In a previous blog post, I had talked about Test Driven Development, or TDD. Today, I’m going to introduce a different approach that aims to almost rectify the potential shortcomings of TDD, that approach being Behavior Driven Development, or BDD for short.

BDD can be described  as “a collaborative approach to software development that aims to bridge the communication gap between business and technical teams” with the core idea of creating a “shared understanding of the software’s intended behavior using concrete examples” (Test Guild).

“The process revolves around writing scenarios using the Given-When-Then format, which describes the preconditions (Given), the action or event (When), and the expected outcome (Then).” This is a format that can be easily understood regardless of what people specialize in. TDD involved writing test cases and coding based on those test cases which mainly involved the developers, testers, and those that are closely linked to the programming and technical development. BDD, on the other hand, can involve the non-technical, such as stakeholders and those from other departments on top of the developers and testers. It can be simply put as, “compared to test-driven development (TDD) which is developer-centric, BDD is a team-wide practice” (Test Guild).

The Given-When-Then format allows for less misunderstanding when it comes to what is required of the software. Developers may use names that are short and to the point to describe something but it doesn’t match the behavior that is desired. The same developer or others that have just started working on the code may simply go along with it not realizing that what is desired of the code is something more or something else entirely. By using this format along with full sentences describing exactly what the code should do, there will be less room for error, misunderstanding, and time wasted fixing the code down the line.

One of the difficulties that seems to arise with the implementation of BDD is the inclusion of implementation details in scenarios. This is because scenarios are meant to focus solely on behavior. Including implementation details is basically attempting to set something in stone; scenarios describe what is desired of the code and how developers achieve that can change many times. It ends up adding more work every time that detail has to be met or changed.

BDD is an interesting topic, it seems to be a direct upgrade from TDD but that isn’t always the case. Take a classroom environment for example, it’s a bit odd as we (the students) could be considered developers but what about the other roles in the process? Would the professor act or technically be a stakeholder? It’s a process that can be learned at any point but it seems it can be only truly put into practice in a real world environment. We can certainly take aspects of BDD into mind, the Given-When-Then format and basing development around desired behaviors seems to have little to no downsides for any situation. 

Source: https://testguild.com/what-is-bdd/

From the blog CS@Worcester – Kyler's Blog by kylerlai and used with permission of the author. All other rights reserved by the author.

The blog post “Software Testing Basics: Positive vs. Negative Software Testing” explores two fundamental approaches in software testing: positive and negative testing. I chose this blog post because this semester we have been taught a variety of software testing techniques and strategies. From this blog post, it has categorized some of the techniques we have learned into one of two categories mentioned, positive or negative testing. I found this useful as it also allows us to know easily when to utilize certain techniques for certain scenarios.

The blog begins by describing the significance of software testing in ensuring the quality and reliability of software applications. Testing is important not only to detect bugs but also to enhance user experience and maintain credibility. Positive testing involves validating the software’s expected behavior under normal conditions. Test cases are designed to verify that the system functions as intended when provided with valid inputs. This method aims to affirm that the software performs its functions accurately and efficiently. By executing positive tests, developers can gain confidence in the system’s reliability and usability. On the other hand, negative testing focuses on the software’s ability to handle invalid or unexpected inputs and conditions. Test cases are designed to provoke errors, exceptions, or failures within the system. This approach aims to uncover vulnerabilities, defects, or unforeseen scenarios that may compromise the software’s performance or security. Negative testing is crucial for identifying weaknesses and enhancing the robustness of the software.The blog emphasizes the complementary nature of positive and negative testing. While positive testing validates the correctness of the software’s intended behavior, negative testing uncovers potential issues that might have been overlooked. Together, they provide comprehensive test coverage and contribute to the overall quality assurance process.Moreover, the blog discusses various strategies and techniques for conducting positive and negative testing. For example, positive testing involves scenarios such as input validation, boundary testing, and functional testing, where the focus is on confirming the expected outcomes. While, negative testing encompasses techniques like boundary value analysis, error guessing, and stress testing, aimed at challenging the error-handling capabilities of the code.

After reading this blog post, I feel like I would be better prepared for software testing or quality assurance. The descriptions of positive versus negative testing in my opinion were very helpful in solidifying my knowledge on software testing as well as teaching me new aspects of it. As previously mentioned, the blog post was beneficial for teaching me to know when to utilize certain techniques for various scenarios.

https://www.testmonitor.com/blog/software-testing-basics-positive-vs.-negative-software-testing

From the blog CS@Worcester – Giovanni Casiano – Software Development by Giovanni Casiano and used with permission of the author. All other rights reserved by the author.

What is JUnit?

JUnit is a Java testing framework that simplifies writing reliable and efficient tests. It’s especially suited for testing Java applications and offers features like multiple test cases, assertions, and reporting. JUnit is versatile and supports various test types, including unit, functional, and integration tests.

JUnit and Testing Types

JUnit primarily focuses on unit testing but can also handle functional and integration testing. Functional tests evaluate the functionality of a system as a whole, while integration tests assess how different components of a system work together.

How Does JUnit Work?

JUnit works by allowing developers to write tests in Java and run them on the Java platform. It provides features like assertions to verify expected behavior, test runners to execute tests, test suites to group related tests, and reporting tools to analyze test results.

Benefits of Using JUnit

• Organized and readable code.
• Early detection and fixing of errors.
• Improved software quality.
• Increased efficiency in the testing process.

Getting Started with JUnit

To get started with JUnit, developers can access tutorials, documentation, and forums for guidance. Setting up a JUnit project involves installing JUnit in an IDE like Eclipse or IntelliJ IDEA, creating a standard test file, and writing test methods.

Writing Test Methods

Writing a test method involves adding annotations, method signatures, method bodies, and assertions. Assertions like assertEquals, assertNotNull, assertTrue, and fail are essential for verifying expected results.

Creating and Running Tests

Creating and running tests in JUnit requires opening the project in a testing framework, selecting the desired test classes or methods, and executing them. Debugging modes like JDWP and Standard Streams help identify and fix issues during testing.

Troubleshooting Techniques

Troubleshooting techniques include using debuggers, checking documentation and forums, and running tests regularly. Well-written tests follow guidelines like keeping them small, relevant, and well-organized.

JUnit’s Assertions

JUnit’s assertions play a vital role in testing by checking conditions and verifying results. Common assertions include assertEquals, assertNotNull, assertTrue, and fail.

Conclusion

JUnit is a powerful Java testing framework that helps developers create reliable and testable code. By incorporating JUnit into their development process, developers can improve software quality, increase efficiency, and ultimately enhance their Java development skills.

Source – https://www.headspin.io/blog/junit-a-complete-guide

From the blog CS@Worcester – CS: Start to Finish by mrjfatal and used with permission of the author. All other rights reserved by the author.

Data science is a powerful field that can unlock valuable insights from data. However, the quality of those insights depends heavily on the quality of the data used to create them. Imagine building a house on a foundation with cracks. Even the best construction plans won’t prevent problems down the road. Similarly, data science projects built on flawed data can lead to inaccurate results and misleading conclusions. This is where quality assurance (QA) comes in. QA helps ensure the data used is clean, consistent, and reliable, forming a solid foundation for your analysis.

Beyond Typos: The Multifaceted Approach to QA

Data science QA goes beyond simply checking for typos. It’s a comprehensive process that focuses on several key areas:

• Data Cleaning: This involves identifying and fixing errors in your data set, such as missing values, inconsistencies (like duplicate entries), and outliers (data points that fall far outside the expected range). It’s like cleaning up the raw materials before you start building something.
• Model Validation: Once you’ve built your model, you need to test it thoroughly. This involves using data the model hasn’t seen before to assess its accuracy and generalizability. Imagine training a model to predict traffic patterns based on historical data. QA would involve testing the model with data from a new week or month to see if it can still predict traffic accurately.
• Documentation: Clear documentation is essential for any project, and data science is no exception. QA emphasizes documenting the entire workflow, including data cleaning steps, model training processes, and evaluation results. This allows for better understanding and potential replication of your analysis by others.

The Benefits of Rigorous QA

Implementing a robust QA process offers several advantages:

• Improved Data Quality: Clean and accurate data leads to more reliable models and trustworthy insights. This allows businesses to make informed decisions based on solid evidence.
• Reduced Errors: Early detection and correction of errors in data and models prevent misleading conclusions and costly mistakes. This saves time, resources, and helps build trust in data science projects.
• Enhanced Transparency: Clear documentation and well-tested models foster trust in data science projects. Stakeholders can be confident in the validity of the results, leading to better collaboration and buy-in for data-driven initiatives.

Conclusion

QA may not be the most glamorous aspect of data science, but it’s a crucial step towards ensuring project success. By following proper QA procedures, data scientists can ensure the integrity of their work and deliver reliable insights that drive informed decision-making across various domains. Remember, in data science, just like in building a house, a strong foundation is essential for a successful outcome.

Use this link to access the article: https://thedatascientist.com/qa-testing-analytics/ 

From the blog CS@Worcester – Site Title by Iman Kondakciu and used with permission of the author. All other rights reserved by the author.

This week’s blog post will cover System Testing and its main benefits. System Testing, as the name suggests, revolves around evaluating the entire system as a whole. It’s not just about scrutinizing individual components; it’s about ensuring that all parts seamlessly integrate and function as intended. This phase of testing comes after the completion of unit and integration testing, aiming to validate the system against its specified requirements. It involves subjecting the system to a barrage of tests to assess its compliance with functional and non-functional requirements. From testing the user interface to examining performance metrics, System Testing leaves no stone unturned in the quest for a robust and reliable software product. This method is most effective before launching your product, to ensure a total coverage.

Security vulnerabilities can be a project’s nightmare. System Testing acts as a guardian, identifying security loopholes and ensuring the system is robust against potential attacks. One of the key tenets of System Testing is its focus on real-world scenarios. Instead of merely verifying technical functionalities, System Testing endeavors to simulate user interactions and workflows. By replicating typical usage scenarios, testers can unearth potential bottlenecks, usability issues, and even security vulnerabilities lurking within the system. Through testing and analysis, it offers valuable insights into the system’s readiness for deployment. Moreover, System Testing serves as a safeguard against post-release hurdles by preemptively identifying and preventing potential pitfalls.
System Testing does have its cons however, one crucial step in system testing is creating a comprehensive test plan. This is crucial for effective System Testing because it ensures all bases are covered and avoids blind spots.

Like most of the testing techniques we have covered in class, tools play a pivotal role in streamlining the testing workflow. From test automation frameworks like Selenium and Cypress to performance testing tools like JMeter and Gatling, there’s a plethora of tools available to expedite the testing process. Leveraging these tools not only enhances efficiency but also empowers testers to uncover hidden defects more effectively.

System Testing stands as a cornerstone of software quality assurance, offering a panoramic view of the system’s functionality and performance. While it may pose its fair share of challenges, the insights gleaned from System Testing are invaluable in ensuring the delivery of a high-quality, robust software solution. By embracing System Testing, you’re essentially investing in the quality and reliability of your software. It’s the final hurdle before launch, guaranteeing a smooth user experience and a successful project.

Blog Post: https://blog.qasource.com/what-is-system-testing-an-ultimate-beginners-guide

From the blog CS@Worcester – Computer Science Through a Junior by Winston Luu and used with permission of the author. All other rights reserved by the author.

The online world offers incredible convenience, but it also comes with inherent security risks. News stories about data breaches and hacker attacks can make anyone feel uneasy. But there’s a way to fight back, and it’s not what you might think! Security testing allows you to become a good guy hacker (ethically, of course) and uncover weaknesses in websites and applications before the bad guys exploit them. Our recent group activity in class gave us a taste of this exciting field, and this article dives deeper into the world of security testing.

What is Security Testing, Exactly?

Imagine building a fantastic treehouse. Wouldn’t you check for loose boards or shaky branches before inviting your friends over? Security testing operates on a similar principle, but for the digital world. It’s the process of identifying vulnerabilities in software applications, systems, and networks. These vulnerabilities could be weaknesses in login procedures, hidden loopholes in code, or anything that could potentially allow unauthorized access or disrupt operations. Think of it as a proactive approach to cybersecurity, simulating real-world attack scenarios to expose potential security flaws before they become critical issues.

Why is Security Testing Important?

Security testing offers a multitude of benefits for both organizations and users.

• Enhanced Security Posture: By discovering vulnerabilities early on, security testing allows for timely remediation, minimizing the risk of successful cyberattacks. Think of it as patching up holes in your digital castle before a storm hits.
• Improved User Confidence: When users understand that security is a top priority, it fosters trust and confidence in the digital services they utilize. Knowing your information is protected creates a more secure and comfortable online experience.
• Compliance with Regulations: Many industries have regulations for data security. Security testing helps demonstrate compliance with these regulations, ensuring your organization operates within legal boundaries.

Types of Security Testing: Different Tools for Different Tasks

Security testing isn’t a one-size-fits-all approach. Different types of tests cater to specific needs:

• Vulnerability Assessment: This involves automated scans that identify potential weaknesses in software, systems, and networks. It’s like having a security scanner sweep your digital castle for weak spots, providing a broad overview of your security posture.
• Penetration Testing: Often referred to as ethical hacking, penetration testing involves simulating real-world attacks to exploit vulnerabilities and assess the effectiveness of existing security controls. Think of it as our group activity in class, but on a larger scale. Ethical hackers attempt to break into a system, exposing weaknesses so they can be addressed before a real attacker tries the same.
• Static Application Security Testing (SAST): This technique analyzes the source code of an application to identify potential security flaws without running the program. Imagine being able to inspect the blueprints of your digital castle for structural weaknesses before construction begins.
• Dynamic Application Security Testing (DAST): This method interacts with a running application, simulating user actions and searching for vulnerabilities. It’s like testing the security of your completed digital castle by having people try to break in under real-world conditions.

Becoming a Security Champion:

Security testing might seem complex, but even beginners can contribute to a more secure digital environment. Here are some ways to get started:

• Learn the Basics: Numerous online resources offer comprehensive introductions to security concepts and various testing methodologies. Explore free tutorials, articles, and online courses to gain foundational knowledge.
• Spread Awareness: Talk to your friends and family about the importance of online security and strong passwords. Educate those around you about simple steps they can take to protect themselves online.
• Consider a Security Career: The demand for security professionals is skyrocketing! If you’re passionate about technology and protecting data, a career in security testing could be a rewarding path for you.

Remember, becoming a security whiz takes time and dedication. But even small steps can make a big difference. By understanding the importance and different approaches to security testing, you can contribute to a safer online environment.

Read more on this article: https://www.guru99.com/what-is-security-testing.html

From the blog CS@Worcester – Site Title by Iman Kondakciu and used with permission of the author. All other rights reserved by the author.

This week I decided to look up what was going on in the news for software
quality assurance. I found this article about a survey on the future of
quality assurance and found it interesting. The headline was more
specifically about the adoption of A.I. in software testing. I have already
covered some of the potential benefits of the use of A.I. in software
testing, so consider this to be a follow up to that. Keep in mind this
article was written back in December of 2023, so things could have
potentially changed in that time. 

The title of this article states that over 78% of software testers have
adopted A.I. into their testing. This kind of comes as no surprise since
people have been gushing about the new burgeoning technology for a while
now.  The tech industry has made a big effort to adopt A.I. into as
many different fields as possible. The automation of test cases is not a new
subject, but the use of A.I. is a fairly recent addition to the tools
testers have at their disposal. These tools are being implemented in
different sections of the quality assurance process, with an adoption rate
of 51% for test data creation,45% for test automation, 36% for test result
analysis, and 46% for test case formulation. And like I said before, these
are the numbers the end of 2023, who knows what the current numbers
are.

https://www.prnewswire.com/ae/news-releases/ai-adoption-among-software-testers-at-78-reliability-and-skill-gap-the-biggest-challenges-302007514.html

On a side note, the article says that software testers are being involved
much earlier in the development process. This ties in directly with what I
have been learning in class for the past two semesters about sprint
planning. Having testers be there in the sprint planning phase allows to get
the specifications for the test cases earlier than before, but could lead to
test cases without implemented code.

All of this data comes from a survey into the future of quality assurance
by Lambda Test. Some other interesting figures from the survey include
numbers on quality assurance budget and the ratio of QA testers to
developers. Companies, both big and small, seem to see quality assurance as
a valuable part of the software development process, and invest accordingly.
Interestingly, there is also data on the state of testing itself, with a
particularly interesting note about the benchmark for bug identification
being around 10%.

https://www.lambdatest.com/future-of-quality-assurance-survey?utm_source=media&utm_medium=pressrelease&utm_campaign=dec06_kn&utm_term=kn&utm_content=pr

From the blog CS@Worcester Alejandro Professional Blog by amontesdeoca and used with permission of the author. All other rights reserved by the author.