Decision Table in Software Testing

Hari Mahesh

“In preparing for battle, I have always found that plans are useless, but planning is indispensable” – Dwight D. Eisenhower.

That’s what testing software is often like. You can’t always foresee every bug or edge case, but having a good strategy is the required approach. What is one of a tester’s most underrated weapons? – Decision Tables.

If you’ve ever had a complex feature with dozens of edge-cases that make you go cross eyed trying to figure out how to generate coverage, it’s a call for help to step back and build a decision table. They’re the ones who help you take confusion and distill it into clarity. This can help you take a mess of what-ifs and refine them into a neat, logical matrix.

Key Takeaways

1. A decision table is a tabular representation of input conditions and their corresponding actions.
2. The article breaks down a decision table into four parts:
   • Condition Stub (inputs)
   • Action Stub (outputs)
   • Condition Entries (values per rule)
   • Action Entries (expected results per rule).
3. It introduces two main types:
   • Balanced Decision Tables – cover all possible condition combinations, ideal for exhaustive testing but potentially large and complex.
   • Limited Entry Tables – focus on key scenarios for efficiency, but may miss edge cases.
4. Advantages include thorough testing, automation support, ease of regression testing, and better requirement modeling.
5. This article discusses the use cases when decision tables are not a good choice.

What is a Decision Table?

A ‘Decision Table‘ is a tabular representation of a logical structure or algorithm, and it is commonly used in software development and business decision-making processes. It organizes inputs and causes, and also expresses outputs and effects, which in turn, facilitates envisioning how to combine inputs to affect outcomes. For this reason, it is also called a Cause-Effect Table.

Why Use a Decision Table in Software Testing?

A decision table is useful for modelling complex logic in a structured and visual manner. It facilitates structuring over input conditions and their associated actions, which makes decision-making rules more readable and verifiable. Particularly helpful in software testing and requirements analysis, it makes sure that all conditions are accounted for and addressed properly. By clearly expressing logic, it also helps to reduce confusion and improve communication between stakeholders.

• Handles Complex Logic Efficiently: Decision tables provide a method for representing complex logic with multiple combinations of inputs in a structured table format. This allows for a systematic treatment at a glance of all possible cases.
• Complete Test Coverage: Decisions allow testers to design systematic test cases by listing all condition-action combinations. This guarantees that no logic branches will be overlooked in the testing process. Read: What is Test Coverage?
• Reduces Redundancy: The structured approach facilitates detecting and removing duplicate or unnecessary test scenarios. This will allow for an easier way to track your testing progress.
• Clarifies Vague Requirements: Decision tables force stakeholders to be clear about the conditions and their corresponding actions. This enables us to unravel hidden rules and have a common understanding of the system.
• Improves Communication: Decision tables serve as a visual and standardized reference for developers, testers, and business analysts. They bridge communication gaps by clearly documenting decision logic for all parties involved.

Key Components

A decision table is divided into four main parts:

• Conditions Stub: Presents every input condition, or logic statements that impact the decision making phase. Each condition is stated on a distinct row so that we can see exactly what has to be tested.
• Action Stub: Defines all possible actions and/or responses based on various configurations of input conditions. Each action is presented in a separate row to link with the decision rules.
• Condition Entries: Specifies the actual values (e.g., Yes/No or True/False) that each condition can take under a particular rule. These are arranged column-wise, with each column representing a distinct rule or scenario.
• Action Entries: Indicate which actions should be executed based on the combination of condition values in each rule. They are aligned with the condition entries and reflect the expected output per rule.

Structure of a Decision Table

A decision table is in the form of a table, which represents the logical relationship between the inputs (conditions) and outputs (actions). It is comprised of four main parts as follows:

• Condition Stub: This is where all the input conditions or decision rule(s) that influence the outcome are enumerated. For clarity, each condition is listed in a separate row.
• Action Stub: It comprises every potential response, or output, that can happen according to the input conditions. These are also added to separate rows, usually just underneath the conditions.
• Condition Entries: These are the actual values (such as Yes/No, True/False, or specific ranges) that each condition can take for a particular rule. Each column represents one unique rule or scenario.
• Action Entries: This part of the file specifies what actions should be performed for each rule. The conditions are associated with the actions in the same column.

Each row is a condition or an action, and each column is a particular rule, a set of input conditions resulting in an outcome. This architecture provides a full and ordered way to do a compact expressing of complex decision logic.

Decision Table Example:

Here is an example of a Loan Approval Decision Table.

• Conditions Stub: The leftmost rows under Conditions (e.g., Age > 18, Credit Score > 700, Income > $50,000) list all the input conditions.
• Condition Entries: The values under each rule column (Yes/No) show how the conditions apply in that specific scenario.
• Action Stub: The rows under → Actions (e.g., Approve Loan, Request Guarantor, Reject Loan) list all possible outcomes.
• Action Entries: The Xs indicate the actions for each rule based on the given condition values.

Decision Tables Techniques

The two types of decision tables applied to depict and manage decision logic are Balanced Decision Tables and Limited Entry Decision Tables. Each form has its own use in the various ranges of logic complexity, with the scope of analysis or testing as desired.

Balanced Decision Table (Complete Decision Table)

This table contains all possible combinations of causes. Suppose there are ‘n’ sources of binary conditions (i.e., each of which can have one of two values or be ‘true’/’false’, like “Yes”/”No”). In that case, there will be ‘2^n’ entries in the table. This kind of source is typically used when it is very important not to miss out on a rule because a system might fail if a rule is forgotten.

Pros:

• Provides a thorough and complete representation of logic
• Ideal for exhaustive testing, ensuring all possible scenarios are accounted for

Cons:

• The size of the table grows exponentially with the number of conditions
• Can become large, complex, and hard to manage as the number of inputs increases

Limited Entry Decision Table

This table does not contain all of the combinations, but this type of table contains the selected, the relevant, and the high risk rules. It’s used to concentrate on the most important situations – most commonly selected by business risk, priority or probability of occurring.

Pros:

• Easier to create and maintain
• More efficient by focusing on meaningful test cases and avoiding overload

Cons:

• May miss some edge cases or rare scenarios
• Less comprehensive than a complete decision table, which can lead to gaps in coverage

Steps to Create a Decision Table

To create a decision table, there is a systematic and orderly series of steps that must be strictly followed to make sure that all of the potential conditions are considered and correctly matched to the potential results. This simplifies complex logic, makes it clearer, and gets more comprehensive test coverage.

• Identify the Conditions: First, identify all the input conditions, factors, or variables that affect or influence the decision. These are the conditions or tests by which an action is decided upon.
• Identify Possible Actions: Then state all the possible results or courses of action that would arise from each possible combination of conditions. These are choices or actions the system should make.
• Determine Rules: Create all interesting combinations of the previously found conditions. Each (input, output) pair is a separate rule, that is, an individual scenario that can be met by system.
• Define Actions for Each Rule: To each rule, associate the actions to be performed when each set of conditions has been parameterized. This is the relation between inputs and outputs.
• Simplify the Table: Review the list and remove any conflicting rules, or combine similar ones. This works to simplify without sacrificing the logic.
• Validate the Table: Last, validate the decision table against the system requirements or business rules. This makes sure that everything is right with what you want and what you expect to get.

Advantages of Decision Tables

There are many advantages of using decision tables in testing. Let’s look into those.

• Thorough Test Coverage: All logical paths are tested via decision tables because they model each and every possible input condition combination. This leads to full-scope and high-quality test coverage.
• Reduces Ambiguity: Since each condition is documented and for each condition, each possible outcome and vice-versa, decision tables aid in removing confusion or ambiguity from system requirements. That way, you can avoid using the wrong conventions in development and testing.
• Great for Business Rules: They work well with complex business rules, such as in financial, insurance, or compliance systems. Their well-defined structure naturally allows rule-based logic to be modeled and verified.
• Facilitates Automation: One appealing feature of decision tables when automating tests is that the formalism is conducive to generating the step level test scripts. This improves efficiency and repeatability in the procedures run.
  Read: Test Automation Playbook.
• Helps with Regression Testing: Since they are easy to update when rules change, they are particularly useful for keeping track of the modifications and regression testing. This helps ensure a consistent logic validation through changes in software updates.

When Not to Use Decision Tables

Though decision table is very good for complex logic, it is not very applicable in all the situations. There are perhaps some cases where other approaches provide better clarity or efficiency.

• Basic Validations, 1-2 Conditions: However, for logic with only a few simple conditions, a decision table is like using a sledgehammer. If-else statements or checklists tend to be more pragmatic and efficient.
• Sequential Workflows (Use State Diagrams Instead): Decision tables are not suitable for cases in which actions are based on the order or timing of events. State diagrams are better suited for state-behavior modelling, and state-transition diagrams are the better choice in representing state-based transitions.
• High Change Dynamic Environments and Often Changing Rules: Keeping a decision table up-to-date can be time-consuming and error-prone if the business rules are dynamic and get changed frequently. For these cases dynamic rule engines or scripts are more flexible and scalable.

Conclusion

Decision tables are a simple and very effective way to deal with complex logic when testing software. They aid testers to get a sense of all the potential combinations of input and make sure they didn’t miss any corner case. Decision tables increase both test coverage and collaboration with the business, since they make business rules explicit and testable. They are especially powerful in systems powered by multiple conditions and actions. The bottom line is that decision tables add an element of structure, organization, and efficiency to our testing work.

“We spent so much time on maintenance when using Selenium, and we spend nearly zero time with maintenance using testRigor.”

Keith Powe VP Of Engineering - IDT