#software testing program

[katzensilber]

Man, this is why I always hated math class.

Khan Academy gave me this easy (or so I thought) problem to solve:

"A factory makes toys that are sold for $10 a piece. The factory has 40 workers, and they each produce 25 toys a day. The factory is open 5 days a week. What is the total value of toys the factory produces in a day?"

I said to myself, okay...

10 times 40 times 25 equals 10,000. That means the factory produces $10,000 worth of value per WORKING day.

10,000 times 5 equals 50,000. And then there are two days per week (the weekend) when no value is produced. So, per week, the total value produced is still only $50,000.

And finally, there are seven days in a full week, so $50,000 divided by 7 equals roughly $7,142.86. That's the total value of toys produced per day. Not "per work day", but "per day", as it specifically says in the problem.

But what does the teacher say as he guides us through it? 10 times 40 times 25 equals 10,000, so the answer is 10,000.

That's it. The end.

He even acknowledges: "So, you might be thinking, 'Hey wait, we didn't use all the information! We didn't use the "five days per week" information!' And yeah, as it turns out, that was information we didn't need."

'As it turns out'?! Are you kidding me right now?! I carefully read the question, precisely calculated exactly what it was asking for, taking all of the provided information into account... and now you're saying I'm supposed to have somehow magically known to ignore one of those pieces of information in order to make it easier for myself?

Just admit that your problem is worded badly, dude. UGH this kind of shit drives me crazy. Why can't people use words clearly >:(

[realbadatpoker]

My software design process is like 90% "what will take the least amount of effort to implement and test" and I think this is morally correct, actually

[multidimensionalsock]

Types of software testing

As well as the different types of tests there are, there are categories of software testing: manual and automated.

Manual testing

Manual tests are tests that are ran by a human, generally a set of steps is listed with expected results, and someone will run through them confirming if each step has passed or failed.

Manual testing is good for testing things visual elements, giving fast and accurate visual feedback which is closer to how a user would use the software. It's also good for unplanned changes, updating automated test scripts for projects which are changing a lot can be extremely costly.

The human element of Manual testing means that testing can be dynamic, and if an issue is picked up that wasn't necessarily part of the test, it can be raised accordingly. Manual testing is also needed to triage when automation tests have failed, manually running through tests to see the point of failure, if it's a bug or an issue with the automation test, and raising it accordingly.

Automation testing

Automation testing is when tests are written out to be performed by a computer each time they're needed. For example, sending a certain set of inputs to an API and checking it returns what we expect. Automated tests still need to be written by a human, some require a programmer to write each step of the test, some might use frameworks like Gherkin to write tests in human language linked to code in the background.

Automation testing can be a lot quicker than manual testing, which also means more test coverage can be increased. Once the test cases are written out they can then be run anytime they're needed to make sure a software is still behaving as expected, especially after any changes are made to ensure existing functionality wasn't broken unintentionally. Automation testing also allows for tests to be running constantly in the background to pick up any possible faults which can then be triaged.

[angelcoupon]

i dropped my cashews i think this is it for me bye guys #kms

[firstbitsolutions]

Which is better full stack development or testing?

Full Stack Development vs Software Testing: Which Career Path is Right for You?

In today’s rapidly evolving IT industry, choosing the right career path can be challenging. Two popular options are Full Stack Development and Software Testing. Both of these fields offer unique opportunities and cater to different skill sets, making it essential to assess which one aligns better with your interests, goals, and long-term career aspirations.

At FirstBit Solutions, we take pride in offering a premium quality of teaching, with expert-led courses designed to provide real-world skills. Our goal is to help you know, no matter which path you choose. Whether you’re interested in development or testing, our 100% unlimited placement call guarantee ensures ample job opportunities. In this answer, we’ll explore both career paths to help you make an informed decision.

Understanding Full Stack Development

What is Full Stack Development?

Full Stack Development involves working on both the front-end (client-side) and back-end (server-side) of web applications. Full stack developers handle everything from designing the user interface (UI) to managing databases and server logic. They are versatile professionals who can oversee a project from start to finish.

Key Skills Required for Full Stack Development

To become a full stack developer, you need a diverse set of skills, including:

Front-End Technologies: HTML, CSS, and JavaScript are the fundamental building blocks of web development. Additionally, proficiency in front-end frameworks like React, Angular, or Vue.js is crucial for creating dynamic and responsive web interfaces.

Back-End Technologies: Understanding back-end programming languages like Node.js, Python, Ruby, Java, or PHP is essential for server-side development. Additionally, knowledge of frameworks like Express.js, Django, or Spring can help streamline development processes.

Databases: Full stack developers must know how to work with both SQL (e.g., MySQL, PostgreSQL) and NoSQL (e.g., MongoDB) databases.

Version Control and Collaboration: Proficiency in tools like Git, GitHub, and agile methodologies is important for working in a collaborative environment.

Job Opportunities in Full Stack Development

Full stack developers are in high demand due to their versatility. Companies often prefer professionals who can handle both front-end and back-end tasks, making them valuable assets in any development team. Full stack developers can work in:

Web Development

Mobile App Development

Enterprise Solutions

Startup Ecosystems

The flexibility to work on multiple layers of development opens doors to various career opportunities. Moreover, the continuous rise of startups and digital transformation initiatives has further fueled the demand for full stack developers.

Benefits of Choosing Full Stack Development

High Demand: The need for full stack developers is constantly increasing across industries, making it a lucrative career choice.

Versatility: You can switch between front-end and back-end tasks, giving you a holistic understanding of how applications work.

Creativity: If you enjoy creating visually appealing interfaces while also solving complex back-end problems, full stack development allows you to engage both creative and logical thinking.

Salary: Full stack developers typically enjoy competitive salaries due to their wide skill set and ability to handle various tasks.

Understanding Software Testing

What is Software Testing?

Software Testing is the process of evaluating and verifying that a software product or application is free of defects, meets specified requirements, and functions as expected. Testers ensure the quality and reliability of software by conducting both manual and automated tests.

Key Skills Required for Software Testing

To succeed in software testing, you need to develop the following skills:

Manual Testing: Knowledge of testing techniques, understanding different testing types (unit, integration, system, UAT, etc.), and the ability to write test cases are fundamental for manual testing.

Automated Testing: Proficiency in tools like Selenium, JUnit, TestNG, or Cucumber is essential for automating repetitive test scenarios and improving efficiency.

Attention to Detail: Testers must have a keen eye for identifying potential issues, bugs, and vulnerabilities in software systems.

Scripting Knowledge: Basic programming skills in languages like Java, Python, or JavaScript are necessary to write and maintain test scripts for automated testing.

Job Opportunities in Software Testing

As the demand for high-quality software increases, so does the need for skilled software testers. Companies are investing heavily in testing to ensure that their products perform optimally in the competitive market. Software testers can work in:

Manual Testing

Automated Testing

Quality Assurance (QA) Engineering

Test Automation Development

With the rise of Agile and DevOps methodologies, the role of testers has become even more critical. Continuous integration and continuous delivery (CI/CD) pipelines rely on automated testing to deliver reliable software faster.

Benefits of Choosing Software Testing

Job Security: With software quality being paramount, skilled testers are in high demand, and the need for testing professionals will only continue to grow.

Quality Assurance: If you have a knack for perfection and enjoy ensuring that software works flawlessly, testing could be a satisfying career.

Automated Testing Growth: The shift toward automation opens up new opportunities for testers to specialize in test automation tools and frameworks, which are essential for faster releases.

Flexibility: Testing provides opportunities to work across different domains and industries, as almost every software product requires thorough testing.

Full Stack Development vs Software Testing: A Comparative Analysis

Let’s break down the major factors that could influence your decision:

Factors

Full Stack Development

Software Testing

Skills

Proficiency in front-end and back-end technologies, databases

Manual and automated testing, attention to detail, scripting

Creativity

High – involves creating and designing both UI and logic

Moderate – focuses on improving software through testing and validation

Job Roles

Web Developer, Full Stack Engineer, Mobile App Developer

QA Engineer, Test Automation Engineer, Software Tester

Career Growth

Opportunities to transition into senior roles like CTO or Solution Architect

Growth towards roles in automation and quality management

Salary

Competitive with wide-ranging opportunities

Competitive, with automation testers in higher demand

Demand

High demand due to increasing digitalization and web-based applications

Consistently high, especially in Agile/DevOps environments

Learning Curve

Steep – requires mastering multiple languages and technologies

Moderate – requires a focus on testing tools, techniques, and automation

Why Choose FirstBit Solutions for Full Stack Development or Software Testing?

At FirstBit Solutions, we provide comprehensive training in both full stack development and software testing. Our experienced faculty ensures that you gain hands-on experience and practical knowledge in the field of your choice. Our 100% unlimited placement call guarantee ensures that you have ample opportunities to land your dream job, no matter which course you pursue. Here’s why FirstBit is your ideal training partner:

Expert Trainers: Learn from industry veterans with years of experience in development and testing.

Real-World Projects: Work on real-world projects that simulate industry scenarios, providing you with the practical experience needed to excel.

Job Assistance: Our robust placement support ensures you have access to job openings with top companies.

Flexible Learning: Choose from online and offline batch options to fit your schedule.

Conclusion: Which Career Path is Right for You?

Ultimately, the choice between full stack development and software testing comes down to your personal interests, skills, and career aspirations. If you’re someone who enjoys building applications from the ground up, full stack development might be the perfect fit for you. On the other hand, if you take satisfaction in ensuring that software is of the highest quality, software testing could be your calling.

At FirstBit Solutions, we provide top-notch training in both fields, allowing you to pursue your passion and build a successful career in the IT industry. With our industry-aligned curriculum, expert guidance, and 100% placement call guarantee, your future is in good hands.

So, what are you waiting for? Choose the course that excites you and start your journey toward a rewarding career today!

[syncrovoid-presents]

I will continue being gone for a few days, sadly my original al plan of releasing the newest chapter of The Consequence Of Imagination's Fear has also been delayed. My apologies

Can't go into detail because its hush hush not-legally-mentionable stuff but today is my fifth 12 hour no-break work day. I'm also packing to move too in a fortnight (which is a Big Yahoo!! Yippee!! I'll finally have access to a kitchen!! And no more mold others keep growing!!! So exciting!!!)

[arifinfrds-blog]

Maintaining fast unit test feedback is crucial as an app and team grow over time. Without proper modularization, unit testing can become painfully slow. By structuring code into independent modules and utilizing macOS-based testing strategies, we can drastically improve test execution speed. This results in faster development, quicker bug fixes, and a smoother engineering experience. If you’re working on a growing iOS project, now is the time to start modularizing. Not only will it save you time today, but it will keep your project maintainable and efficient as your team and codebase scale. Start with one module, test the benefits, and see the difference! 🚀

[moose-mousse]

THE FIRST VERSION OF THE CODE SHOULD LOOK LIKE CRAP!

PRACTICE WRITING CRAP CODE AND FIXING IT AS A DESIGN METHOD!

IT IS CALLED TEST DRIVEN DESIGN!

[scriptingthewhy]

Navigating the Nervous Waters of Coding

Daily writing promptWhat makes you nervous?View all responses AI-generated image. “This code is going well…a little too well.” The Code Creep: Why Every Line Can Feel Like a Tightrope Walk What makes me nervous? You might think it’s a looming deadline or a particularly gnarly algorithm. And while those definitely get the heart racing, the real source of my coding jitters? It’s the act of…

[multidimensionalsock]

Black box, white box and grey box testing

In manual testing, there is three main methodologies based on how much the testers knows about how the software works.

Black box testing

The lowest level of knowledge on how the software works is black box testing, testers are given a specification to work from, and they have to make sure the software can do all of the requirements and works as expected.

In black box testing, testers do not know how the software is working inside. This can make planning how to test harder as some test cases may cover situations that could never happen based on how it's programmed, leading to redundant testing.

White box testing

White box testing, or clear box testing, is the complete opposite to Black box. Testers are given access to the source code and the full inner workings of the software. This allows for testing on a granular level and analysis of the code to find any issues, weaknesses in design or inefficiencys that may not be as easily picked up by testing from the front end.

It requires knowledge of programming and can be time consuming compared to more common forms of manual testing.

Grey box testing

Grey box testing is the midpoint of black box and white box. The tester is not given access to the source code, but is given an idea of how the software works internally. Often this is through flow diagrams to show the algorithm, what calls are being made to different functions/APIs to get that functionality to work, or knowledge of data structures.

Grey box testing can allow testers to be more efficient and scope tests better. It may allow them to pick up on weaknesses they didn't previously consider, or realise some tests are not needed as the situation where that issue could occur is not possible based on how it's programmed. It can also help remove confusion around how something works.

Arguments against grey box testing is that it may cause under-scoping, if the tester knows how the software works internally, they might miss edge cases as they're thinking closer to how the developer does, rather than considering every possible outcome. It also requires more technical knowledge.

[rahulacademy]

Sharing My Postman API Testing Success Story to Inspire Others

I want to share this with the hope that it may inspire others to begin their journey into the world of API testing with Postman. If you want to start your journey in Postman API testing and have a lot of doubts about where to begin, I hope my success story will guide and inspire you.

I’ll take you through my learning path: the challenges I faced, how I overcame them by using effective resources such as a step-by-step tutorial on API testing using Postman, and access to a number of free APIs to test in Postman.

Today, I am very confident in using Postman for testing and automation, and further would like to share all the tips and lessons that helped me on my way.

Why I Chose to Learn Postman API Testing

As a QA, I realized very fast that knowing Postman API Testing was not an option — it was a must-have. APIs are at the heart of all modern software systems, and testing them guarantees that programs function as intended.

Initially, I worked through manual testing techniques that were time-consuming and error-prone. I knew I needed a solution like Postman to make testing faster, more efficient, and more dependable.

But it wasn’t easy starting out; a little guidance and a flood of online resources often left me feeling lost. Many tutorials were either too complex or lacked real-world relevance. It was then that I found an excellent tutorial on using Postman for API testing that completely changed my approach.

It took very complicated Postman API Testing basics and broke them down into easy-to-digest steps and gradually went ahead to complex ideas.

How I Started: Using Postman Tutorial for Beginners

To every beginner, I recommend one thing — start with the postman tutorial for API testing for beginners. This is an excellent place for getting a sense of how one can go about doing everything from basic things:

Setting up Postman and starting with API requests.

Familiarity with different HTTP methods such as GET, POST, PUT, and DELETE.

Using Postman collections to manage your tests.

Among the very first things I learned was how to use free APIs for testing in Postman, where I could practice right away and without the need for any live projects. These APIs imitate real-life cases, which are just what one needs when beginning to work with API testing.

Examples of such APIs include open APIs for weather, false online businesses, and even imitation JSON data providers. These materials provided me the courage to explore without fear of damaging anything.

Overcoming Challenges: Learning Automation and Scripting

After becoming familiar with the fundamentals, I wanted to delve deeper into automation. I found that manual testing alone was insufficient for larger projects. That’s when I discovered an API testing Postman tutorial that focuses on automation. Here is what I learned:

Writing JavaScript programs to verify API answers.

Automate repeating tests with Postman’s capability.

Creation of environments and variables for the testing of APIs in various configurations.

It sounded overwhelming in theory, but the topics proved to be within the manageable learning curve by further decomposing them into subtopics. The tutorials that I followed included hands-on examples for each one of these topics. That helped me practice how to apply these techniques in a real project.

My Aha Moment: Putting to Practice What I Learned

The turning point in my journey occurred when I applied the knowledge I had gained to actual applications. Using the concepts I learned from a postman tutorial for API testing, I was able to:

Test live e-commerce platform REST APIs.

Automate repetitive test cases, saving hours manually.

Set up dynamic environments for staging, development, and production.

However, the most satisfying aspect was learning how to work with a free API for Postman testing, which made it relatively easy to practice and refine my skills. For example, I used public APIs to test workflows like user authentication, product search, and order placement.

Tips for a Beginner to Get Started with API Testing Using Postman

Here are some tips that worked really well for me when I took a dive to get started with Postman API testing:

Take a Good Beginning

Look out for a pretty beginner-friendly tutorial on Postman. This should have all the basics in as straightforward and simple a manner as possible. Examples with step-by-step explanations would be very impressive.

Free APIs for Practice

One of the best methods to boost confidence is to use a free API for Postman testing. Some excellent solutions are OpenWeatherMap, JSONPlaceholder, and TheCatAPI.

Learn the Fundamentals First

Before getting into automation, learn how to send requests, use various HTTP methods, and validate results.

Key Lessons I Learned Along the Way

Here are some of the main lessons that helped me a lot when learning:

Consistency is key: Even 30 minutes of Postman practice each day may bring about significant development.

Break down problems: If something appears too complicated, divide it into smaller, more manageable stages. For example, begin with basic GET queries before progressing to more sophisticated procedures.

Not skipping automation: Once you’ve mastered the fundamentals, move on to automation with Postman’s excellent API testing guide. Automation not only saves time, but it also ensures that tests are consistent.

Why I Recommend Postman for API Testing

If someone is interested in software testing or development, this can truly transform their experience. Here’s why:

It is both beginner-friendly and powerful enough for advanced testing.

You can practice using a free API for testing in Postman without any restrictions.

Learning was smooth, including with the community and other resources, such as the API testing tutorial for Postman.

Following the right resources and practicing regularly turned all struggles into a success story. Now, I proudly manage large projects that include API testing, and Postman is a key component of my work toolkit.

Final Words: Your Journey to Success

If I could give you one bit of advice, it would be: don’t be frightened to start. Everyone starts somewhere, and with the correct tools and resources, you’ll be surprised at how quickly you can learn Postman API Testing. Whether you’re working through a Postman lesson for beginners or digging into automation with a postman tutorial for API testing, each step gets you closer to your objective.

Remember that the learning process isn’t about perfection. Use free APIs for testing with Postman, practice often, and keep researching. I hope that my tale motivates you to take the first step toward mastering Postman API testing and achieving your career objectives.

Originally Article Publish at:- https://shorturl.at/iBsE4

[jailbreak-show]

First concepts / doodles / first animation in an animating program!

[Video description: Polly tilting her head back and forth. End VD.]

[aiadis]

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[eliast-94]

How Good is the quality of OSS

Understanding Software Quality

What makes great software? It’s not just fancy features or spotless code but it’s about creating tools that people love to use and that treat everyone fairly. In the fast-changing world of software development, the idea of “quality” means much more than just working code.

From a technical perspective, Amy Ko.jo, in Cooperative Software Development, highlights key traits like correctness, reliability, robustness, performance and portability. These are the building blocks for good software, helping it stay free of buts, handle unexpected problems and work across different devices. In this article, we’ll explore how these traits play a big role in testing and finding buts which are critical for building reliable systems.

But software isn’t just about machines or computers but it’s also about people using it. A major part of software quality is making sure it doesn’t unfairly harm or exclude anyone. For example, Amy J. Ko explains, biased data or algorithms can lead to discrimination like reinforcing harmful stereotypes. Fixing these biases is a key part of building software that regards everyone equally.

The Quality of Open-Source Software

Open-Source Software has sparked a lively debate about its quality. On one side, supporters say OSS creates better products because of the way it’s built which is by a global community of developers working together. As Oleh Romanyuk explains in FreeCodeCamp’s article on the Pros and Cons of OSS, open-source software is shaped by thousands of contributors each bringing unique skills and experience from different industries and technologies. This mix of perspectives makes it easier to spot and fix problems quickly, which means the software becomes more reliable and functional over time.

Data backs up this claim. The Coverity Scan Open-Source Report shows that OSS often has fewer bugs per thousands of lines of code compared to proprietary software. Why? Because open-source projects are constantly reviewed and improved by many developers creating a kind of “always-on” quality control system.

But the story doesn’t end there. A blog post by the World Bank, Quality of Open-Source Software: How many Eyes are Enough? points out that bigger proprietary software projects often beat OSS in quality. The reason you ask. Big companies have dedicated teams of paid experts and structured processes to find and fix complex problems. These teams don’t just fix the obvious, but they tackle the tough ones that require deep knowledge of the software’s inner workings.

This brings up a challenge for open-source software projects. They often lack the consistent funding and organized workflows that proprietary software teams have. As Amy K. Jo explains in Cooperative Software Development, software quality isn’t just about the code but also how the code is created. While OSS does a great job fixing simpler bugs through teamwork, the harder to spot issues may require the resources and expertise that only a well-funded proprietary team can provide.

So, is open-source software better? The answer isn’t so simple. OSS thrives on collaboration, bringing together diverse ideas and talents to create something great. But proprietary software benefits from structure, funding and expert teams. Maybe the real takeaway is this: quality depends not just on the software itself but also on the people and process behind it.

The Role of Quality Assurance in OSS.

Open source thrives on community collaboration - volunteers from around the world contributing their time, skills and insights to develop, debug and enhance software. However, because open source operates on a voluntary basis, challenges like varying levels of expertise, inconsistent time commitments and the “release early, release often” philosophy can make quality assurance difficult. For open source to maintain high-quality standards, developers, quality engineers and users must work together  to ensure the software remains reliable and functional.

Continuous integration tools like Jenkins are essential in this process. Projects like Pulp use Jenkins to automate testing, monitor results and catch integration failures early. This helps ensure only stable, well-tested code reaches the end users. Automated test frameworks such as Pulp Smash further strengthen quality by allowing contributors to write flexible, portable tests that identify regression swiftly.

Community Test Days also play a key role. Projects like Fedora organize test days, inviting users to propose areas for testing, document their findings, and collaborate in forums like IRC channels. These test days empower users to become active participants in quality assurance, ensuring critical issues are identified and addressed. Additionally, Bug Triage days, like Foreman’s Bug Day, give users the chance to prioritize and resolve existing bugs, reducing the backlog of unresolved issues.

Through tools like continuous integration, automated testing, community test days and but triage, open-source projects can ensure high quality and maintain stability even in the face of decentralized development.

Addressing Bias in Open-Source Software: Overlooked Quality in OSS?

Bias in OSS development specially when it comes to gender, continuous to be a significant issue. Women are underrepresented in OSS and they miss out on a valuable development and professional opportunities. As new jobs open up, many women lack the experience needed to apply which can only continue this cycle. According to researchers like Anita Sarma and Steinmacher,  these problem may be build into the very tools used for OSS development which creates barriers that discourage women from participating.

Their research focuses on tools like Eclipse, Git, GitHub, Jira and Hudson, tools that weren’t always designed with divers users in mind. Steinmacher explains, “If someone implements a tool without considering a diverse set of user, they may include such kinds of bugs which affect one gender more that the other.”  The team plans  to use GenderMag, a method developed by Margaret Burnett to identify gender-biased barriers in these tool.   

To truly improve the quality of OSS, addressing bias requires a deliberate effort from a diverse group of contributors who bring a variety of perspectives to the table. By prioritizing inclusivity in design and testing, OSS can create software that works for everyone not just a select few. Without this focus, bias can undermine the overall quality and fairness of OSS, reducing its effectiveness and limiting its impact. In the end, addressing bias is not just about fairness but also about improving the overall quality of OSS and ensuring it works for everyone.

References

Ajko, A. (n.d.). Cooperative software development: Quality. University of Washington. Retrieved from https://faculty.washington.edu/ajko/books/cooperative-software-development/quality

Gibbons, S. (2021, December 29). What is great about developing open source and what is not? FreeCodeCamp. Retrieved from https://www.freecodecamp.org/news/what-is-great-about-developing-open-source-and-what-is-not/

Black Duck Software. (n.d.). Coverity Scan: Open source. Retrieved from https://www.blackduck.com/

M. K. (2019, May 28). The quality of open source software: How many eyes are enough? World Bank Blogs. Retrieved from https://blogs.worldbank.org/en/opendata/quality-open-source-software-how-many-eyes-are-enough

How Good is the Quality of Open Source software compared to proprietary software © 2024 is licensed under Creative Commons Attribution-ShareAlike 4.0 International