Welcome back, fellow coders! Today, I’m going back to a technique called path testing. 

Why is Path Testing Important?

Software development thrives on creating programs that function flawlessly, regardless of user interaction. Traditional testing methods might miss certain sections of code depending on user choices. Path testing, however, takes a different approach. It systematically executes every possible path a program can take, significantly increasing the likelihood of encountering and eliminating potential errors.

Here’s how path testing elevates your software development game:

• Enhanced Bug Detection: Think of bugs like sneaky goblins hiding in the castle’s shadows. Path testing, by meticulously traversing every path, shines a light on these goblins, exposing them before they can cause problems for users.
• Improved Software Quality: Just like a well-maintained castle provides a secure and comfortable environment, path testing leads to the creation of high-quality software. Identifying and rectifying errors early on ensures a more robust and reliable program.
• Increased Confidence in Functionality: Having meticulously explored every potential path within the program, testers gain a heightened sense of assurance. They know, with greater confidence, that the program will perform as intended, leading to a more predictable and stable user experience.

Exploring the Different Levels of Path Testing

Path testing isn’t a one-size-fits-all approach. There are various levels of coverage, each focusing on a specific aspect of the program’s execution paths:

• Statement Coverage: This foundational level resembles meticulously walking across every single floorboard within the castle. It ensures that every single line of code within the program is executed at least once during testing.
• Decision Coverage: Taking things a step further, decision coverage is like exploring every hallway and doorway, ensuring you’ve taken both the left and right turns at every intersection. It guarantees that each decision point within the program (such as if statements and loops) is evaluated with both possible outcomes – true and false.
• Condition Coverage: This is the most rigorous level, akin to meticulously checking every wall and secret passage within the castle. It ensures that each individual condition within a decision (e.g., the expression in an if statement) is evaluated to be both true and false at least once.

The Path to High-Quality Software

By incorporating path testing into the software development lifecycle, developers gain a valuable tool for creating exceptional applications. This structured approach ensures comprehensive coverage of potential execution paths, leading to the identification and rectification of errors before they manifest as real-world problems.

Inspired by: Path Testing: The Coverage

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 am revisiting some fundamental test case design techniques: equivalence partitioning and boundary value analysis. While these terms might sound complex, they offer a structured and efficient approach to software testing, particularly for numerical inputs or situations with defined input ranges.

Equivalence Partitioning: Dividing the Input Landscape Strategically

Imagine a program that validates user age for login purposes. Traditionally, one might be tempted to test every single possible age value from 0 to 120 (or whatever the defined limit may be). This brute-force approach, however, quickly becomes impractical and inefficient as the number of possible inputs grows. Equivalence partitioning offers a more strategic solution.

Equivalence partitioning involves dividing the entire set of possible input values (the input domain) into distinct classes where the program is expected to behave similarly for all values within a class. These classes are called equivalence partitions. In the age validation example, we could define the following equivalence partitions:

• Valid Ages: This partition encompasses all ages that fall within the expected range for a user (e.g., 0 to 120).
• Invalid Ages: This partition includes all values outside the valid range, such as negative numbers or values exceeding the limit (e.g., negative numbers or ages greater than 120).
• Empty or Null Values: This partition considers scenarios where the user leaves the age field blank or enters an invalid value that evaluates to null.

By identifying these partitions, we can significantly reduce the number of test cases needed for comprehensive testing. Instead of testing every single age within the valid range, we can select representative test cases from each partition. For example, we could test valid ages with values at the beginning, middle, and end of the range (e.g., 0, 30, and 120). Similarly, we could test invalid ages with a negative number and a value exceeding the limit.

Boundary Value Analysis: Sharpening Our Focus on Critical Areas

Equivalence partitioning provides a solid foundation for test case design. However, it’s important to pay close attention to the boundaries or edges of each partition. This is where boundary value analysis comes into play. Boundary value analysis focuses on testing the specific values that lie at the borders of each equivalence partition. This includes:

• Minimum and Maximum Valid Values: In the age validation example, this would involve testing the program’s behavior with values at the beginning (0) and end (120) of the valid age range.
• Values Just Above and Below the Valid Range: This involves testing one value above the maximum valid age (e.g., 121) and one value below the minimum valid age (e.g., -1).

The rationale behind testing these boundary values is that programs are often more susceptible to errors at the edges of their input domains. By testing these specific values, we can identify potential issues that might be missed by random testing within the valid range.

Conclusion

Equivalence partitioning and boundary value analysis are valuable tools for software testers. They promote efficient test case design, improve test coverage, and ultimately contribute to the development of high-quality software.

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

In the realm of software development, testing plays a crucial role in ensuring the reliability, functionality, and quality of the final product. As software systems become increasingly complex, traditional testing methods may not suffice, particularly in object-oriented (OO) programming environments. This blog explores the intricacies of OO testing and its significance in software engineering practices.

Summary of Object-Oriented Testing

Object-oriented testing focuses on validating the interactions, behaviors, and integrity of objects, classes, and their relationships within an OO system. Unlike traditional testing methods that primarily test individual functions, OO testing addresses the unique challenges posed by OO programming, such as data dependencies, inheritance, polymorphism, and dynamic binding.

The blog outlines various techniques used in OO testing, including:

• Fault-based testing: Identifying faults in the design or code and creating test cases to uncover errors.
• Class testing based on method testing: Testing each method of a class to ensure its functionality.
• Random testing: Developing random test sequences to mimic real-world scenarios.
• Partition testing: Categorizing inputs and outputs to test them thoroughly.
• Scenario-based testing: Stimulating user actions to test interaction patterns.

Moreover, the blog highlights the purposes of OO testing, such as validating object interactions, identifying design errors, assessing code reusability, handling exceptions, and maintaining system uniformity.

Purpose of Object Oriented Testing

1. Object Interaction Validation: Ensure that objects interact appropriately with each other in various situations.
2. Determining Design Errors: Identify limitations and faults in the object-oriented design, focusing on inheritance, polymorphism, encapsulation, and other OOP concepts.
3. Finding Integration Problems: Evaluate an object’s ability to integrate and communicate within larger components or subsystems, locating issues such as improper method calls or data exchange problems.
4. Assessment of Reusable Code: Evaluate the reusability of object-oriented code, ensuring that reusable parts perform as intended in different scenarios, leveraging features like inheritance and composition.
5. Verification of Handling Exceptions: Confirm that objects respond correctly to error circumstances and exceptions, ensuring the software is resilient and durable.
6. Verification of Uniformity: Maintain consistency within and between objects and the overall object-oriented system, enhancing maintainability and readability by following naming standards, coding styles, and design patterns.

Personal Reflection

While traditional software testing emphasizes system-level functionality and performance, object-oriented testing focuses on validating interactions and behaviors within OO systems. Both resources underscored the importance of rigorous testing in software engineering, albeit with different approaches.

In my future practice, I intend to incorporate elements from both traditional and object-oriented testing methodologies. By applying fault-based testing, random testing, and scenario-based testing techniques from OO testing, I aim to identify and rectify potential errors early in the development process. Additionally, I will continue to emphasize comprehensive system testing to ensure software meets user requirements and quality standards.

Understanding both traditional and object-oriented testing methodologies equips me to contribute effectively to the creation of high-quality software solutions. By integrating the insights gained from both resources, I am confident in my ability to enhance software testing practices and deliver reliable software products in today’s dynamic software development landscape.

Source: https://www.geeksforgeeks.org/object-oriented-testing-in-software-testing/

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.

In the realm of software development, ensuring the quality and reliability of a software solution is paramount. One crucial aspect of this process is system testing. In this blog post, we’ll delve into what system testing entails, its process, types, tools used, as well as its advantages and disadvantages.

What is System Testing?

System Testing is a vital phase in software development, where the complete and integrated software solution is evaluated to ensure it meets specified requirements and is suitable for end-users. It’s conducted after integration testing and before acceptance testing, focusing on both functional and non-functional aspects.

System Testing Process

System Testing involves several steps:

1. Test Environment Setup: Creating a testing environment for quality testing.
2. Creating Test Cases: Generating test cases for the testing process.
3. Creating Test Data: Generating data for testing.
4. Executing Test Cases: Running test cases using the generated data.
5. Defect Reporting: Detecting and reporting system defects.
6. Regression Testing: Testing for side effects of the testing process.
7. Log Defects: Logging and fixing detected defects.
8. Retesting: Repeating tests if unsuccessful.

Types of System Testing

1. Performance Testing: Evaluates speed, scalability, stability, and reliability.
2. Load Testing: Determines system behavior under extreme loads.
3. Stress Testing: Checks system robustness under varying loads.
4. Scalability Testing: Tests system performance in scaling up or down.

Tools used for System Testing

Several tools aid in system testing, including JMeter, Selenium, HP Quality Center/ALM, and more. The choice depends on factors like technology used, project size, and budget.

Advantages of System Testing

• Ensures comprehensive testing of the entire software.
• Validates technical and business requirements.
• Detects and resolves system-level problems early.
• Improves system reliability and quality.
• Enhances collaboration between teams.
• Increases user confidence and reduces risks.

Disadvantages of System Testing

• Time-consuming and expensive.
• Requires good debugging tools.
• Dependent on quality of requirements and design documents.
• Limited visibility into internal workings.
• Can be impacted by external factors like hardware configurations.

Personal Reflection

This resource has equipped me with valuable insights into system testing, which I believe will greatly enhance my job hunting process in software development. Understanding the various testing processes, types, and tools will make me a more competitive candidate, allowing me to target roles that specifically require expertise in system testing. Additionally, knowing the advantages and disadvantages of system testing will help me assess potential job opportunities more effectively, ensuring alignment with my skills and preferences. As I have seen many open roles looking for Software Q&A applicants.

Source: https://www.geeksforgeeks.org/system-testing/

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.

I recently read quite a few blogs regarding test-driven development (TDD), with many of them referencing behavior-driven development (BDD). This left me curious to learn about BDD and how it was different from TDD. Phillip Rogers does a great job breaking down what BDD is, the three principles of BDD, and some examples of BDD with Gherkin in his blog: “Behavior-driven development principles and practices.” (https://blog.logrocket.com/product-management/behavior-driven-development-principles-practices/#:~:text=Behavior%2Ddriven%20development%20(BDD),%2C%20domain%2Dspecific%20scripting%20language.) 

What is Behavior-Driven Development?

Behavior-driven development (BDD) is a product management approach focusing on defining system behavior from the user’s perspective. It emphasizes user interaction, collaboration among stakeholders, and aligning the product with user needs. BDD is a test-first development method.

3 Principles of Behavior-Driven Development:

1. What the software could do: Discovering and understanding customers needs to avoid building the wrong features. Techniques like impact mapping help prioritize features based on customer value.

2. What the software should do: Collaboratively writing structured documentation (executable specifications) articulating user needs. This involves using scenarios and examples in a given-when-then format to describe user behaviors.

3. What the software does: Automating desired behavior based on specifications, writing code, and iteratively improving both code and tests. This aligns with the test-driven development (TDD) process of writing failing tests, writing code to pass tests, and refactoring.

Behavior-Driven Development practices:

Impact mapping: A visual technique that reinforces what user outcomes are most important and are therefore more important to the project.

Story mapping: A visual technique that is used to maintain an understanding of what specifications are needed for a feature.

Three amigos: Forming sub-groups with different skill sets to work together. This brings different perspectives and thought processes into groups that may not have been there otherwise.

Benefits of Behavior-Driven Development

BDD being focused on the users’ perspective gives an improved understanding of the users’ goals. The tests created for BDD are typically higher level tests covering user scenarios. This ensures a high test coverage. Other benefits include enhanced collaboration, code reuse, and reduced rework as required changes are more likely to be seen early on.

Behavior-Driven Development vs Test-Driven Development

BDD and TDD are both test-first development methods that require planning and understanding of the project before beginning development. So, how are they different? TTD is mainly focused on the functionality of a feature. Whereas, BDD is focused on the users’ experience with that feature. BDD is more focused on testing specific scenarios a user may encounter. One notable difference is the fact that a single developer can do TDD where-as the amount of insight needed to do BDD requires everyone from developers to stakeholders,

From the blog CS@Worcester – CS Learning by kbourassa18 and used with permission of the author. All other rights reserved by the author.

For this week’s blog, I decided to research security testing because we didn’t have the chance to go over it in class. While researching, I found a blog called “Security Testing: Types, Tools, and Best Practices” by Oliver Moradov. The article is split up into a few main sections: “What is Security Testing?”, “Types Of Security Testing”, “Security Test Cases and Scenarios”, “Security Testing Approaches”, “What Is DevSecOps?”, “Data Security Testing”, “Security Testing Tools”, and  “Security Testing Best Practices”.

The first section “What is Security Testing?” explains the definition of security testing then spits off into two sections that explain the main goals and key principles of security testing using bullet points to organize the information. Security testing determines if the software is vulnerable to cyber assaults and evaluates the effect of malicious or unexpected inputs on its operations. Security testing demonstrates that systems and information are safe and dependable and that they do not accept unauthorized inputs. It’s a type of non-functional testing that focuses on testing if the software is configured and designed correctly. The main goals of this kind of testing are to identify assets, risks, threats, and vulnerabilities. It gives actionable instructions for resolving detected vulnerabilities and can verify that they have been effectively fixed. The key principles of security testing are confidentiality, integrity, authentication, authorization, availability, and non-repudiation.  

The next section provides multiple sections that delve deeper into the multiple types of security testing. The examples provided are penetration testing (ethical hacking), application security testing (AST), web application security testing, API security testing, vulnerability management, configuration scanning, security audits, risk assessment, and security posture assessment. I knew about a few of these types of security testing. However, it was interesting to learn about API security testing and security posture assessments. It provided information like how APIs allow attackers to gain access to sensitive data and utilize them as an entry point into internal systems and the basics of what a security posture entails. 

The blog then discusses some important test scenarios like authentication, input validation, application, and business logic then provides other tests in a bulleted list. It then discusses the types of approaches ( white box, black box, and grey box testing) and a few useful tools.

The next section that I found very important was the section about best practices. The best practices mentioned were: “Shift Security Testing Left”, “Test Internal Interfaces, not Just APIs and UIs”, “Automate and Test Often”, “Third-Party Components and Open Source Security” and “Using the OWASP Web Security Testing Guide”. I knew about some of the practices like automating and testing often and testing often but I did not know about the Web Security Testing Guide (WSTG). I like the fact that the author provided a link to that resource as well. I think this blog is a great resource for those who want to learn about security testing. It is well organized and made me feel like I’m a bit better prepared to enhance security for future projects. 

From the blog CS@Worcester – Live Laugh Code by Shamarah Ramirez and used with permission of the author. All other rights reserved by the author.

With artificial intelligence increasing computational power and variability in usage, I wondered what advances were being made with AI. The tedious and repetitive aspect of test-driven development can sometimes leave the development process stagnating, so I was interested in how AI is changing the software testing process. This blog post, AI for Unit Testing: Revolutionizing Developer Productivity, by Philip Riecks, expands on how AI is improving the quality of our code and the productivity of our developers. 

The article highlights AI’s revolutionary steps in software testing and development. It discusses tools like IDE plugins that act as digital coding assistants and surveys from GitLab that show a significant increase in AI usage and demand for AI testing solutions. Philip explains the benefits of AI, which include streamlining test creation, boosting developer productivity, reducing developer fatigue, and many more. The article addresses why developers hate unit testing, highlighting the importance of it despite its tedious nature. It then gives an assortment of those tools with a small explanation of their specialization.

I found this article very enlightening, especially regarding the impressive abilities of AI-driven tools. My first thought when thinking of AI is to fear for developers’ jobs or worry about copyright infringement. It is nice to see that the focus of AI tools based on this article is to help developers by removing tedious tasks and allowing them to focus on improving the code. One of the sections mention AI’s ability to use user stories to generate test cases automatically. This was particularly interesting to me because a big part of behavioral-driven development involves using user scenarios when developing tests. Having AI take the workload off those using the BDD method would significantly increase productivity.

While reading, I still worry about the experience of those who use AI. If AI predicts defect areas, creates tests, and assists you every step of the way, how will that affect your ability to do those tasks? I also wonder if it matters if our abilities are lowered if we always have the tool at our disposal anyway. I imagine it would end up the same way we use calculators. We learn and can do calculations, but use the tool for convenience. Overall, I’m cautiously excited about AI, the stress taken off developers’ shoulders, and the increased time they will receive to focus on enhancing their projects.  

In the future, I will endeavor to learn more about AI, focusing on current and upcoming tools. When I use these tools, I will use them as an assistant and not as a crutch. 

The Article:https://www.diffblue.com/resources/ai-for-unit-testing-revolutionizing-developer-productivity/

From the blog CS@Worcester – KindlCoding by jkindl and used with permission of the author. All other rights reserved by the author.

Unit Testing

Unit testing is a process in software testing where the smallest functional unit of code is tested. A common practice for unit tests is to first write the tests as code. Then the test code can be run automatically when changes are made. Doing this allows errors to be found, and isolated quickly if a test fails. Automating tests helps to ensure that efforts are focused on coding, rather than running tests.

As stated previously, a unit test is a block of code that verifies the accuracy of the smaller blocks of the code such as a function. The unit test checks that the block of code runs as expected, determined by the developer’s logic. A block of code may have more than one unit test assigned to it, in order to cover the full behavior of the block of tested code.

A block of code cannot be tested using a unit test because a unit test cannot use external data. Therefore the unit test needs to run in isolation. Because unit tests must run in isolation, this helps to improve the design of the code base to ensure that no function relies too heavily on other parts of the system. Doing this prevents code smells which can lead a rigid system due to insufficient modularization.

Unit testing strategies

There are strategies used when creating unit tests to ensure coverage of all test cases. Some of these strategies include error handling and numerous checks such as logic, boundary, and object oriented. Boundary checks and error handling are similar in the sense that they both check the behavior of the system based on inputs that are invalid/outside the expected input range. Object oriented checks ensure that the state of persisted objects are updated correctly. Lastly, logic checks ensures that the system performs as expected given a valid input.

Benefits of unit testing

A major benefit to unit testing is the increased efficiency when testing code and discovering bugs. Whenever the system code is changed, the same set of unit tests are run. If a test fails, it is easy to identify what caused the failure because tests are small and isolated. Therefore, unit tests help catch any bugs before the system reaches production. Another benefit to unit testing is unit tests act as another form of documentation. Unit tests act as documentation because developers can read the tests to see how to code should behave. Having accurate documentation is an important part of software, so that other developers know exactly what the expected behavior of the code is.

Conclusion

This article was chosen because I enjoyed that it explained when unit testing is less beneficial unlike other resources. This allowed me to understand when unit testing should, and should not be used. I enjoyed learning more about unit testing outside of class as it is such as integral part of software development. Therefore, I plan to implement unit testing in future projects to ensure system accuracy.

Resources:

https://aws.amazon.com/what-is/unit-testing/#:~:text=Unit%20testing%20is%20the%20process,test%20for%20each%20code%20unit.

From the blog CS@Worcester – Zack's CS Blog by ztram1 and used with permission of the author. All other rights reserved by the author.

Test-driven development is a method that talks about writing tests before writing code. It emphasizes how TDD has changed software development by making testing an iterative, ongoing process rather than an end phase near the project’s end. This blog talks about the TDD process, the roots of agile development, and its cycle of testing, code, and refactoring. As a computer science major understanding modern software development methods like TDD is important. I chose this source to gain more information about TDD’s principles, benefits, and best practices. Test-driven development’s approach to testing aligns with my idea of making sure that my software is high-quality. The source ideas of test-driven development integration with CI/CD pipelines also intrigued me, as it works with the best practices. It shows the idea of TDD, where each cycle starts with a clear testable goal, collaboration, and making sure it’s high quality throughout development. Learning about test-driven development agile principles highlighted the importance of flexibility, customer feedback, and adaptability in modern software development. One key takeaway was TDD’s role in enhancing collaboration between technical and non-technical stakeholders. By aligning development with user expectations and business objectives through clear, testable goals, test-driven development creates communication gaps and ensures that the software meets defined requirements. This topic means a lot to me as effective collaboration is needed for successful software projects.

The blog’s explanation of TDD’s benefits, such as improved design, and lower long-term costs changed the view of its value. Its emphasis on continuous improvement and code quality connects with my ideas of great software craftsmanship. The topic on best practices, including starting simple, writing expressive tests, and building an understandable test suite helps provide changes for applying test-driven development effectively. I plan on applying TDD’s principles and best practices in my future projects. Making sure I start simple, writing expressive tests, and building an understandable test suite are the steps I want to add to my skills. Additionally, integrating test-driven development into CI/CD pipelines for rapid and reliable deployments connects with software development best practices and emphasizes code reliability. This source not only has opened my understanding of TDD but also inspired me to embrace its principles in my software development skills. Reading and learning more about TDD’s principles, benefits, and integration with CI/CD pipelines is interesting. It has given me a deeper understanding of proactive testing, collaborative development, and efficient code delivery. Using a test-driven development cycle and best practices is not just a method. It’s an idea that fosters excellence and reliability in software development. This source has made me want to approach software development with a proactive testing mindset, ensuring quality and reliability in every line of code.

https://circleci.com/blog/test-driven-development-tdd/

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