DEV Community: Balajee Venkatachalam

Future Of Manual Testers in Age of AI

Balajee Venkatachalam — Sat, 14 Mar 2026 18:39:34 +0000

The future of manual testing in the age of AI is changing, but it is not disappearing. Artificial intelligence can now perform many repetitive testing tasks such as running regression tests, generating test data, and identifying common defects. Because of this, some of the routine work that manual testers used to do will gradually be handled by AI tools and automated systems. This helps save time and allows testing to be performed faster and more efficiently.

However, manual testing will still remain important because AI cannot fully replace human thinking and judgment. Testers are better at understanding user behavior, identifying usability issues, performing exploratory testing, and noticing unexpected problems in an application. Humans can think creatively and evaluate software from the perspective of real users, which AI tools often cannot fully replicate.

In the future, the role of manual testers will evolve into a more analytical and strategic role. Instead of only executing test cases, testers will design better test strategies, validate the results produced by AI tools, and focus more on improving overall software quality. Manual testers will also benefit from learning additional skills such as automation basics, API testing, and working with modern testing tools.

Overall, AI will support testers rather than completely replace them. The future of testing will involve a combination of human intelligence and AI-powered tools, where testers use technology to work smarter and ensure high-quality software.

Decision Table Testing

Balajee Venkatachalam — Sat, 14 Mar 2026 18:36:04 +0000

Decision Table Testing is a black-box testing method that represents different combinations of inputs and their corresponding outcomes in a structured tabular format. It consists of three primary elements:

Conditions: The input variables that impact the system’s behavior.
Actions: The outcomes or system responses based on combinations of conditions.
Rules: Specific combinations of conditions and their corresponding actions.
This method allows testers to cover multiple scenarios systematically by defining and organizing the rules that guide the system’s behavior. Each rule represents a unique combination of inputs that yield a specific output, simplifying the testing process.

Types of Decision Tables
Decision tables come in different forms, each suited to modeling specific levels of decision-making complexity. The choice of table depends on how many conditions are involved, how those conditions interact, and the variety of possible outcomes you need to capture.

Main types of decision tables:

Limited Decision Table
A Limited Decision Table is the simplest form, best suited for situations where conditions are independent and have only two possible values, such as True or False. Because it focuses on straightforward logic, it’s often used for validating basic scenarios with minimal complexity.
Example: A login system that checks whether both “Username is valid” and “Password is correct.”

Extended Decision Table
An Extended Decision Table is designed for more complex scenarios involving multiple conditions and their interdependencies. It is especially useful when a decision depends on various inputs that can combine in different ways, allowing testers to cover a much wider range of possibilities.
Example: A loan approval process where factors like “Income,” “Credit Score,” and “Debt-to-Income Ratio” interact to determine eligibility.

Condition–Action Table
A Condition–Action Table maps each condition directly to a specific outcome or action, making it easy to see what the system should do under particular circumstances. This type of table works well when each condition has a clear and direct impact on what happens next.
Example: A discount engine where “Membership Status” and “Purchase Total” decide whether a customer receives a discount.

Switch Table
A Switch Table applies when decisions hinge on a single controlling condition that branches into different outcomes. This approach simplifies the logic into a straightforward structure, making it easier to test predictable, mutually exclusive paths.
Example: A traffic light system where the signal color (Red, Yellow, Green) determines whether vehicles stop, slow down, or go.

Rule-Based Decision Table
A Rule-Based Decision Table brings together multiple rules to handle highly nuanced or layered decision logic. It is ideal for systems where different variables interact in complex ways and where compliance, risk, or business rules must be explicitly captured.
Example: An insurance eligibility system that considers “Age,” “Driving Record,” and “Location” to determine approval or rejection.

Boundary Value Analysis

Balajee Venkatachalam — Sat, 14 Mar 2026 18:22:02 +0000

Boundary value analysis is a test technique used to verify that software functions correctly when processing boundary values, such as the minimum and maximum values of input parameters. It is important to apply this technique because boundary values are often a source of errors in software applications.
By using boundary value analysis, as a software tester, you can ensure that the software functions correctly in all situations where boundary values play a role. The analysis is especially important for cross-functional teams involved in the development and testing of software. By using this technique, cross-functional teams can improve the quality of software and detect errors at an early stage. This is important to prevent delays and additional costs in the development process.

Because boundary value analysis also provides a common language and methodology for testing boundary values, it leads to better collaboration between cross-functional teams. This also results in fewer misunderstandings and more efficient communication between team members.

Common Manual Testing Techniques

Balajee Venkatachalam — Sat, 14 Mar 2026 18:11:30 +0000

Software testing techniques are methods used to design and execute tests to evaluate software applications. The following are common testing techniques:

Manual testing - Involves manual inspection and testing of the software by a human tester.
Functional testing - Tests the functional requirements of the software to ensure they are met.
Non-functional testing - Tests non-functional requirements such as performance, security, and usability.
Unit testing - Tests individual units or components of the software to ensure they are functioning as intended.
Integration testing - Tests the integration of different components of the software to ensure they work together as a system.
System testing - Tests the complete software system to ensure it meets the specified requirements.
Acceptance testing - Tests the software to ensure it meets the customer's or end-user's expectations.
Regression testing - Tests the software after changes or modifications have been made to ensure the changes have not introduced new defects.
Performance testing - Tests the software to determine its performance characteristics such as speed, scalability, and stability.
Security testing - Tests the software to identify vulnerabilities and ensure it meets security requirements.
Exploratory testing - A type of testing where the tester actively explores the software to find defects, without following a specific test plan.
Boundary value testing - Tests the software at the boundaries of input values to identify any defects.
Usability testing - Tests the software to evaluate its user-friendliness and ease of use.
User acceptance testing (UAT) - Tests the software to determine if it meets the end-user's needs and expectations.