with Example Tutorial. Thank you.

Path Testing in Software Testing with Example | Triangle Problem

This post explains Path Testing in software testing. Path testing is one of the test design techniques. Path testing is a structured testing methodology, meaning it is based on mathematics. Path testing is white box testing and complementary to other software testing methodologies like requirements based testing. View my Path Testing tutorial to understand path testing. Then read on.

 

In order to use path testing techniques, you should know about the Control Flow Graph, which represents the program or the algorithm to be tested. Here is the Control Flow Graph for the Triangle Problem example below. In this Control Flow Graph, 1 is the Entry Node and 10 is the Exit node. The nodes 1 through 10 represent the Steps below. The directional arrows e.g. Node 1 to Node 2 represent the control flow between the Steps. The directional arrows are called Edges. Using the Control Flow Graph, you can compute the Cyclomatic Complexity, which is E - N + 2, where E is the number of Edges and N is the number of Nodes. In this Control Flow Graph example, Cyclomatic Complexity is 12 - 10 + 2 = 4.

 

The Triangle Problem is to find out the type of the triangle, given its' three sides. Here is the algorithm for the Triangle Problem.

 

In path testing for triangle problem, there are four basis (independent) paths of algorithm execution, which you need to test with test data.

• Not a Triangle: Node1 > Node2 > Node3 > Node10
• Equilateral Triangle: Node1 > Node2 > Node4 > Node5 > Node10
• Isosceles Triangle: Node1 > Node2 > Node4 > Node6 > Node7 > Node10
• Scalene Triangle: Node1 > Node2 > Node4 > Node6 > Node8 > Node9 > Node10
  

Want to learn Path testing with example explained in detail? Want to learn the Path Testing process? Then, please view my Path Testing in Software Testing tutorial. Thank you.

SQL Queries Tutorial | Sql Query tutorial for Beginners with Examples

This is my first post of the year 😀. As I mentioned in my SQL Queries Tutorial and Sql Query tutorial for beginners with examples, the SQL queries that you can use for practice are below.

 

SQL Queries (these SQL queries in DBMS are explained in the above SQL Tutorial for Beginners):

 

1) [SQL for beginners] Get all fields of all records from the Customers table.
select * from Customers

2) [SQL for beginners] Select only the named fields from the Customers table.
select CustomerID, CustomerName, Country from Customers

3) [SQL for beginners] Select only 5 records and only the given fields from the Customers table.
select top 5 CustomerID, CustomerName, Country from Customers

4) [SQL for beginners] Select only the given fields from all records which match the given condition in the Customers table.

select  CustomerID, CustomerName, Country from Customers where Country = 'USA'
5) [SQL for beginners] Select all fields of all records from the Employees table.
select * from Employees

6) Select all records from the Employees table ordered by FirstName field.
select * from Employees order by FirstName

7) Select all records from the Employees table ordered by FirstName field in descending order.
select * from Employees order by FirstName desc
8) Select OrderID field with alias ID, CustomerID field with alias Customer and so on from the Orders table.
select OrderID as ID, CustomerID as Customer, OrderDate as [Date] from Orders

9) [SQL Joins] Select with Inner Join of Orders table with Customers table.
select Orders.OrderID, Customers.CustomerName, Customers.Country
from Orders inner join Customers on Orders.CustomerID = Customers.CustomerID
10) Select those Employees whose EmployeeID does not appear in the Orders table.
select * from Employees where EmployeeID not in (select EmployeeID from Orders)

11) [SQL Joins] Select with Left Join of Employees table with Orders table.
select Employees.FirstName, Employees.LastName, Orders.OrderID
from Employees left join Orders on Employees.EmployeeID =Orders.EmployeeID
order by Employees.FirstName, Employees.LastName
12) [SQL Joins] Select with Right Join of Orders table with Employees table.
select Employees.FirstName, Employees.LastName, Orders.OrderID
from Orders right join Employees
on Employees.EmployeeID =Orders.EmployeeID
order by Employees.FirstName, Employees.LastName
13) [SQL Joins] Select pairs of products with the same price using Self Join of Products table.
select P1.ProductID as ID1, P1.ProductName as Name1, P1.Price as Price1, P2.ProductID as ID2, P2.ProductName as Name2, P2.Price as Price2
from Products P1 inner join Products P2 on P1.Price = P2.Price and P1.ProductID <> P2.ProductID
14) [SQL queries examples] Using Union, select Country field values from the Customers table and Suppliers table.

select Country from Customers union select Country from Suppliers

15) [SQL queries examples] Using Union All, select Country field values including duplicates from the Customers table and Suppliers table.
select Country from Customers union all select Country from Suppliers
16) Using Group By, count the total number of suppliers per country from the Suppliers table.
select count(SupplierID) as TotalSuppliers, Country
from Suppliers group by Country
17) Using Group By, count the total number of products per price point from the Products table.
select count(ProductID) as ProductsNumber, Price
from Products group by Price order by Price
18) Using the above SQL query, select only those price points that have more than one product.
select count(ProductID) as ProductsNumber, Price
from Products group by Price having count(ProductID)>1 order by Price
19) Using a sub query, select those customers who have ordered any quantity more than 90 units.
select CustomerID, CustomerName from Customers 

where CustomerID = any (select Orders.CustomerID from Orders inner join OrderDetails on Orders.OrderID = OrderDetails.OrderID  where OrderDetails.Quantity > 90)

You can practice the above SQL Queries on W3Schools website.