Author Archives: RickDjouwe1

Understanding Pairwise and Combinatorial Testing

Hello everyone, and welcome back to my weekly blog post! This week, we’re diving into an essential software testing technique: Pairwise and Combinatorial Testing. These methods help testers create effective test cases without needing to check every single possible combination of inputs. Similar to most of the test cases selection methods we’ve learned.

To make things more relatable, let’s start with a real-life example from the insurance industry.

A Real-Life Problem: Insurance Policy Testing

Imagine you are working for an insurance company that sells car insurance. Customers can choose different policy options based on:

  1. Car Type: Sedan, SUV, Truck
  2. Driver’s Age: Under 25, 25–50, Over 50
  3. Coverage Type: Basic, Standard, Premium

If we tested every possible combination, we would have:

3 × 3 × 3 = 27 test cases!

This is just for three factors. If we add more, such as driving history, location, or accident records, the number of test cases grows exponentially, making full testing impossible.

So how can we test efficiently while ensuring that all critical scenarios are covered?
That’s where Pairwise and Combinatorial Testing come in!

What is Combinatorial Testing?

Combinatorial Testing is a technique that selects test cases based on different input combinations. Instead of testing all possible inputs, it chooses a smaller set that still covers key interactions between variables.

Example: Combinatorial Testing for Insurance Policies

Instead of testing all 27 cases, we can use combinatorial testing to reduce the number of test cases while still covering important interactions.

A possible set of test cases could be:

Test Case Car Type Driver’s Age Coverage Type
1 Sedan Under 25 Basic
2 SUV 25–50 Standard
3 Truck Over 50 Premium
4 Sedan 25–50 Premium
5 SUV Over 50 Basic
6 Truck Under 25 Standard

This method reduces the number of test cases while ensuring that each factor appears in multiple meaningful combinations.

What is Pairwise Testing?

Pairwise Testing is a type of combinatorial testing where all possible pairs of input values are tested at least once. Research has shown that most defects in software are caused by the interaction of just two variables, so testing all pairs ensures good coverage with fewer test cases.

Example: Pairwise Testing for Insurance Policies

Instead of testing all combinations, we can create a smaller set where every pair of values appears at least once:

Test Case Car Type Driver’s Age Coverage Type
1 Sedan Under 25 Basic
2 Sedan 25–50 Standard
3 SUV Under 25 Premium
4 SUV Over 50 Basic
5 Truck 25–50 Premium
6 Truck Over 50 Standard

Here, every pair (Car Type, Driver’s Age), (Car Type, Coverage Type), and (Driver’s Age, Coverage Type) appears at least once. This means we cover all important interactions with just 6 test cases instead of 27!

Permutations and Combinations in Testing

To understand combinatorial testing better, we need to understand permutations and combinations. These are ways of arranging or selecting elements from a set.

What is a Combination?

A combination is a selection of elements where order does not matter. The formula for combinations is: C(n, r) = n! / [r! * (n – r)!]

where:

  • n is the total number of items
  • r is the number of selected items
  • ! (factorial) means multiplying all numbers down to 1

Example of Combination in Insurance

If an insurance company wants to offer 3 different discounts from a list of 5 available discounts, the number of ways to choose these discounts is: C(5,3)=5!3!(5−3)!

So, there are 10 different ways to choose 3 discounts.

What is a Permutation?

A permutation is an arrangement of elements where order matters. The formula for permutations is: P(n, r) = n! / (n – r)!

where:

  • n is the total number of items
  • r is the number of selected items

Example of Permutation in Insurance

If an insurance company wants to assign 3 priority levels (High, Medium, Low) to 5 claims, the number of ways to arrange these claims is: P(5,3)=5!(5−3)!

So, there are 60 different ways to assign priority levels to 3 claims.

Why Use Pairwise and Combinatorial Testing?

  1. Saves Time and Effort – Testing fewer cases while maintaining coverage.
  2. Covers Critical Scenarios – Ensures every important combination is tested.
  3. Finds Defects Faster – Most bugs are caused by two interacting factors, so pairwise testing helps detect them efficiently.
  4. Reduces Costs – Fewer test cases mean lower testing costs and faster releases.

When Should You Use These Techniques?

  • When a system has many input variables
  • When full exhaustive testing is impractical
  • When you need to find bugs quickly with limited resources
  • When testing insurance, finance, healthcare, and other complex systems

Tools for Pairwise and Combinatorial Testing

To make the process easier, you can use tools like:

  • PICT (Pairwise Independent Combinatorial Testing Tool) – Free from Microsoft
  • Hexawise – A combinatorial test design tool
  • ACTS (Automated Combinatorial Testing for Software) – Developed by NIST

These tools help generate optimized test cases automatically based on pairwise and combinatorial principles.

Conclusion

Pairwise and Combinatorial Testing are powerful techniques that allow testers to find defects efficiently without having to test every possible combination. They save time, reduce costs, and improve software quality.

Next time you’re dealing with multiple input variables, try using Pairwise or Combinatorial Testing to make your testing smarter and more effective!

From the blog Rick’s Software Journal by RickDjouwe1 and used with permission of the author. All other rights reserved by the author.

Mastering Software Quality: Path Testing and Decision-Based Testing in Real-World Applications

Introduction (GREAT NEWS!!!!)

Hello everyone, I apologize for the delay in posting this week’s blog. I’ve been balancing a lot lately, but I’m excited to share some great news with you. I recently secured a summer internship at Hanover Insurance Group as an automation developer, and I couldn’t be more thrilled! As I dive into this amazing opportunity, I want most of my projects to focus on solving, exploring, or even just addressing challenges within the insurance industry. That’s why this week’s post on Path Testing and Decision-Based Testing will highlight real-world applications in insurance software. Let’s jump in!

How Proven Testing Techniques Ensure Reliability in Insurance Software Systems

In the insurance industry, software systems play a critical role in managing claims, processing policies, and ensuring compliance. Given the complexity of insurance workflows, robust testing is essential to avoid costly errors and enhance customer satisfaction. Two effective testing methods: Path Testing and Decision-Based Testing, are invaluable in achieving high-quality software. Let’s explore these techniques with simple examples and see how they apply to real-world insurance applications.

What is Path Testing?

Ensuring Every Route in the Code is Tested

Path Testing involves checking all possible execution paths within a program to ensure each one functions as expected. This technique is particularly useful in complex systems where different inputs and scenarios lead to various execution routes.

Example:
Consider an insurance claims processing system where a claim can go through multiple steps:

  1. Eligibility Check: Is the policy active?
  2. Coverage Validation: Does the claim fall under covered incidents?
  3. Fraud Check: Are there any red flags?
  4. Approval Process: Does the claim meet all criteria for approval?

Path Testing would generate test cases to ensure every possible scenario is covered, such as:

  • Active policy, valid coverage, no fraud, claim approved (Success)
  • Inactive policy (Failure)
  • Valid policy but uncovered incident (Failure)
  • Fraud detected (Failure)

What is Decision-Based Testing?

Validating Every Decision Made by the Software

Decision-Based Testing (also known as Branch Testing) focuses on testing each decision point in the code, such as conditional statements and logic branches.

Example:
In the same insurance claims system, the decision to approve or deny a claim might depend on multiple conditions:

 ClaimCheck(isPolicyActive) {
    if (isCoveredIncident) {
        if (!isFraudulent) {
            System.out.println("Claim Approved");
        } else {
            System.out.println("Claim Denied: Fraud Detected");
        }
    } else {
        System.out.println("Claim Denied: Uncovered Incident");
    }
} else {
    System.out.println("Claim Denied: Inactive Policy");
}

Decision-Based Testing would create test cases to cover all possible outcomes:

  • Active policy, covered incident, no fraud (Approved)
  • Active policy, covered incident, fraud detected (Denied)
  • Active policy, uncovered incident (Denied)
  • Inactive policy (Denied)

Real-World Application: Insurance Claims Processing Systems

Why Insurance Software?
Insurance software involves complex business rules and multiple decision points. Errors in these systems can lead to mismanagement of claims, financial losses, or regulatory issues.

How Are These Testing Techniques Used?

  1. Path Testing: Ensures that all possible claim processing scenarios are thoroughly tested, including edge cases like expired policies or unusual claim amounts.
  2. Decision-Based Testing: Validates that all critical decisions, such as fraud detection or policy eligibility, are handled accurately by the system.

Example Scenario:
An insurance company uses a claims management system that automatically processes thousands of claims daily. Path Testing would ensure that every possible claim scenario is tested, while Decision-Based Testing would verify that all decision points, such as flagging a claim for manual review, function correctly.

Key Differences Between Path Testing and Decision-Based Testing

Aspect Path Testing Decision-Based Testing
Focus All possible execution paths Each decision point (branches)
Best For Complex insurance workflows Policy validation and claim decisions
Example Application Claims processing systems Fraud detection and approvals

Conclusion: Delivering Reliable Insurance Software with Strategic Testing

For software engineers working in the insurance industry, combining Path Testing and Decision-Based Testing is crucial. These techniques ensure the software is well-equipped to handle every possible scenario and make accurate decisions in policy and claims management. By implementing these robust testing strategies, insurance companies can boost efficiency, reduce errors, and maintain compliance with regulatory standards.

For further exploration, consider:

Software-testing-laboon-ebook

From the blog Rick’s Software Journal by RickDjouwe1 and used with permission of the author. All other rights reserved by the author.

The Intersection of Manual Testing, Automated Testing, Equivalence Class Testing, and Security Testing

Hello guys, welcome to my second blog. In my previous blog, I explored JUnit testing, focusing on boundary value analysis and how to use assert Throws for exception handling in Java. Those concepts helped us understand how to write robust test cases and ensure that our software behaves correctly at its limits.

Building on that foundation, this post expands into a broader discussion of manual vs. automated testing, equivalence class testing, and security testing. These methodologies work together to create a comprehensive testing strategy that ensures software is functional, efficient, and secure.

Introduction

Software testing is a critical part of the software development lifecycle (SDLC). Among the various testing methodologies, manual testing, automated testing, equivalence class testing, and security testing play vital roles in ensuring software reliability, performance, and security. This article explores these techniques, their strengths, and how they work together.

Manual vs. Automated Testing

Testing software can be broadly categorized into manual testing and automated testing. Each approach serves specific purposes and has its advantages.

Manual Testing

Manual testing involves human testers executing test cases without automation tools. It is useful for exploratory testing, usability testing, and cases requiring human judgment.

Pros:

  • Suitable for UI/UX testing and exploratory testing
  • Requires no programming skills
  • Provides a human perspective on software quality

Cons:

  • Time-consuming and repetitive
  • Prone to human errors
  • Inefficient for large-scale projects

Automated Testing

Automated testing uses scripts and testing frameworks to execute test cases automatically. It is ideal for regression testing and performance testing.

Pros:

  • Faster execution and scalable for large projects
  • Reduces human errors
  • Works well with continuous integration/continuous deployment (CI/CD)

Cons:

  • High initial setup cost
  • Requires programming expertise
  • Not suitable for exploratory testing

Example: Java Automated Test Using Selenium

Here is a basic example of using Java to automate a test: I have a simple Calculator class and an Add method. There is a test that runs without human intervention once executed

public class Calculator {
    public int add(int a, int b) {
        return a + b;
    }
}


import static org.junit.jupiter.api.Assertions.assertEquals;
import org.junit.jupiter.api.Test;

public class CalculatorTest {
    @Test
    public void testAddition() {
        Calculator calculator = new Calculator();
        int result = calculator.add(2, 3);
        assertEquals(5, result); 
    }
}

Equivalence Class Testing

Equivalence Class Testing (ECT) is a black-box testing technique that reduces the number of test cases while ensuring comprehensive test coverage. It divides input data into equivalence classes, where each class represents similar expected outcomes.

How It Works:

  • Identify input conditions
  • Categorize inputs into equivalence classes (valid and invalid)
  • Select one representative input from each class for testing

Example: Equivalence Class Testing in Java

Consider a function that validates age input:

public class AgeValidator {
    public static String validateAge(int age) {
        if (age >= 18 && age <= 60) {
            return "Valid Age";
        } else {
            return "Invalid Age";
        }
    }

    public static void main(String[] args) {
        System.out.println(validateAge(25)); // Valid input class
        System.out.println(validateAge(17)); // Invalid input class
        System.out.println(validateAge(61)); // Invalid input class
    }
}

Security Testing: A Critical Component

Security testing ensures that applications are protected against cyber threats. This is increasingly crucial with rising cyberattacks and data breaches.

Key Security Testing Techniques:

  • Penetration Testing: Simulating cyberattacks to identify vulnerabilities.
  • Static Code Analysis: Reviewing source code for potential security flaws.
  • Dynamic Analysis: Testing a running application for security weaknesses.
  • Fuzz Testing: Inputting random data to identify unexpected behavior.

Example: Basic SQL Injection Test

A common security vulnerability is SQL Injection. Here’s an example of a vulnerable and a secure implementation:

Vulnerable Code:

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.Statement;

public class SQLInjectionVulnerable {
    public static void getUserData(String userId) {
        try {
            Connection conn = DriverManager.getConnection("jdbc:mysql://localhost:3306/mydb", "user", "password");
            Statement stmt = conn.createStatement();
            String query = "SELECT * FROM users WHERE id = " + userId; // Vulnerable to SQL Injection
            ResultSet rs = stmt.executeQuery(query);
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

Secure Code:

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.PreparedStatement;
import java.sql.ResultSet;

public class SQLInjectionSecure {
    public static void getUserData(String userId) {
        try {
            Connection conn = DriverManager.getConnection("jdbc:mysql://localhost:3306/mydb", "user", "password");
            String query = "SELECT * FROM users WHERE id = ?";
            PreparedStatement pstmt = conn.prepareStatement(query);
            pstmt.setString(1, userId);
            ResultSet rs = pstmt.executeQuery();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

How These Testing Methods Work Together

Each testing approach contributes uniquely to software quality:

  • Manual and automated testing ensure functional correctness and usability.
  • Equivalence class testing optimizes test case selection.
  • Security testing safeguards applications from threats.

By integrating these methods, development teams can achieve efficiency, reliability, and security in their software products.

Conclusion

A strong testing strategy incorporates manual testing, automated testing, equivalence class testing, and security testing. Leveraging these approaches ensures robust software quality while improving development efficiency.

For further exploration, consider:

From the blog Rick’s Software Journal by RickDjouwe1 and used with permission of the author. All other rights reserved by the author.

Effective Exception Testing in JUnit 5: Boundary Value Testing and AssertThrows

Introduction

In modern software development, ensuring that a program handles exceptions correctly is crucial for building robust applications. Exception testing in JUnit 5 allows developers to verify that their code properly handles error scenarios, improving reliability and maintainability. This blog post explores key techniques such as Testing for Exceptions in JUnit 5, Boundary Value Testing, and using AssertThrows to create effective test cases.

Testing for Exceptions in JUnit 5

JUnit 5 provides a streamlined way to test exceptions in Java applications. Unlike JUnit 4, which required using the expected attribute or @Rule, JUnit 5 introduces Assertions.assertThrows(), offering a more flexible and readable approach.

Example of Exception Testing in JUnit 5

Consider a method that calculates the square root of a number. If a negative number is provided, it should throw an IllegalArgumentException.

import static org.junit.jupiter.api.Assertions.*;
import org.junit.jupiter.api.Test;

class MathUtilsTest {

    double calculateSquareRoot(double number) {
        if (number < 0) {
            throw new IllegalArgumentException("Number must be non-negative");
        }
        return Math.sqrt(number);
    }

    @Test
    void testCalculateSquareRootException() {
        IllegalArgumentException exception = assertThrows(IllegalArgumentException.class, () -> {
            calculateSquareRoot(-5);
        });
        assertEquals("Number must be non-negative", exception.getMessage());
    }
}

This test verifies that the method correctly throws an exception when given invalid input, ensuring robustness.

Boundary Value Testing

Boundary Value Testing (BVT) is a technique used to test the limits of input values. It focuses on edge cases, such as minimum and maximum values, where software is most likely to fail.

Example: Boundary Testing for Age Validation

Consider a function that validates a user’s age for registration, allowing only ages between 18 and 65.

boolean isValidAge(int age) {
    return age >= 18 && age <= 65;
}

Boundary tests should check values just inside and just outside the valid range:

import static org.junit.jupiter.api.Assertions.*;
import org.junit.jupiter.api.Test;

class AgeValidatorTest {
    
    @Test
    void testAgeBoundaries() {
        assertTrue(isValidAge(18)); 
        assertTrue(isValidAge(65));  
        assertFalse(isValidAge(17)); 
        assertFalse(isValidAge(66)); 
    }
}

BVT ensures the system correctly distinguishes between valid and invalid inputs.

Testing for Exceptions with AssertThrows

The assertThrows method in JUnit 5 simplifies exception testing, making tests more readable and maintainable. It helps validate that methods correctly handle invalid inputs by throwing the expected exceptions.

Example: Division by Zero Handling

Consider a simple method that performs division:

int divide(int dividend, int divisor) {
    if (divisor == 0) {
        throw new ArithmeticException("Cannot divide by zero");
    }
    return dividend / divisor;
}

We can use assertThrows to verify proper exception handling:

import static org.junit.jupiter.api.Assertions.*;
import org.junit.jupiter.api.Test;

class DivisionTest {

    @Test
    void testDivideByZero() {
        ArithmeticException exception = assertThrows(ArithmeticException.class, () -> {
            divide(10, 0);
        });
        assertEquals("Cannot divide by zero", exception.getMessage());
    }
}

This ensures that the division method correctly throws an exception when dividing by zero.

Conclusion

Testing exceptions effectively is a vital part of software quality assurance. JUnit 5’s assertThrows method, combined with Boundary Value Testing, enables developers to create thorough test cases that improve the reliability and robustness of applications. By writing well-structured exception tests, developers can prevent unexpected failures and ensure their applications behave as expected under various conditions.

For further reading, check out:

#JUnit5 #ExceptionTesting #AssertThrows #BoundaryValueTesting

From the blog Rick’s Software Journal by RickDjouwe1 and used with permission of the author. All other rights reserved by the author.

Rick Djouwe’s Blog

Hello, and welcome to my blog!

My name is Woubinwou Djouwe Rick Manuel, but most people call me Rick. I am an undergraduate Computer Science student at Worcester State University, and this blog is dedicated to documenting my journey in CS-443: Software Quality Assurance and Testing.

About Me

I have a strong passion for software engineering and artificial intelligence, and I enjoy working on projects that solve real-world problems. Throughout my academic journey, I have gained experience in web development, Python, Java, C++, and database management. I also have a background in tutoring and mentoring students in math and computer science.

From the blog Rick’s Software Journal by RickDjouwe1 and used with permission of the author. All other rights reserved by the author.