Decision Table Testing: How Companies Can Save Bug Fixing Costs?

Decision table testing is a strategic approach in software testing that systematically evaluates how a system responds to various combinations of conditions and actions. By mapping inputs to outcomes, it ensures all scenarios are tested, helping identify edge cases and potential issues. 

This technique is particularly useful for complex business rules, automated workflows, or systems with multiple user inputs. It provides clarity and structure to the testing process.

In this blog, you will learn how to become a more effective software tester by understanding its key components and applying best practices to improve testing.

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What is Decision Table Testing? A Simple Guide

Decision table testing is a black-box testing technique that helps to model and evaluate system behavior based on various input conditions and their corresponding actions. The technique uses a structured table format to represent all possible combinations of inputs and the expected system outputs or actions. This makes it easier to test complex systems with multiple variables. 

Software testing is a crucial process in the software development lifecycle. It helps to remedy potential factors that can lead to performance glitches and errors, thus ensuring a better user experience.

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Key Characteristics of Decision Table Testing:

• Ensures that all possible input combinations are tested.
• Helps in organizing complex conditions and actions clearly.
• Focuses solely on input-output behavior, without needing to know internal system workings.
• Minimizes the risk of missing critical test cases or combinations.

Also Read: What Do Software Engineers Do? Roles, Responsibilities & Career Scope

Components of a Decision Table

A decision table in software engineering is made up of three primary components: Conditions, Actions, and Rules. Each component plays a crucial role in organizing the logic of how the system should behave based on different input combinations. 

Let's break down each part in detail:

1. Conditions

Conditions are the various inputs or factors that can influence the system's behavior. These are typically the variables that change or are evaluated in a system. In a decision table, conditions are represented as columns.

Example: In an online shopping system, conditions could include factors like whether a user is logged in, if a product is in stock, or whether a discount code is applied.

Conditions may have different possible values, like:

• Yes/No
• True/False
• In Stock/Out of Stock
• Discount Code Applied/Not Applied

Each condition represents a specific factor that must be evaluated during testing.

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2. Actions

Actions are the expected outcomes or results that occur when specific combinations of conditions are met. These are the behaviors the system should exhibit based on the evaluated conditions. Actions are typically represented as rows in a decision table.

Example: In the same shopping system, actions include allowing the purchase, applying a discount, or showing an out-of-stock message.

Actions are the results that testers want to ensure happen for each unique combination of conditions.

3. Rules

Rules represent the different combinations of conditions and actions that drive the outcome. Each rule corresponds to one row in the decision table, and it shows which combination of conditions leads to which actions. 

The rows of a decision table in software engineering are essentially the rules that specify the system's behavior for each condition combination.

Example: If the user is logged in, the product is in stock, and a discount code is applied, the expected actions would be to allow the purchase and apply the discount.

Here's a sample decision table for an online shopping system, where we evaluate the conditions against possible actions:

Structure:

Looking ahead, here are some methods to interpret the table:

• Conditions: The first three columns represent the different input conditions for each test case (logged in, in stock, discount code applied).
• Actions: The last four columns represent the actions (results) triggered by the conditions.
• Rules (Rows): Each row represents a rule that combines the conditions and actions. For example, the first row represents the scenario where the user is logged in, the product is in stock, and the discount code is applied. 

The corresponding actions are: Allow Purchase (Yes) and Apply Discount (Yes), with no out-of-stock message or login redirection.

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Purpose of Decision Table Testing

The primary purpose of decision table testing in software engineering is to simplify the process of validating complex systems. It does this by reducing the sheer number of possible test cases. It achieves this by organizing conditions and actions into a structured format. 

This helps testers visualize and manage all the possible combinations of inputs and their corresponding outputs. 

The structured approach ensures that no scenarios are overlooked, increasing the overall reliability and accuracy of testing. By breaking down complex systems into manageable, visual tables, decision table testing provides several key benefits:

• Complete Coverage of Input Combinations: Decision table testing ensures all possible input combinations are tested. It is crucial for complex systems with multiple interacting conditions, where manual testing would be too time-consuming and error-prone.
• Reduction of Test Case Complexity: Instead of manually testing every combination of inputs, the decision table in software engineering simplifies this process by minimizing redundancy. This ensures efficient use of resources while maintaining comprehensive coverage.
• Elimination of Missed Scenarios: One of the biggest challenges in software testing is ensuring that every possible scenario is accounted for. Decision table testing provides a clear visual representation of all condition-action combinations. This makes it easier to identify any potential gaps in the test coverage.
• Identification of Edge Cases: It examines all possible combinations. Thus, it helps testers spot edge cases and unexpected behavior that may not be evident with traditional testing methods.

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Next, let’s look at how to create a decision table for testing.

How to Create a Decision Table For Testing?

Creating a decision table involves a structured process to ensure that all relevant conditions and actions are accounted for, along with testing every possible scenario. 

By following a step-by-step approach, testers can build an effective decision table that helps streamline testing efforts and ensure comprehensive coverage.

Let's break down the process.

1. Identifying Conditions and Actions

The first step in creating a decision table in software engineering is identifying the conditions (inputs) and actions (outputs) that will drive the decision-making process.

Conditions: These are the factors or inputs that affect the system's behavior. Start by listing all the possible conditions that may impact the outcome of the system.

• Example: In an online shopping system, conditions might include:
  • Is the user logged in?
  • Is the product in stock?
  • Is a discount code applied?

Actions: Next, identify the actions or responses that the system should take based on the conditions. These represent the expected outcomes or results.

• Example: Possible actions could be:
  • Allow purchase
  • Apply discount
  • Show out-of-stock message
  • Redirect to the login page

Tip: Be sure to keep the conditions clear and logical to avoid confusion later. Conditions should ideally be independent of each other to reduce complexity and overlap.

2. Creating the Table

Once the conditions and actions are identified, the next step is to create the decision table itself. This involves structuring the table so that every possible combination of conditions is represented, with corresponding actions listed for each combination.

Here’s how to proceed.

• List Conditions in Columns: Each condition should be represented as a column in the table. The number of columns will correspond to the number of conditions.
• List Actions in Rows: Each action should be represented as a row in the table. The number of rows will depend on the number of actions to test.
• Populate the Table with Rules: Each row in the decision table represents a rule, which is a unique combination of condition values (e.g., Yes/No, True/False). For each rule, identify which actions should occur based on the conditions.

Example Table Structure:

Structure:

Each row (rule) represents a specific set of input conditions, and each column represents the outcome based on those conditions.

3. Validating the Table

Once you create the decision table in software engineering, you need to validate it to ensure its completeness and accuracy.

• Check All Possible Combinations: Ensure that every possible combination of conditions is represented. If there are too many combinations to manually test, use a logical approach to reduce redundancy or focus on critical conditions.
• Ensure No Missing Scenarios: Double-check that all relevant scenarios, including edge cases, are included in the table. 

For instance, consider cases where certain conditions might be rare or less likely but still important to test.

• Review Logic and Clarity: Ensure that the conditions are clearly defined and that actions are logically aligned with each condition combination. This is crucial to avoid ambiguity in the expected outcomes.
• Validate with Stakeholders: Validate the table with system designers, developers, or other stakeholders to ensure it accurately represents the system's behavior and covers all required scenarios.

Key Tips for Effective Decision Table Creation:

• Use logical and distinct conditions that cover all input possibilities.
• Ensure each action is clearly tied to specific condition combinations.
• Keep the table as simple as possible but comprehensive enough to cover edge cases and all possible combinations.
• Continuously validate the table to ensure it accurately reflects the system's behavior and provides comprehensive test coverage.

There are multiple types of decision tables that you can use for your software testing projects. Let's have a look at some of them.

Different Types of Decision Tables Used for Testing

Decision tables come in various forms, each suited to different levels of complexity in the system being tested. The type of decision table used depends on the number of conditions and actions involved and how they interact with each other. 

Let's explore three primary types: Standard Decision Table, Extended Decision Table, and Combinatorial Decision Table, detailing when and why each is used.

1. Standard Decision Table

A Standard Decision Table is the most basic form, suitable for simple systems with a limited number of independent conditions and actions. It is typically used when the system under test has relatively straightforward logic where conditions do not depend on each other.

When to Use:

• Systems with a small set of conditions.
• Simple decision-making scenarios where each condition independently triggers specific actions.

Advantages:

• Simplicity: Easy to create and understand, making it suitable for less complex systems.
• Clarity: Clearly shows how each condition influences the outcome.
• Quick to Implement: Ideal for cases where minimal testing complexity is involved.

Example Use Case: An online registration form where conditions might include "Is the email valid?" and "Is the user already registered?" Each of these conditions leads to specific actions, such as allowing registration or showing an error.

Structure:

2. Extended Decision Table

An Extended Decision Table is used when there are more complex conditions, where some conditions are dependent on the values of other conditions. This type of table adds more structure and flexibility to handle these dependencies.

When to Use:

• Systems with conditions that depend on the state of other conditions.
• Situations where actions vary based on combinations of conditions.

Advantages:

• Handles Dependencies: Allows for more complex logic, where one condition's state can influence others.
• Organizes Complex Scenarios: Breaks down complicated decision-making processes into more digestible components.
• Improved Clarity for Complex Systems: By clearly defining dependencies, it ensures all combinations are tested correctly.

Example Use Case: A loan approval system where the "Loan Approved" action depends not only on the applicant's credit score but also on whether the applicant's income is above a certain threshold.

Structure:

3. Combinatorial Decision Table

A Combinatorial Decision Table is the most advanced type of decision table. It is used when the system has multiple conditions that interact with each other in a complex way.

This table is particularly useful when you need to account for a large number of input combinations that might not be obvious at first glance.

When to Use:

• Systems with many conditions that interact in various ways.
• Complex systems where conditions are not independent and the number of combinations grows exponentially.
• Testing for edge cases or combinations that could lead to unexpected results.

Advantages:

• Comprehensive Testing: Ensures that all possible combinations of conditions are tested, even those that may not seem likely or immediately obvious.
• Minimizes Redundancy: Combines multiple conditions into a single row, reducing the need to test each combination manually.
• Ensures Robustness: Helps identify rare combinations or edge cases that could cause the system to behave incorrectly.

Example Use Case: A multi-factor authentication system where conditions such as "Is the password correct?", "Is the user's device recognized?", and "Is the time of login within allowed hours?" interact with each other to determine if access is granted.

Structure:

Summary of When to Use Each Type:

• Standard Decision Table: Best for simple systems with independent conditions and actions. Easy to implement and interpret.
• Extended Decision Table: Ideal for systems with conditional dependencies between factors. Offers more flexibility and handles complex scenarios.
• Combinatorial Decision Table: Suited for highly complex systems with many interacting conditions. Ensures all combinations are tested, even edge cases, for robust testing.

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The next section showcases some examples of decision tables that will help you to understand them better. 

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An Example of Decision Table Testing

Decision table testing helps testers visualize all possible condition combinations and ensures that the system behaves correctly in every scenario. By breaking down complex systems like login screens into decision tables, you can create comprehensive test cases that cover all potential user inputs and system states. This technique is powerful in ensuring high test coverage and catching edge cases in software testing.

Here’s a step-by-step example of Decision Table Testing:

Scenario: Testing a Simple Login System

We’ll create a decision table to test a login screen. The conditions we’ll evaluate include:

• Whether the username is correct.
• Whether the password is correct.
• Whether the user’s account is active.
• Whether the system is under maintenance.

The expected actions will be:

• Allow login: The user can log in successfully.
• Display error message: Show an error due to incorrect username/password or inactive account.
• Redirect to maintenance page: If the system is under maintenance, users should be redirected to a maintenance page.

Step 1: Define Conditions and Actions

Conditions:

• Is the username correct? (Yes/No)
• Is the password correct? (Yes/No)
• Is the account active? (Yes/No)
• Is the system under maintenance? (Yes/No)

Actions:

• Allow login
• Display error message
• Redirect to maintenance page

Step 2: Construct the Decision Table

Now, let’s list all possible combinations of the conditions. The decision table should have 2^4 = 16 possible combinations (because each condition has two outcomes: Yes or No). Here’s what the table looks like:

Step 3: Evaluate Each Row

Each row in the decision table represents a unique combination of conditions, and you need to determine the appropriate actions based on the conditions.

• Row 1: All conditions are positive (username, password, account active), and the system is not under maintenance. Therefore, the action is Allow login.
• Row 2: Username and password are correct, but the account is not active. The action is to Display error message.
• Row 3: Username and password are correct, the account is active, but the system is under maintenance. The action is to Redirect to maintenance page.

Continue evaluating each row in the table, determining which action applies based on the conditions.

Step 4: Identify Test Cases

Now that you’ve built the decision table, you can identify the test cases based on the combinations of conditions.

Test Case 1:

• Conditions: Username correct, password correct, account active, system not under maintenance.
• Expected Action: Allow login.
• Expected Outcome: The user is allowed to log in.

Test Case 2:

• Conditions: Username correct, password correct, account inactive, system not under maintenance.
• Expected Action: Display error message.
• Expected Outcome: The system shows an error message that the account is inactive.

Test Case 3:

• Conditions: Username correct, password incorrect, account active, system not under maintenance.
• Expected Action: Display error message.
• Expected Outcome: The system shows an error message that the password is incorrect.

Test Case 4:

• Conditions: Username correct, password correct, account active, system under maintenance.
• Expected Action: Redirect to maintenance page.
• Expected Outcome: The system redirects the user to a maintenance page.

Step 5: Execute and Validate the Test Cases

Execute the test cases by inputting the conditions into the system and verifying that the actions occur as expected. This ensures that all potential scenarios are tested, reducing the risk of errors and improving the coverage of the login system.

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Next, let’s look at the benefits and limitations of decision table testing.

Advantages and Challenges of Decision Table Testing

Decision table testing is particularly useful for identifying inconsistencies in business logic and simplifying the testing process for systems with numerous input conditions. However, while decision table testing has many advantages, it also comes with certain challenges, especially when dealing with large, complex systems.

Below is a comparison of the key advantages and limitations of decision table testing:

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With these challenges outlined, let’s explore the best practices to overcome them.

Best Practices for Decision Table Testing

It's essential to follow some key best practices to make the most of decision table testing and overcome its challenges. Let's explore some recommended strategies:

1. Start Simple

When first implementing decision table testing, it's best to start with simple tables and gradually build complexity as the system evolves. This helps testers gain familiarity with the process before dealing with more intricate conditions and actions.

Take into account these approaches.

• Begin with Basic Scenarios: Start with systems that have fewer conditions and actions. This allows for a better understanding of how decision tables work and helps you identify the most common decision paths.
• Expand Gradually: Once you're comfortable with simpler tables, you can start adding more conditions or actions as needed. This progressive approach ensures that you don't become overwhelmed with complexity early on.
• Focus on Core Logic: Initially, focus on the most critical conditions and actions before expanding the table to cover edge cases and less common scenarios.

2. Automate Where Possible

For larger systems with many conditions and actions, manually managing decision tables can be tedious and prone to errors. Automation tools can streamline the process, making it faster and more accurate.

Here are some methods to consider.

• Use Automation Tools: Automated testing tools can generate and execute decision table tests more efficiently, reducing the time needed for manual table creation and scenario execution.
• Integrate with Test Suites: Some testing frameworks allow you to integrate decision table testing into your broader test suite, automating the generation of test cases from the decision table itself.
• Maintain Accuracy: Automated tools can help minimize human error when creating or updating decision tables, ensuring that the right conditions and actions are included in the tests.

3. Regularly Review Tables

As software systems evolve and business logic changes, it's essential to keep decision tables up to date. Regularly reviewing and updating decision tables helps ensure their accuracy and effectiveness in testing.

Consider these strategies:

• Update with System Changes: Whenever the system or requirements change, revisit the decision table to add or adjust conditions and actions that reflect the new logic.
• Cross-Check with New Features: While adding new features, review the decision table to see if any new scenarios need to be tested. This helps prevent gaps in test coverage.
• Involve Stakeholders: Collaborate with developers, product managers, and business analysts to verify that the decision table aligns with the latest understanding of the system's behavior.

With the growth in the software industry, there is now a growing demand for trained software testing professionals. If you are looking to learn about the intricate aspects of software testing, upGrad courses can help you to do just that. 

Also Read: Top 35 Software Testing Projects to Boost Your Testing Skills and Career

How Can upGrad Help You Become a Software Tester?

Software testing is a crucial component of the software development lifecycle, ensuring the delivery of high-quality applications. To excel in this field, professionals need to develop a strong understanding of various testing methodologies, tools, and best practices. 

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References:  
https://magnitia.com/blog/software-testing-statistics-2023/
https://toolsqa.com/software-testing/istqb/decision-table-testing/