manual testing Archives

Mutant Testing A QA Engineer’s Honest Experience With Smarter Testing

I still remember the day I first came across the term Mutant Testing. It popped up in a technical discussion, and for a moment, I thought someone was joking. “Mutation? Like genetics?” But once I dug deeper, it changed the way I evaluate test cases—even after years of living and breathing software quality assurance.

Mutant testing didn’t just teach me about code strength.
It taught me something about the assumptions we quietly carry in our work.

🔍 What Mutant Testing Really Means

Think of mutation testing as a smart way of challenging your test suite.

You take a piece of working code, create small intentional changes—called mutants—and then run your test cases to see if they catch the errors.

It’s like checking your home security system by trying different “fake break-ins” to see if the alarm works.

For example, suppose the original code is:

if (age > 18)

A mutant might be:

if (age >= 18)

Now you ask:
Do your tests detect this as wrong?
If the answer is no, that means your test suite isn’t strong enough—even if it looks complete on paper.

🧪 My First Real Experience With Mutant Testing

Years ago, we were preparing a system for a major release. The team trusted our regression suite because it had grown over many sprints. Automation scripts were stable, and manual tests were documented neatly.

Yet something didn’t feel right. The green passing results felt too… easy.

That’s when I decided to try mutant testing on one module. I didn’t use a tool at first—I manually created small code variations just to experiment.

When I ran the tests, several mutants survived.

Not one or two.
Enough to make me pause and rethink.

Some mutants were simple logic flips. Others were boundary changes. The results showed us one clear truth:

We had test cases, but we didn’t have strong coverage.
That’s the day I realized how mutation testing “humbles” even the most experienced QA engineer.

🎯 What Mutant Testing Revealed About Our Tests

The surviving mutants highlighted things we didn’t see during routine test writing:

✔ 1. Missing Negative Cases

Many tests validated only the happy path.
When we flipped conditions (like > to >=), tests passed quietly.

✔ 2. Weak Assertions in Automation

The UI tests walked through the correct flows, but our assertions were too soft.
The tests said “Pass” even when logic behind the UI changed.

✔ 3. Boundary Blind Spots

For example, a discount logic:

if (amount >= 1000)

When mutated to:

if (amount > 1000)

our tests didn’t catch the difference because we didn’t test at exactly 1000.

✔ 4. Overconfidence

We assumed certain parts of the code were too “simple” to break.
The mutants proved how dangerous assumptions can be.

Mutant testing didn’t just expose gaps—it improved our mindset.

🛠 Can Mutant Testing Be Done Manually? Absolutely.

You don’t need fancy tools to understand mutation testing.
In fact, my very first experiment was done manually.

Here’s how you can do it yourself:

Pick a small piece of logic.
Change one operator, condition, or value.
Run your existing test cases.
See whether they fail.

If they fail → your test suite “killed” the mutant.
If they pass → the mutant “survived,” meaning your tests need improvement.

Manual Mutation Example

Original code:

if (score == 50)
    grade = "Pass";

Manual mutant:

if (score != 50)
    grade = "Pass";

If your tests don’t catch this, you’re missing critical negative tests.

When Manual Testing Works

Small modules
Critical calculations
Teaching junior testers
Quick validation before writing automation

When Manual Testing Fails

Large projects
Frequent code changes
CI/CD environments
Time-sensitive releases

This is where automated mutation testing tools shine.

⚙️ Tools That Bring Mutation Testing to Life

If you want to automate mutation testing (and save yourself hours), here are great tools:

Stryker.NET (C#/.NET)
PIT / Pitest (Java)
MutPy (Python)
Cosmic Ray (Python)
Major (Java)

Among these, Stryker.NET is my go-to because of its clean dashboard and simple CI integration. It visually shows which mutants were killed, which survived, and how strong your test suite truly is.

💡 A Little Story: How One Mutant Saved Us

During one release cycle, a small change was introduced in a permission rule.
A mutant flipped the condition from:

if(hasAccess)

to:

if(!hasAccess)

Shockingly, our test suite didn’t notice.

When investigating, we realized the logic itself had a deeper flaw—and would have caused real access issues for users.

The mutant didn’t just survive.
It exposed a real production bug we had overlooked.

After that, even developers started appreciating mutation results.
Mutant testing slowly became part of our quality culture.

🧠 Lessons Mutant Testing Taught Me About QA

Over the years, this technique shaped how I think about quality:

✔ Strong code coverage doesn’t guarantee strong testing

Mutation score tells the real story.

✔ Negative tests matter more than we think

Most surviving mutants point directly to missing negative cases.

✔ Assertions must be meaningful

Not just “page loaded,” but “logic validated.”

✔ Quality grows when we challenge assumptions

Mutant testing forces you to think like a real bug.

✔ A weak test suite is more dangerous than a bug

Because it gives a false sense of safety.

🚀 How You Can Start With Mutant Testing

Here’s a simple roadmap I always recommend:

Start with one module—not the whole system.
Focus on small logical blocks or critical business rules.
Run mutants manually or with tools.
Review every survivor with developers.
Strengthen your test cases intentionally.
Add mutation testing into CI once stable.
Track mutation score just like code coverage.

You’ll see improvements quickly—sometimes within a single sprint.

🔚 Final Thoughts

Mutant testing isn’t just a technique.
It’s a mindset.

It pushes you to think deeper, write smarter test cases, and remove overconfidence from your QA process. Whether you try it manually or with tools, it reveals blind spots that traditional testing often misses.

If you’re serious about improving test quality—not just expanding the number of test cases—mutation testing is one of the most powerful steps you can take.

Why Hard Work is Essential in Quality Assurance: Avoiding the Pitfalls of “Looking Sharp”

Introduction: The Truth Behind “Looking Sharp” in QA

In the world of Quality Assurance (QA), it’s easy to look sharp without doing the actual work. You might be using fancy tools, running automated tests, or showing off your shiny bug-tracking system—but if you haven’t done the deep, thorough testing, it’s just surface-level work. Much like a pencil that appears sharp but isn’t properly sharpened, some QA processes might look polished but aren’t doing the heavy lifting required to ensure quality.

In this blog, we’ll break down why QA isn’t about looking good—it’s about the work you put in behind the scenes. It’s the hard work, attention to detail, and constant improvement that separate good QA teams from great ones.

The Danger of “Looking Sharp” Without the Work

The phrase “It’s easy to look sharp when you haven’t done any work” perfectly captures a dangerous mindset in QA. Many teams focus on external tools and metrics—like automated tests that pass quickly or bug-tracking systems that are well-organized—thinking that these are signs of good QA. But these tools are only helpful when they’re used properly.

A sharp pencil looks great, but it won’t get any work done unless it’s used. Similarly, just running automated tests or following basic guidelines without deeper analysis can create the illusion of quality, without actually catching all potential issues.

True QA requires more than just passing automated tests or generating bug reports. It requires diligent work, attention to detail, and a commitment to continuous improvement.

What Real Diligence in QA Looks Like

Effective QA isn’t about checking a box and moving on—it’s about ensuring that every feature works as expected, and every potential issue is addressed. Let’s break down the key areas that require hard work and dedication in QA:

1. Comprehensive Testing: Going Beyond the Basics

To deliver real quality, testing needs to be thorough. Relying only on surface-level checks or automated tests might miss edge cases that can cause big problems later on. QA professionals should test everything from unit tests to integration tests, and even perform exploratory testing to uncover hidden issues.

It’s about testing in real-world conditions—ensuring that the app or product behaves as expected when used by a variety of people in different environments.

2. Manual vs Automated Testing: Finding the Right Balance

Automation can be a huge help, but it can’t catch everything. Automated tests excel at repetitive tasks, but they miss the finer details of user interaction and UX. Manual testing is still needed to check how users experience the software. For instance, testers can evaluate how intuitive an interface is, or check if the software performs well on different devices.

QA should focus on a balance—automating repetitive tests while still leaving room for manual testing to cover areas that automation can’t.

3. Continuous Improvement: QA Is an Ongoing Journey

Quality assurance is never a one-time event. Just like a pencil needs to be sharpened regularly, QA processes need constant refinement. After every release, teams should reflect on what went well, what didn’t, and how they can improve next time.

Staying updated with the latest tools and methodologies, learning from past mistakes, and adapting to user feedback are all essential components of continuous improvement in QA.

4. Traceable Documentation: Clear and Detailed Bug Reports

When bugs are found, they need to be thoroughly documented. This includes providing detailed descriptions of the issue, steps to reproduce it, and potential fixes. Clear documentation helps ensure that nothing gets missed and that bugs don’t resurface in future releases.

Good documentation also helps with tracking progress and ensuring accountability. It’s not enough to find issues—teams must also ensure they’re being properly addressed and tracked.

5. Collaboration: Working Together for Better QA

QA doesn’t work in a silo. It requires collaboration with developers, product managers, and other stakeholders to understand the project’s goals and ensure that testing aligns with those goals.

Clear communication throughout the development cycle helps avoid misunderstandings and ensures everyone is on the same page. When QA teams collaborate closely with developers, it’s easier to catch issues early and fix them before they become bigger problems.

Avoiding Common Pitfalls in QA

While striving for sharpness is important, many teams fall into common traps that make their QA efforts less effective. Here are some pitfalls to watch out for:

1. Over-Reliance on Automation

Automation is great for speed, but it shouldn’t be the only method used in QA. Some parts of testing, like user experience and complex functionality, are better suited for manual testing. Relying too heavily on automation can lead to overlooked issues.

2. Neglecting the User Experience

Sometimes, teams get so focused on technical requirements that they forget about the user. QA should ensure that the product isn’t just functional—it should be user-friendly and easy to navigate. Neglecting UX can result in frustrated users, even if the software works perfectly technically.

3. Skipping Regression Tests

When new features are added, old ones can sometimes break. Regression testing helps ensure that new changes don’t interfere with existing functionality. Skipping this step can lead to serious problems down the line.

4. Failing to Learn from Mistakes

QA is an evolving process. The tools, techniques, and practices that worked last year might not be effective today. Teams should always be learning and adapting—whether it’s refining testing strategies, incorporating user feedback, or staying updated on new testing tools.

The Evolving Role of QA in Software Development

QA is no longer just a final check before shipping a product. With modern development methods like Continuous Integration and Continuous Deployment (CI/CD), QA is integrated into every part of the development lifecycle. QA professionals now need to test early, test often, and test continuously to ensure that the product meets high standards at every stage.

This means QA teams need to work closely with developers, ensuring that tests are automated where possible and executed regularly throughout the development process. This helps catch issues early, making the development cycle faster and more efficient.

Conclusion: The Power of Diligence in QA

Looking sharp in QA isn’t the goal—doing the hard work that guarantees a top-quality product is what matters. By focusing on comprehensive testing, balancing automation with manual checks, and embracing continuous improvement, QA professionals can deliver software that works seamlessly and meets user expectations.

Learn Test Data Management (TDM) the Easy Way: For QA Beginners

In software testing, having the right data is just as important as having the right test cases. If you’re testing a banking app, you can’t do much without having accounts, balances, and transaction histories to work with.

This is where Test Data Management (TDM) becomes crucial.

📘 What is Test Data Management (TDM)?

Test Data Management (TDM) is the process of:

Creating,
Maintaining,
Storing, and
Using data specifically for software testing.

It ensures testers have access to clean, relevant, and secure test data that simulates real-world scenarios without affecting live systems.

🔎 Real-Life Analogy

Imagine testing an online shopping website. Here’s the kind of test data you’ll need:

User accounts (names, emails, passwords)
Products (name, price, stock count)
Orders (status, payment type)
Shipping info

Without this data, testing will either fail or give false results.

🎯 Why is Test Data Management Important?

Benefits	Explanation
🎯 Increases test accuracy	Well-prepared data helps testers find real bugs.
⏱️ Saves time	Testers don’t waste time creating or searching for data.
🔐 Ensures security	Sensitive info (like customer data) is hidden or masked.
🔁 Supports automation	Automated tests run better with reusable data.
⚙️ Boosts test coverage	Different types of data (valid, invalid, edge cases) cover more scenarios.

🧪 Types of Test Data You’ll Use

Type	Example	Purpose
Valid data	Correct username/password	Checks positive flows
Invalid data	Wrong password, invalid email	Tests error handling
Boundary data	0, 1, 1000 items	Tests system limits
Null values	Empty fields	Tests mandatory validations
Duplicate data	Same phone number or email	Tests uniqueness validations

🛠️ Ways to Generate Test Data

Manual Entry:
You enter data by hand. Best for small tests.
Example: Fill out a form with sample name, email.
Copy from Production (Masked):
Real user data copied after hiding private info.
Example: Replace real names with fake ones, but keep structure.
Data Generation Tools:
Auto-generate data using tools or scripts.
Examples: Faker (Python/JS), Mockaroo, SQL scripts.
Automated Data Loaders:
Write scripts to load data directly into the database.

🔐 Test Data Security: Why It Matters

Using real customer data in testing is risky.
Leaks can violate privacy laws (like GDPR).
Always mask or anonymize sensitive data.

✅ Best Practice: Replace “John Doe” with “TestUser001” and remove real emails or phone numbers.

🧩 Common Challenges in TDM

Challenge	Explanation	Tip
Data duplication	Too many copies slow down testing	Use version control for data sets
Outdated data	Tests may fail if data is old	Automate regular data refresh
Environment mismatch	Data works in one test server, fails in another	Standardize environments
Poor data masking	Real names, emails visible	Use masking tools or scripts

🚀 TDM Tools for Beginners

Tool	Use Case
Mockaroo	Generate fake data (CSV, JSON, SQL)
Faker	Programmatically create data in Python/JS
Katalon TestOps	Test management + data handling
Delphix / Informatica	Advanced data virtualization (for enterprises)
PostgreSQL/MySQL scripts	Generate data using SQL for back-end tests

🧠 Quick Tips for Fresher Testers

✅ Use unique and clear naming in test data. (e.g., User_Test001)
✅ Always document test data used in each case.
✅ Try to reuse test data across test cycles.
✅ When in doubt, ask for sample datasets from your dev team.
✅ Learn simple data generation tools — they will save your time.

📌 TDM in Agile and Automation

TDM plays a major role in:

Agile testing (frequent releases = frequent test data needs)
CI/CD pipelines (automated tests need stable and reusable data)
Automated UI/API tests (data setup and teardown is crucial)

Example: Before each automated test, generate test users via API → run test → delete users post-test.

✅ Summary: TDM at a Glance

Feature	Value
Definition	Managing test-specific data for quality testing
Importance	Ensures effective, fast, and secure testing
Who needs it?	Manual testers, automation engineers, QA leads
Must-know for	Freshers, QA interns, SDETs, Test Managers

💬 Final Thoughts

Test Data Management may sound like a technical term, but it’s simply about being prepared with the right data before testing anything. If you’re a fresher in the QA world — learning TDM will help you become more confident, efficient, and reliable as a tester.

Understanding the Difference Between SDET and QA Analyst: The Essential Roles in Software Testing

In the fast-paced world of software development, ensuring the quality of a product is paramount. Software testing plays a crucial role in identifying defects, improving usability, and verifying the functionality of an application. However, within the field of software testing, two roles often cause confusion: Software Development Engineer in Test (SDET) and Quality Assurance (QA) Analyst. While both aim to deliver high-quality software, their approaches, skill sets, and responsibilities differ significantly. This article aims to clarify these differences and shed light on the impact each role has in modern software development.

What is a QA Analyst?

A Quality Assurance Analyst (QA Analyst) focuses on ensuring that the product meets user expectations, functional requirements, and overall usability. They are primarily concerned with manual testing and exploratory testing, evaluating the product from the end user’s perspective.

Key Responsibilities of a QA Analyst:

– Manual Testing: QA Analysts execute test cases manually to identify defects and ensure that the software meets its functional requirements. Manual testing is essential when testing user interfaces, workflows, and usability aspects that are challenging to automate. – Test Case Design: They write and design detailed test cases based on requirements, ensuring comprehensive coverage of the application’s functionality. – Exploratory Testing: QA Analysts engage in unscripted, exploratory testing to uncover potential edge cases and usability issues that automated tests may not identify. – Collaboration with Teams: They work closely with product owners, developers, and designers to validate workflows and ensure the application is user-friendly. – Bug Reporting and Tracking: Defects found during testing are logged, tracked, and managed using tools like JIRA, ensuring they are addressed before release.

Tools and Skills Used by QA Analysts:

– JIRA for bug tracking and project management. – TestRail for test case management and reporting. – Postman for API testing. – Knowledge of manual testing methodologies and test execution.

When is a QA Analyst Most Valuable?

– Small to medium-sized applications. – Early-stage projects where the product’s user interface and usability need detailed testing. – Projects that require human intuition for exploring new features and identifying potential user experience issues.

What is an SDET?

A Software Development Engineer in Test (SDET) is a specialized role that bridges the gap between development and testing. SDETs focus on test automation, creating frameworks and tools that ensure continuous testing across various stages of the Software Development Life Cycle (SDLC). They possess strong software development skills and are heavily involved in CI/CD pipelines, ensuring that quality is maintained at every stage of the development process.

Key Responsibilities of an SDET:

– Test Automation: SDETs write automated test scripts for unit tests, integration tests, UI tests, and performance tests. Automation significantly speeds up testing cycles and ensures comprehensive test coverage. – CI/CD Integration: SDETs are involved in setting up and maintaining Continuous Integration (CI) and Continuous Delivery (CD) pipelines. They ensure that automated tests are executed whenever code is integrated, allowing for fast feedback. – Building Test Frameworks: SDETs develop reusable test frameworks that can be applied across different projects, making it easier to scale testing as the application grows. – Performance and Load Testing: They also conduct performance tests, stress tests, and load tests to ensure the application can handle high traffic and remains stable under peak loads. – Shift-Left Testing: SDETs work alongside developers to shift testing earlier in the SDLC, allowing defects to be identified and fixed earlier in the development process, which reduces costs and speeds up time-to-market.

Tools and Skills Used by SDETs:

– Automation Tools: Selenium, Cypress, Playwright, Appium for automating UI and API tests. – CI/CD Tools: Jenkins, GitLab CI, CircleCI, Travis CI for integrating tests into the development pipeline. – Languages: Proficiency in programming languages like JavaScript, Python, Java, and C#. – Containerization: Tools like Docker and Kubernetes for creating test environments and ensuring tests run in consistent conditions.

When is an SDET Most Valuable?

– Large, complex applications where manual testing becomes inefficient. – High-velocity teams in Agile or DevOps environments, where quick releases and continuous testing are necessary. – Applications that require extensive automated regression, load, and performance testing.

Key Differences Between QA Analysts and SDETs

Which Role is More Impactful in Today’s Development Environments?

The importance of each role largely depends on the nature of the project and the testing strategy adopted by the organization. – SDETs are crucial in large-scale, fast-paced environments, especially with frequent code changes and deployments. They enable continuous testing and feedback, which is essential in Agile and DevOps settings. Automation not only saves time but also increases test coverage, ensuring that defects are caught early in the development process. – QA Analysts remain invaluable for manual testing, especially in validating user experience, UI consistency, and edge-case scenarios that may be difficult to automate. Conclusion: Both SDET and QA Analyst roles are essential for delivering high-quality software. While the SDET role is focused on automation and scalability, the QA Analyst role ensures that the product is user-friendly and meets functional specifications. The key to success lies in the collaboration between these two roles, ensuring that software is thoroughly tested, performs well, and delivers a seamless experience to users.

Why Software Testing is the Backbone of Successful Tech Companies

More and more technological focus is on software and practically every business and industry today have software at its core. Companies ranging from those in the finance sector, or even healthcare, and extending to e-commerce and education sectors are relying more and more on complex and efficient software systems to be able to use their resources effectively, create value for their clients, and be competitive on the market. Still, in spite of the many benefits that software offers, there are some down sides especially if the software is inadequately tested. Repercussions face businesses due to bugs, security holes, performance issues and other disruptive factors. This is the reason why software testing has become the lifeline and the Most Important Function of Tech Companies It Ensured the reliability of products and their competitive position with regard to the quality of the user experience.

Preventing Catastrophic Failures

A major responsibility that software testers must take up is to ensure that any form of deviation or defect is rectified before the software is deployed. One software bug can create chaos and lead to loss of money, loss of image, and may even lead to costly lawsuits. For instance, in 2012, a software bug at Knight Capital Group made the company lose 440 million dollars within a span of just 45 minutes, which almost brought the firm to its knees. Also, a similar lack of attention to software in the healthcare industry can cause fatalities by making unsubstantiated proposals on treatments or even miss critical medical conditions. These are among the things that make companies look the other way when it comes to making cuts on testing.

Problems of this type can be avoided in the first place by testing various properties early in the software development process. It makes certain that the systems perform as expected in a variety of situations and circumstances. For technology firms, user-initiated disruptions are not only futile, but also undesirable if continuity of customer trust is to be maintained, which in turn lends itself to competitiveness against other firms as well as maximizing overall revenue.

Enhancing User Experience (UX)

As the world is becoming a global marketplace, user experience (UX) has become the most important key competitive advantage for any online business. Today’s consumers will leave applications, sites, or platforms that perform even a tad slow, have bugs, or are cumbersome to use in a heartbeat. This is where software testing comes in. It guarantees that the applications perform within acceptable limits, are usable on different devices and are usable in smooth ways.

Usability testing is among the biggest ways targeted at making sure that the software is the right fit for the targeted users. This helps companies discover and adjust any design or navigation problems that would irritate users or affect their experience. Also, performance testing also assesses the way the application behaves under a heavy load, in order to make sure that it will withstand the highest volume of use. All these tests help in building up the user-friendly components of a product leading to increased user retention and customer loyalty as well.

Supporting Agile and DevOps Methodologies

There is an increase in the implementation of both Agile and DevOps as methods of development in the tech firms. Especially, these methodologies include building and deploying applications incrementally through constant refinement and relentless deployment. Nevertheless, without constant verification and validation, it would be close to impossible to keep the quality of software in such a velocity-oriented environment.

Testing is there in the whole life cycle of development in practice and DevOps. Various tools for conducting tests automatically check the effectiveness of the new code, evaluate the code for faults, and verify that the added features do not interfere with any of the previous features. With this level of testing, companies can release more updates frequently while maintaining the quality level. It also allows them to accommodate customer requirements quickly thus improving the development time.

Ensuring Security in an Increasingly Digital World

The increasing inter-connectedness of the world has exposed software companies to security threats and as such, the security concerns keep changing. Information security breaches can result in great risks like compromising large amounts of data, exposing very private data to unauthorized people and the strenuous process to repair the damage done to the corporation’s reputation. Hence, this leads to Security testing being recognized as an essential part of the overall comprehensive testing process.

Security testing confirms the prevention of such defects in the software system, which can open up certain user’s vulnerabilities to external people with malicious aspirations. And, it provides measures to ensure sensitive information security, correct enforcement of user permissions, and protection against hacking attacks in the systems. For technology companies, the requirement for such analysis is not only the safety of users – it is rather fundamental for the security of the organization itself and for foreseeing such damaging things as legal consequence as a result of data leakage.

Reducing Long-Term Costs

Towards this goal, some companies take it as an unnecessary cost, Jeanie Noe Pahutan asserts that the opposite is true. This is why it is vital to deal with a defect as early as possible during the software lifecycle. Studies show that the cost of adjusting post-verification errors can rise to 30 times more than appropriating these errors as they occur in the coding activity. A reason for this is that such problems are usually at the later stages of the cycle, which usually leads to having to change several stages that come after it, which makes the development and release of the product take longer than planned.

Testing helps prevent companies from releasing products with bugs and later putting up very extravagant and unnecessary post-release patching or emergency bug fixing. Also, it lessens the amount of support and maintenance that will be needed once the product has been released to its intended users. In the end, testing helps achieve the objectives of the technology companies as they are able to release high quality software without having to keep spending resources in correcting errors.

Driving Innovation with Confidence

At last, let us look at one more aspect that is so often underappreciated – software testing and its contribution to innovation. If companies are confident with the stability and security of the prolusion software, they are able to extend the limits, so to say. New features or new technologies can be tested by developers without a fear of causing a disruptive change. Testing offers a cushion that gives companies the ability to be very aggressive on innovation and yet ensure quality.

The process of testing has also become highly effective and extensive with the introduction of test automation. As opposed to state manual testing where only a limited number of tests can be performed, automated testing can achieve this within a number of minutes due to the fact that pre-scripted tests are controlled by a program which also gives a result. This enables technology firms to continue living with the reality of ever achieve enhancement of their systems by releasing novel modifications sequentially in constant terms to outpace their rivals.

Conclusion

Testing software cannot be viewed merely as a process of performing many chores — it is an activity that determines how successful tech companies will be. It avoids expensive mistakes and poor usability, embraces Agile and DevOps processes, secures systems and promotes creativity. In the business where the pace, consistency, and users’ trust matter most — software testing is a core practice that focuses on the long-term health of the business. Businesses that choose to adopt an effective test strategy would not only mitigate risks but also create an opportunity that will better their prospects and foster creativity.