DEV Community: Alexi

Manual vs. Automation Testing: Where Should You Invest First?

Alexi — Thu, 03 Sep 2026 15:32:15 +0000

Automation testing rarely stands on its own. Writing reliable automated tests requires a solid understanding of manual testing scenarios and outcomes. Moreover, automation still struggles in areas that require human judgment, empathy, and creativity.

Common Mistakes Killing Your ROI

❌ Trying to automate everything on day one

❌ Ignoring test maintenance costs (they add up quickly)

❌ Automating unstable features that change weekly

❌ Choosing tools based on trends instead of specific project needs and team capabilities

❌ Forgetting that manual testing validates whether software aligns with business intent, not just technical correctness

Start with manual testing if:

✓ You're launching an MVP or prototype

✓ Features are evolving rapidly

✓ Your team lacks automation expertise

✓ The product has a short lifecycle

✓ You need quick validation without infrastructure setup

Invest in automation when:

✓ You have stable, repetitive test cases

✓ Regression testing consumes significant manual effort

✓ You're scaling rapidly (users, features, releases)

✓ CI/CD integration is critical

✓ Long-term product maintenance is planned

The Hybrid Strategy

Manual testing is irreplaceable for user experience and visual inspections, while automated testing shines in handling repetitive tasks and large-scale projects. Used together, they complement each other and ensure stronger product quality.

AI-Assisted Testing

Up to 56% of companies are already investigating AI adoption in testing, with 38% viewing AI as a solution for tester shortages.

But my point is: It’s not a competition between people and AI. When used together, they simply make it easier to keep up the pace and still deliver solid results.

How to Improve the Testing Process Across Multiple Devices

Alexi — Fri, 28 Aug 2026 14:14:26 +0000

Enhancing the testing process across different devices is crucial to ensuring high software quality and compatibility. Below are several strategies and recommendations to improve this process:

1. Establish a Clear Testing Strategy

Create a test plan: Identify key aspects of the application that need testing, such as functionality, performance, security, and usability. Determine the target devices and platforms for testing and establish a testing schedule.

2.Set Up a Comprehensive Test Environment

Emulators & simulators: Use emulators and simulators for mobile testing to quickly verify functionality across different devices.

Physical devices: Whenever possible, test on real devices to obtain more accurate results.

3.Leverage Test Automation

Automated testing: Develop automated tests for core application functionalities to accelerate testing.

Cross-platform testing tools: Utilize tools like BrowserStack or Sauce Labs to test applications across different devices.

4. Implement CI/CD Practices

Continuous Integration & Deployment: Integrate testing into the CI/CD pipeline to automate test execution and accelerate release cycles.

5.Consider Device Diversity

Target audience analysis: Identify the most popular devices and platforms among your users and prioritize testing on them.

Varied configurations: Ensure testing covers different screen sizes, resolutions, OS versions, and hardware specifications.

6.Keep Test Cases Up to Date

Test case updates: Regularly review and update test scenarios to reflect application changes and support new devices.

7.Collect and Analyze Test Data

Logs & reports: Gather testing logs and reports to analyze issues and identify trends.

User feedback: Consider user feedback on application performance across devices to refine the testing approach.

8.Maintain Proper Documentation

Testing process documentation: Document testing procedures to ensure consistency and clarity across the team. Regularly generate test reports to track progress and identify areas for improvement.

9. Invest in Team Training

Training & skill development: Train testers on new tools and methodologies to improve their efficiency in testing across multiple devices.

Collaboration: Encourage close collaboration between developers and testers to better understand and resolve issues.

By following these recommendations, you can significantly improve testing efficiency across multiple devices, leading to higher software quality and a better user experience

Myths About Automated Testing

Alexi — Fri, 28 Aug 2026 14:08:09 +0000

Automated testing has become essential to modern software development, but it’s often misunderstood. Despite its benefits, several myths persist that can mislead organizations when implementing test automation. Let’s take a look at some myths about automated testing.

Myth1

*100% Automation is Possible *

The idea that full automation is achievable is a common misconception. While automation is incredibly effective for repetitive, well-defined tasks, it cannot fully replace manual testing. Certain tests, such as exploratory testing or usability tests, are inherently impossible to automate due to their need for human judgment and creativity.

Myth 2

*Developers Are Better Than Automated Testers *

While developers may have an advantage in programming skills, testers bring a unique mindset focused on uncovering bugs and verifying system functionality. Automated testers are specialized in creating reliable testing frameworks and ensuring code quality, offering a crucial perspective that developers may not prioritize.

Myth3

*Automation Is Expensive *

Although setting up automation can require an upfront investment, when done right, it can significantly reduce overall testing costs. Automated testing reduces the need for repetitive manual testing and speeds up the testing process, ultimately delivering more cost-effective long-term results.

Myth 4

*Automation Is Only for Large Projects *

Some people believe automation only benefits large-scale projects, but this is not the case. Even smaller projects can benefit from automation by improving test efficiency, reducing human error, and ensuring consistent test execution. It can help maintain high-quality standards across projects of all sizes.

How a Balanced Testing Pyramid Turns QA Into a Business Advantage

Alexi — Fri, 26 Jun 2026 09:56:46 +0000

Are slow releases, rising QA costs, and late-stage defects slowing your product down?
If bugs still reach production despite significant testing effort, the issue is rarely “not enough testing”.
More often, it’s a lack of a coherent testing strategy.

The Software Testing Pyramid is more than a model; it provides a clear framework for balancing test types to maximize efficiency, speed, and reliability.

The 4 Core Layers: A Detailed Breakdown

The pyramid is divided into 4 levels (from bottom to top):

unit testing (module);
integration testing;
system testing;
user acceptance testing.

Level 1: Unit Testing

Unit tests verify the smallest pieces of your application. When a unit test fails, it pinpoints the exact location of the error, providing immediate, actionable feedback to developers.

Level 2: Integration Testing

This testing level aims to identify interface faults between modules/functions. Integration tests can interact with the code without using any UI actions, typically performed by developers.

Level 3: System Testing

System testing holds great significance as it ensures that the application meets the technical, functional, and business requirements defined by the customer.

Level 4: User Acceptance Testing

This level of testing verifies that the software product meets end-user expectations and is ready for real-world use in production.

The Anti-Patterns: Common Traps to Avoid

Many teams inadvertently adopt "anti-patterns" that invert the pyramid, leading to disastrous consequences for their testing efforts.

The Testing Ice Cream Cone

This is the most common and dangerous anti-pattern. It features a massive layer of slow manual or automated E2E tests, a thin layer of integration tests, and a tiny, almost non-existent base of unit tests. Teams fall into this trap because testing through the UI feels intuitive, and there's often pressure to "just test the feature" without investing in foundational unit tests.

Consequences: Slow feedback loops, a flaky test suite that no one trusts, high maintenance costs, and bugs being discovered late in the development cycle, when they are most expensive to fix.

The Testing Hourglass

In this anti-pattern, teams have a good number of unit tests and E2E tests, but a "pinched" middle with very few integration tests. This often happens when developers focus on their units, and QA focuses on the full system, leaving the crucial connections between components untested.

Consequences: While individual units work and the overall system might appear to function, bugs remain hidden in the interactions between two elements of the system. This can lead to subtle, hard-to-diagnose issues in production.

Optimizing your testing strategy requires experience, context, and the ability to balance speed with risk.

Testing vs Checking: What’s the Difference?

Alexi — Thu, 25 Jun 2026 10:09:15 +0000

In the world of quality assurance, we often hear these two terms thrown around: testing and checking. Some use them interchangeably. But they are not the same. Testing and checking are two different types of activities. They deserve a distinction.

Let’s break it down.

Testing is a cognitive activity. It’s about learning the product, exploring behaviors, forming hypotheses, asking questions, and making informed inferences. Testing is not just about confirming what you already know; it’s about discovering what you don’t.

📌 Testing:

Has an open-ended purpose: to understand behavior and identify risks

Includes unexpected observations

Relies on human thinking and interpretation of results

May include checks, but is not limited to them

Checking is a process of confirmation, validation, and verification. It is the process of verifying specific facts about the product, algorithmically. Checking is part of testing.

📌 Checking:

Follows a precise algorithm: “If X, then Y”

Can be fully automated

Doesn’t provide a deep understanding, only signals that something matches (or doesn’t match) expectations

It is a part of testing, but not testing in the complete sense

So we can say that

🔸 Testing is a human activity.

🔸 Checking is something a machine can do.

💡 Why is this distinction important?

Understanding the difference between testing and checking is the key to an informed, flexible, and truly effective approach to quality assurance.

If we confuse the two, we might wrongly assume that running automated checks is enough. But bugs often hide outside the expected, and it takes human judgment and exploration to uncover them.

This is precisely why we distinguish between the aspects of the testing process that can be performed by machines and those that require QAs.

AI and ML in Software Testing: How These Technologies Are Transforming QA

Alexi — Mon, 08 Jun 2026 06:09:29 +0000

Artificial Intelligence (AI) and Machine Learning (ML) are rapidly transforming the field of software testing and quality assurance (QA). Traditional testing approaches are giving way to more efficient methodologies that leverage AI and ML to improve defect detection.

Integrating AI and ML into QA processes yields several significant benefits:

Faster Test Execution: AI-powered tools can execute tests in parallel, speeding up the testing cycle. This reduces the time to get feedback on code changes.
Reduced Manual Effort: Routine tasks like test runs, data entry, and bug assessment can be handled by AI.
Cost Savings: Automated testing with AI can lead to significant cost savings. Tests can run continuously without human intervention.
Enhanced Defect Detection: Machine learning models can analyze test data to detect patterns that indicate potential defects. This allows QA teams to address issues before they affect users, improving software reliability.

While AI offers many advantages, it also comes with challenges and limitations:

Implementing AI in testing can be complex. Setting up AI models or tools requires data preparation, configuration, and often a certain level of technical expertise.
AI systems, especially deep learning models, can make decisions that are hard to interpret.
If not carefully validated, AI can produce false positives (flagging something as a defect when it’s not) or false negatives (missing a real d
efect).
AI tools often require ongoing maintenance and updates.

To successfully integrate AI and ML into QA, you may consider the following best practices:

Define what you want to achieve with AI in QA. Whether it’s reducing test execution time, improving defect detection - having clear goals will guide your implementation.
Don’t rely solely on AI automation or solely on manual testing. Instead, adopt a hybrid model in which AI handles repetitive or data-intensive tasks, while humans handle the creative, judgment-based aspects.
Identify which testing tasks will benefit most from AI. Start with high-impact areas like automating large test suites, predicting defects, or handling visual testing.

AI and ML are transforming QA in profound ways. Those who embrace these technologies and integrate them thoughtfully into their testing workflows will gain a competitive edge in delivering high-quality software faster.

Welcome to the Fast-Food Era of Testing: Over-Weight by Tests

Alexi — Mon, 25 May 2026 07:24:59 +0000

In software testing, it’s crucial not only to ensure the quality of the product but also the quality of the testing process itself. This is assessed using QA metrics—indicators of test effectiveness, code coverage, and teamwork. One key metric is test coverage—the percentage of code or requirements covered by tests. QA professionals must stay flexible, assess project needs, and clearly communicate priorities to PMs. They should not blindly follow test plans or documentation; instead, they should apply critical thinking and common sense.

I recently attended a testing conference where the concept of the “Fast-Food Era of Testing—being overwhelmed by tests” caught my attention.

I want to share it with you because I completely agree with the speaker’s point: achieving 100% test coverage remains unachievable, so the task of QA is to strike a balance.

*Fast-Food” Testing: 100% Code Coverage ≠ 100% Bug Free Product *

There are some misconceptions about high test coverage, such as the assumption that it guarantees bug-free software. Blindly pursuing 100% test coverage can create more problems than it solves. Here’s how:

False Sense of Security:

Achieving 100% coverage may seem like a victory, but there may be hidden problems. Bugs often hide in areas that automated tests can’t predict, such as untested edge cases or real-world scenarios, because test coverage only shows how much of the app’s functionality is covered by tests, not how good those tests actually are.

Maintenance Cost:

More tests mean higher maintenance costs, as each test needs to be updated and managed regularly.

Diminishing Returns:

As you get closer to 100% coverage, it becomes harder to add meaningful tests. At some point, you’re just writing superficial, redundant tests to tick a box or boost metrics. You might even start writing tests that cover lines of code, but don’t test the actual functionality.

Opportunity Cost:

Time and resources spent on maintaining excessive tests could be better utilized elsewhere, such as improving tests quality or developing new features.

Business Risk:

Over-reliance on a large number of tests can introduce business risks, such as delayed releases or increased costs, impacting overall business performance.

The “Health” plan

To keep testing healthy, think of a balanced “meal plan” for QA:

H

— High-Value Focus

Focus on Minimum Viable Testing (MVT). Add only tests that bring clear business value.

E

— Eliminate Junk

Find and change flaky, remove duplicate, or low-value “fast-food” tests.

A

— Adopt Routines

Hold regular pruning sessions and refactor to keep the test suites clean and reliable.

L —

Level Coverage

Balance coverage at all levels—unit, integration, system. Give priority to high-risk, business-critical flows rather than chasing 100 % coverage.

T

— Track Relevance

Design tests with purpose. Continuously check if each test still aligns with current requirements and business needs.

H

— Healthy Mindset

Apply the 80/20 rule: 20% of well-designed tests often catch 80% of critical issues — so value quality over quantity.

Manual vs Automated Testing: A False Dichotomy

Alexi — Mon, 11 May 2026 07:21:53 +0000

In testing, we often talk about the “balance between manual and automated testing,” but this is a misleading way to think about it. Testing is not about dividing work into manual or automated. It is a process of exploring and verifying the product.

When faced with a certain task, the focus should not be on “balance,” but instead on which tools and approaches are best suited to accomplish that task.

Manual testing is indispensable, as manual test cases serve as the foundation for future automation. Manual testing revolves around the aspects that automated testing can't cover. These include visual application checks and the ability to test specific user experience-based scenarios that are impractical to automate. On the other hand, automated testing has its advantages. It eliminates the human factor, allows you to use the same scenarios repeatedly, and is much faster than manual testing.

Moreover, manual testing experience is invaluable for automation testers. Understanding the app from a user's perspective helps automation testers write better scripts and prioritize what to automate.

However, this is not a question of balance, but of effectiveness in choosing the right approach for the current product needs.

For example, when you go to the store, you don’t think about “balancing walking and biking.” Instead, you consider whether the bike will save time or effort, whether you’re in a hurry, or if it’s more convenient to carry your groceries by bike. You simply choose the option that best accomplishes the task.

The key point is to have a diversity of tools and approaches. This diversity enables better adaptation to the product’s complexity. It is diversity, not balance, that is the key to quality testing.

Let’s Talk About Micromanagement....

Alexi — Mon, 11 May 2026 07:16:07 +0000

Is Micromanagement Sometimes Good and Necessary?

Let’s Talk About Micromanagement....

The dictionary defines micromanagement as “to direct or control in a detailed, often meddlesome manner.” Micromanagement can lead to destructive leadership, which in turn may harm the company’s interests, create a toxic work environment, and reduce employee productivity and motivation.

When Micromanagement Makes Sense?

There are situations where it can be helpful, but only temporarily (from 1 week to 1 month):

*Onboarding a new employee to your team *

At first, even skilled professionals may need direct, hands-on guidance in certain areas to adapt to the workflow and understand the product quickly. This focused support can accelerate their integration. The key is to know when to give them space to work independently.

*Introducing a trainee or junior to a project *

For less experienced team members, close supervision helps them learn faster, avoid common pitfalls, and build confidence before taking on more autonomy.

*Managing high-risk projects *

When mistakes could have serious consequences, maintaining tight control in the early stages can protect outcomes while the team aligns on expectations.

In these cases, focused micromanagement helps ensure success while gradually transitioning to greater independence.

Micromanagement might look like a good way to make sure everything gets done correctly, but in the long run, it usually backfires. Trust, autonomy, and open communication go much further than constant oversight and help create an environment where teams thrive, innovate, and reach their full potential. Finding the right balance between freedom and control is what a good manager is really about.

The Importance of Testing Your E-commerce Website

Alexi — Fri, 17 Apr 2026 08:41:06 +0000

In today’s digital-first world, your e-commerce website is crucial to your business’s success. But what happens when a beautifully designed website fails to deliver on functionality? Customers can’t add items to their cart, payments fail, or mobile users face a glitchy checkout. The result? Plummeting sales, frustrated customers, and a damaged brand reputation.

Here’s the hard truth: 88% of online shoppers won’t return to a website after a bad user experience, and a one-second delay in page load time can lead to a 7% drop in conversions. In a $6.3 trillion e-commerce industry, these numbers are more than just statistics—they’re a wake-up call.

Key Aspects to Test

Functional Testing: Ensure every feature—product pages, search bars, add-to-cart buttons, and checkout processes—works flawlessly. A single broken button can lead to abandoned carts.

Payment Gateway Testing: (part of functional testing) A key aspect of e-commerce testing is eliminating failed transactions to boost revenue and enhance customer confidence.

Usability Testing: (performed alongside functional testing) Deliver an intuitive, mobile-friendly, and accessible shopping experience. Frustration-free navigation = higher conversions.

Compatibility Testing: Ensure seamless performance across browsers, devices, and operating systems.

Performance Testing: Optimize for traffic spikes during sales events. Slow load times or crashes can cost you revenue.

Security Testing: Protect customer data and ensure compliance with PCI DSS (Payment Card Industry Data Security Standard). A single breach can destroy trust and lead to legal repercussions.

Best Testing Approaches

Combine Automation and Manual Testing: Automation speeds up repetitive tasks, while manual testing uncovers real-world usability issues.

Adopt Continuous Testing: Integrate testing into your development workflow to catch issues early and often.

Involve Real Users: Conduct beta testing and A/B testing and gather feedback to fine-tune the customer journey.

The Bottom Line

The success of your website entirely depends on the customer experience. A single technical issue can mean the difference between keeping and losing a customer. By investing in a comprehensive testing strategy, you’re not just preventing problems—you’re creating opportunities for growth, loyalty, and competitive advantage.

Hidden Features of Postman You Might Not Know

Alexi — Tue, 07 Apr 2026 09:18:56 +0000

Postman is already a favorite tool for testing APIs, but it offers several less obvious features that can take your testing to the next level. Here are some hidden features:

_1. Monitoring Requests _

Postman allows you to set up monitors to run your collection of requests at specific intervals and get detailed reports. This is great for checking API stability over time.

Where it's useful: Monitoring API performance and receiving failure alerts in real-time.

_2. Postman Flows _

A visual tool for creating complex workflows without writing code. With Flows, you can chain multiple requests like a flowchart, building automated test scenarios.

Where it's useful: For setting up multi-step test scenarios with dependencies between requests.

_3. Code Generation _

Postman can generate code snippets for your HTTP requests in multiple programming languages, including JavaScript, Python, Ruby, Go, Swift, and more.

Where it's useful: Quickly integrate API requests into your application without writing them from scratch.

_4. Environment Variables _

You can create environment variables for different setups (Dev, Staging, Production) and switch them on the fly without modifying your requests manually.

Where it's useful: Running the same collection in multiple environments without editing individual requests.

5. File Upload Support

Postman supports file uploads for POST and PUT requests. This is useful for testing APIs that handle file transfers, such as images or documents.

Where it's useful: Testing file upload functionality in services like cloud storage.

6. Automated Response Validation (Test Scripts)

You can write JavaScript test scripts to validate API responses automatically. For example, you can check the status code, response structure, or specific field values.

Where it's useful: Creating functional API tests and validating returned data.

_7. CI/CD Integration _

Postman collections can be easily integrated with Jenkins, GitLab CI/CD, or other CI/CD tools. This automates API testing with every code commit.

Where it's useful: For full API test automation as part of your deployment pipeline.

Postman is more than just a request runner—it's a full-featured API testing and automation platform. What's your favorite hidden feature?

The Testing Pyramid: A Strategic Approach to Efficient Software Testing

Alexi — Tue, 07 Apr 2026 09:14:57 +0000

Software testing is essential for ensuring a product's functionality and quality, but how do we optimize it to catch issues at the early stages of development? The answer is the Testing Pyramid.

According to the ISTQB glossary, the Testing Pyramid is "A graphical model representing the relationship of the amount of testing per level, with more at the bottom than at the top." In simpler terms, the Testing Pyramid prioritizes smaller, automated tests at the base and progressively fewer, more complex tests as you move up. Here's a closer look at the levels and benefits of this approach:

Levels of Testing Pyramid

*1. Unit Testing *

Unit testing is the primary testing phase in software development. It focuses on independently testing individual software units or components to ensure correct functionality and accurate output. Developers regularly create and execute unit tests using automated testing tools to streamline the testing process

*2. Integration Testing *

Following unit testing, integration testing focuses on how different software components interact. This phase helps catch any issues arising when these units are combined, ensuring that your system's parts work smoothly.

*3. System Testing *

System testing assesses the entire software system to validate its functionality against specified requirements. This testing phase ensures all components are properly integrated, and the software operates as intended in the target environment.

*4. Acceptance Testing *

Acceptance testing is the last level to ascertain whether the software is ready for deployment to production. It confirms whether the software aligns with business requirements and adequately meets user needs.

Why Use the Testing Pyramid?

Logical framework: The testing pyramid provides a clear framework for prioritizing different levels of testing. It recommends executing smaller, simpler tests (unit tests) first while reserving more complex tests (integration and end-to-end tests) for later stages.

Early feedback: The testing pyramid allows testers to receive prompt feedback on application performance by integrating tests at various stages of the software development cycle. This rapid detection and resolution of defects ensure the delivery of a high-quality product to the user by addressing issues early in the development process.

Enhanced test coverage: The pyramid ensures broad test coverage across the entire application by testing at multiple levels. This comprehensive approach identifies potential risks in various components early on.

Cost efficiency: Early bug detection through unit tests minimizes the cost of fixing defects, as issues are identified before they escalate into more significant problems later in the development cycle.