As the Fall semester kicks off and I begin to dive into the curriculum of Software QA and Testing I quickly realized how little I actually know and how in depth testing really needs to be. That being said I want to use my blog posts as an opportunity to learn about different types of testing. That lead me to go with the article “A Simple Guide to Interoperability Testing” written by the team over at ThinkSys. I really had no idea what Interoperability Testing was before I read this so I decided to learn. I also liked that it was written in 2017. I know a lot of software topics have remained the same for decades but there’s something refreshing about reading something that has been published more recently.

First off, interoperability testing is a type of non-functional testing. This means it is testing the way a system operates and the readiness of the system. In the most general sense interoperability is how well a system interacts with other systems and applications. A great example provided is a banking application system (seen below) where a user is transferring money. There is data/info exchange on both sides of the transfer without an interruption of functioning to finish the transaction.

The testing of the functionality that takes place to allow a fluent interaction between systems is what interoperability testing really is. It ensures end to end functionality between systems based on protocols and standards. The article covers 5 steps to perform this type of testing. They consist of:

1. Planning/Strategy: Understand each application that will be interacting in the network
2.  Mapping/Implementing: Each requirement should have appropriate test cases associated. All test plans and test cases are developed.
3. Execution: Running all test cases and logging and correcting defects. Also retesting and regression testing after patches have been applied.
4. Evaluate: Determine what the test results mean and ensure you have complete coverage of requirements.
5. Review: Document and review the testing approach, outline all test cases and practices so further testing can improve on what has been done.

Some of the challenges that can arise with interoperability testing include the wide range of interactions that can take place between systems, testing multiple system environments can be difficult, and root causes of defects can be harder to track with multiple systems involved.

After reading this article I can definitely see the complexity in interoperability testing. Taking an iterative approach seems like it would be the best method because you can use your results each iteration to create better test cases and more coverage. Trying to tackle all the test cases in one execution would be overwhelming and it would be difficult to have close to full coverage. It seems like interoperability testing would need to take place anytime an application is updated as well to make sure the systems that interact with it are still compatible. Now that I have a general understanding of interoperability testing I am certain it will play a role in future jobs and work I do. With today’s technology, it is rare to have a complete standalone application that doesn’t interact with additional systems.

In conclusion I enjoyed this article because it was simple, to the point, and I was able to retain the information.

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

After a discussion with a friend about the recent eclipse, the subject of the apocalyptic end of the world came up. I was reminded of Y2K, and decided that it may be worth some research, as I was too young at the time to really understand what was truly going on. As a student of computer science, perhaps it would provide me with some important examples of things not to do in my own coding. On a blog post written by Steve Rowe for Microsoft Developer, he shares what he learned from an instructor about the true cause of the Y2K scare, a lack of implementation of the DRY, or the Don’t Repeat Yourself principle. Y2K was caused not by mistakenly representing a four-digit year with too few digits, but by making this error over and over throughout and across multiple files. Unless absolutely necessary, code with identical or near-identical functionality should not be duplicated. Following the DRY principle makes maintaining and repairing code easier and simpler; it is important that those striving to become excellent programmers follow this principle.

While my mistakes are not going to cause the same devastation as the mistakes of the developers that caused the Y2K scare (yet), they have certainly caused me a great deal of frustration while programming for assignments or personal projects. On more than one occasion, I’ve found myself repeatedly trying to remedy a certain piece of code, only to find out later that the error was caused by similar code that was implemented elsewhere. It was this duplicated code that was actually responsible for the error, not the unused or irrelevant piece that I had been wasting time attempting to correct. My failure to follow (or even be aware of) the DRY principle, which I was unfamiliar with before looking over the syllabus for Software Construction, Design and Architecture has resulted in countless hours of wasted time and energy. Any programmer, no matter how good he or she may think they are, could always stand to improve. Not only will following the DRY principle allow your code to be more easily understood by others, it will make writing documentation and performing any maintenance much simpler. Steve Rowe makes an interesting comment before closing his post, stating that, if duplicating code is deemed necessary, “It might not be a bad idea to put a comment in the code to let future maintainers know that there’s similar code elsewhere that they should fix.” If we all attempt to better follow DRY and Rowe’s advice, maybe we can avoid future Y2K-esque scares.

From the blog CS@Worcester – ./George Matthew by gmatthew and used with permission of the author. All other rights reserved by the author.

http://creately.com/blog/diagrams/class-diagram-relationships/
I thought class diagrams were complex when first introduced, but this blog post breaks it down into simple concepts that are easier to understand. This article has helped me a lot in learning the current course materials on class diagrams. It has helped me to determining and distinguishing the different components in class diagrams and their relationships, which are applicable in object-oriented modeling.
As stated in the article class diagrams are the main building blocks in object-oriented modeling. Their main function is to show the relationship between different objects in the system. This includes their attributes, operations, and relationships among them. Classes in a class diagram are represented as boxes partitioned in three. An example of a class is the loan account with three partitions. The first is the class name, which in this case is loan account. The middle is the class attributes which are the type, accountName, dateReleased, and loanAmount. The last is the method or possible operations associated with the class. The example shows all of the relevant data of a particular object in a systematic and clear way. A class diagram is simply a collection of classes.
Relationships between classes are interrelated through different types of logical connections. The following are the different types:
Association – encompasses just about any logical connection or relationships between classes.
Directed Association – shows directionality with an arrowhead, arrowhead depicts a container-contained directional flow
Reflexive Association – occurs when classes may have multiple functions or responsibilities.
Multiplicity – active logical connection when cardinality of class in relation to another is depicted.
Aggregation – formation of particular class as result of one class being aggregated or built as a connection, directionality is a diamond shape near the parent class to the child class.
Composition – similar to aggregation, difference being emphasizing dependence of contained class to life cycle of container class, directionality line is a diamond shape adjacent to the container class and directionality arrow to the contained class.
Inheritance/Generalization one associated class is a child of another by virtue of assuming same functionality, to show relation a solid single arrowhead is drawn from the child class to the parent class, with the arrowhead unfilled
Realization – shows implementation of functionality defined in one class by another class, relationship is indicated by broken lines.
This article was a overview of class diagrams. I chose it for its simplicity in explaining design concepts. It is worth reading for someone looking for a review and it has helped me a lot in understanding the course materials.

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