The blog post this is written about can be found here.

I picked this blog post because because we’ve been utilizing mock objects in class lately, and this post explains in-depth the logic behind using them in addition to succinctly summarizing the different types of mock objects.

Using mock objects focuses a test on the specific code we want to test, eliminating its dependencies on other pieces of code we don’t care about at the moment. This way, if a test fails, we can be sure it’s because of a problem in the code under test and not in something called by it. This greatly simplifies searching for faults and reduces time spent looking for them.

Mock objects also serve to keep the test results consistent, especially when the real object you’re creating a mock of can undergo unpredictable changes. If you utilize a changing database, for instance, your test might pass one time and then fail the next, which gives you no useful information.

Mock objects can also reduce the time necessary to run tests. If code would normally call outside resources, running hundreds of tests which utilize the actual code could take a long while. Mocks of these resources would respond much more quickly. Obviously we want to test calls to the actual resources at some point, but they aren’t necessary in every instance.

“Mock” is also used as a generic term for any kind of imitation object used to replace a real object during testing, of which there are several. Fakes return a predictable result, but the result isn’t based on the logic used to obtain a result in the real object. Stubs return a specific result in response to specific input, but they aren’t equipped to handle other inputs. Stubs can also retain information about how they were called, such as how many times and with what data. Mocks are far more sophisticated versions of stubs which will return values in similar ways, but can also hold expectations about how many times each method should be called, in which order, and with what data. Mocks can ensure that the code we’re testing is using its dependencies the exact way we want it to. Spies replace the methods of the real object a test wants to call instead of acting as a stand-in for the object. Dummies are objects that are passed in place of another object, but never used.

Creating the most sophisticated type of mock seems like it might take more time than it’s worth, but existing mocking frameworks can take care of most of the work of creating mock objects for your tests.

In the future I expect to write tests that utilize mocking. This post, along with Martin Fowler’s article, has given me a good starting point in being able to utilize them effectively as well as decide how elaborate a mock needs to be for a particular test.

From the blog CS@Worcester – Fun in Function by funinfunction and used with permission of the author. All other rights reserved by the author.

The blog post this information is sourced from can be found here.

I chose this blog post because it briefly summed up the general responsibility assignment software patterns, which I wanted to learn about. GRASP are patterns that serve as guidelines to which classes or objects should be assigned responsibilities. There are nine patterns in total.

A general method for deciding which class to assign a responsibility to is to assign it to the information expert: the class that has the necessary information to carry out the responsibility in full.

When trying to decide which object should be responsible for creating new instances of a class, the Creator pattern says that the responsibility of creating Class A instances should be assigned to Class B if Class B contains instances of Class A or gathers instances of Class A into one place, if Class B keeps a record of Class A objects, if Class B is closely associated with Class A objects, or if Class B has all the information necessary to create a Class A object – that is, it’s an information expert about the responsibility of creating Class A objects.

The controller pattern answers the question of what should handle input system events. Controllers can represent the entire system, device, or subsystem, in which case they’re referred to as façade controllers. They can also be use case or session controllers, which handle all system events of a use case. The controller doesn’t itself do the work, but instead delegates it to the appropriate objects and controls the flow of activity.

The low coupling pattern holds that responsibilities should be assigned in such a way that coupling remains as low as possible – that is, there is low dependency between classes, high reuse potential, and changes in one class have a low impact on other classes

High cohesion means the responsibilities in a class are highly related or focused on a single goal. The amount of work one class does should be limited, and classes shouldn’t do lots of unrelated things.

If behavior varies based on type, polymorphism holds that the responsibility of defining that variation should be assigned to the types for which the variation occurs.

Pure fabrication classes exist to maintain high cohesion when assigning responsibilities based on the information expert pattern would not. They don’t represent something in the problem domain.

Indirection maintains low coupling by assigning mediation responsibilities between two classes to an intermediate class.

The protected variations pattern assigns responsibilities that create a stable interface around points of likely variation or instability to protect other parts of the system from being affected by any variation/instability.

This post gave me ideas I can refer back to when solving the problem of which of several classes should be assigned a particular responsibility. The problems addressed by these design patterns exist in just about every software development project, so there’s no doubt I will find it useful in the future.

From the blog CS@Worcester – Fun in Function by funinfunction and used with permission of the author. All other rights reserved by the author.

From the blog CS@Worcester – Not just another CS blog by osworup007 and used with permission of the author. All other rights reserved by the author.

Today I will be talking about the decorator pattern. I found a blog on the decorator pattern by Bambielli’s Blog. The decorator pattern, according to the blog, allows objects to have new responsibilities at runtime without changing any code in their underlying classes. The blog writer then makes a point to favor composition over inheritance because it can reduce the frequency of runtime errors. It also conforms to the “open for extension closed for modification” rule of good programming. Decorating a class is essentially extending objects to add functionality at runtime. This allows things to be more current and up to date for user demands. In the UML diagram provided by the blog, the abstract decorator class extends the abstract component, which gives the abstract decorator the implementations to be used in place of the component implementations. The decorator classes extend the abstract decorator class, and provide the abstract decorator class with the current overriden methods.

The blog uses a pizza shop as an example. Pizza can come in a variety of toppings and crusts. The decorator pattern allows us to construct any combination of pizza toppings. Concrete classes DeepDish and ThinCrust extend Abstract Class Pie. The decorator pattern comes into effect with the topping decorator. The Abstract Class ToppingDecorator extends Abstract Class Pie, and the ToppingDecorator class has two decorators, PepperoniDecorator and CheeseDecorator.

The blog points out some disadvantages to the decorator pattern, one being that decorating objects manually is a hassle due to the large number of parameters to pass. The solution to this? Use the factory pattern in combination with the decorator pattern to make the objects for you, eliminating you having to manually pass all the parameters.

I chose this pattern because I am always looking to learn how to improve my code and make it  more efficient. Learning different design patterns is a great way to help my cause. The only thing about design patterns is that they aren’t always widely applicable. Most design patterns are specific for a small number of cases, so learning more design patterns helps me to overcome more situations that I face when coding. I think this blog really helped my understanding of the decorator pattern. I had looked at a few before this one, and the decorator pattern seemed to be pretty vague to me. The pizza example in this one really helped solidify my understanding of this pattern. All the examples from the other blogs had lots of code samples, and not a lot of explanation. Though simple and basic, I really liked the pizza topping example. I hope to apply this in future practice. I would like to have a program that allows users to make a number of different combinations (such as a sandwich topping program, or a car customizer program (color, size, etc.)). This pattern seems to be really effective with being able to create whatever combination of choices the user asks for.

Here’s the link: http://www.bambielli.com/posts/2017-04-02-decorator/

From the blog CS@Worcester – The Average CS Student by Nathan Posterro and used with permission of the author. All other rights reserved by the author.

This week I read on article on Automated Testing. The article explains why Test Automation software is the best way to increase the effectiveness, efficiency and coverage of our software testing. As per the article, an automated testing tool is able to playback pre-recorded and predefined actions, compare the results to the expected behavior and report the success or failure of these manual tests to a test engineer. Once automated tests are created they can easily be repeated and they can be extended to perform tasks impossible with manual testing. Because of this, savvy managers have found that automated software testing is an essential component of successful development projects. Some of the major merits of using Automated Testing over the Manual software testing are:

Automated Software Testing Saves Time and Money: Once created, automated tests can be run over and over again at no additional cost and they are much faster than manual tests. Automated software testing can reduce the time to run repetitive tests from days to hours. A time savings that translates directly into cost savings.

Vastly Increases Your Test Coverage: Automated software testing can increase the depth and scope of tests to help improve software quality. Lengthy tests that are often avoided during manual testing can be run unattended. They can even be run on multiple computers with different configurations. Automated software testing can look inside an application and see memory contents, data tables, file contents, and internal program states to determine if the product is behaving as expected. Test automation can easily execute thousands of different complex test cases during every test run providing coverage that is impossible with manual tests.

Testing Improves Accuracy: Even the most conscientious tester will make mistakes during monotonous manual testing. Automated tests perform the same steps precisely every time they are executed and never forget to record detailed results. Testers freed from repetitive manual tests have more time to create new automated software tests and deal with complex features

Automation Does What Manual Testing Cannot: Even the largest software and QA departments cannot perform a controlled web application test with thousands of users. Automated testing can simulate tens, hundreds or thousands of virtual users interacting with a network, software and web applications.

Automated QA Testing Helps Developers and Testers: Shared automated tests can be used by developers to catch problems quickly before sending to QA. Tests can run automatically whenever source code changes are checked in and notify the team or the developer if they fail. Features like these save developers time and increase their confidence.

Source: https://smartbear.com/learn/automated-testing/

From the blog CS@Worcester – Not just another CS blog by osworup007 and used with permission of the author. All other rights reserved by the author.

Last class, we were divided into teams to begin working on the software technical code review.  I thought it would be useful to look up what kinds of practices are the most effective, with regard to reviewing code.  I found a post by Gareth Wilson entitled “Effective Code Reviews – 9 Tips from a Converted Skeptic” , which explains the intuition behind the process of conducting code reviews and then provides a list of nine tips to help readers get started with their own reviews.  I hope that this article will help me be more effective in my contribution to the team’s overall review.

Wilson begins the post by listing the benefits of coducting code reviews as: it helps you find bugs, it ensures radability and sustainability of code, it spreads understanding of the implementation throughout the team, it helps new teammates get up to speed with the team’s process, and it exposes each member of the team to different approaches.  He explains that many entry level software engineers don’t appreciate the value of code reviews, at first, and that he was no different until he realized that the code reviews he was apart of were being conducted poorly. After gaining some experience and developing new working strategies at different companies, Wilson now feels confident enough to provide advice on how to conduct code reviews effectively.  His nine tips to performing effective code reviews are:

• Review the right things, let tools do the rest – IDE’s and developer tools are in-place to not only help you troubleshoot problems and assure quality, but also help you notice the small style and syntax errors that are detrimental to readability and uniformity of code.  Knowing this, you should let the tools make note of those problems instead of including them in a code review.  Ensuring that code is correct, understandable, and maintainable is the goal, so that should be the focus of any code review.
• Everyone should code review – Conducting code reviews spreads the understanding of code implementation, and helps new developers get up-to-speed with the working practices of an organization, so the ivolvement of veteran reviewers and newcomers is equally valued.
• Review all code – A proper code review means that it was done as thoroughly as possible.  Wilson believes that no code is too short or simple to review, and that reviewing every line of code means that nothing is overlooked, and that you can feel more confident about the quality and reliability of code after a rigorous review of it is done.
• Adopt a positive attitude – Code reviews are meant to be beneficial experiences and, by heading into them with a positive attitude and responding to constructive criticism appropriately, you can maximize the potential for this.
• Review code often and in short sessions – Wilson believes that the effectiveness of a code review will begin to dwindle after about an hour, so it is best to refrain from reviewing for any longer than that.  A good way to avoid doing this is to set aside time throughout the day to coincide with breaks, to help form a habit and resolve issues quicker whilst code is still fresh in the head of developers.
• It’s OK to say “It’s all good” – Not all code reviews will contain an issue.
• Use a checklist to ensure consistence – A checklist will help to keep reviewers on track.

I think these tips are useful to consider and I hope to apply them in the upcoming code review.

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

As a junior in college majoring in CS, naturally I cannot stop worrying about what is going to happen to me after I finish college. I recognize that I am not the best programmer in my major, there are plenty of colleagues I know with more experience, better grades, and stronger connections that will help move their career down the line. Comparatively, I worry about my own standing in the industry once we all graduate, so what am I to do? Firstly, enough self deprecating, I need some experience.

https://www.quora.com/How-do-you-get-a-programming-job-or-internship-if-you%E2%80%99re-a-sophomore-CS-major-but-dont-have-experience-How-do-you-choose-a-project-and-set-goals-for-it

This link is a question posted on quora.com asking how to get a job as a CS major in college with little experience outside the classroom, with advice from people currently in the field. The first person down the list of answers, Jane Huang, has particularly useful and calming advice. She goes over 5 points explaining how to answer this question, each of which can apply to various people with the same question.

Her first statement is meant to immediately disarm any person panicking and stressing out over what to do. She emphasizes that although it seems like life is hitting us fast, we are still very young and have plenty of time on our hands to gain experience with. She includes that interviewers will cut you some slack generally as they expect you to learn as you go.

Next she states that its very important to learn a framework, any framework. You can get by as long as you know either ruby on rails or django in python, since most frameworks are similar and you can adjust accordingly after you learn at least one. This isn’t a particularly daunting task, you can learn django in about a week if you practice it about three hours a day. It is also important to just start working on a project that you can manage, it doesn’t have to be original or groundbreaking, just finishing a project is good experience and something you can show as knowledge outside the classroom.

Lastly she makes the point that you might not enjoy coding, and should consider another field you might enjoy more. This isn’t meant to demotivate anybody in the field, you can do it if you believe you can do it. Her point is that if you are afraid switching your major too late and hate the idea of having to spend another year in college to make up for it, imagine spending many more years in a field you find you don’t like and dragging yourself to work every day to support yourself or your future family. Conversely, you don’t have to absolutely love programming in order to succeed professionally. It isn’t required that you have an extreme passion for programming, so really don’t think about it too much but don’t commit to it if you honestly don’t like it.

From the blog CS@Worcester – CS Mikes Way by CSmikesway and used with permission of the author. All other rights reserved by the author.

Source: https://www.tomdalling.com/blog/software-design/solid-class-design-the-liskov-substitution-principle/

SOLID Class Design: The Liskov Substitution Principle written by Tom Dalling on Tomdalling.com is a five part series about the SOLID class design principles in OOP. He starts off with a problem about inheritance. For instance, if you had a penguin which is a bird that falls under an “is a” relationship. However, when the penguin inherits from the bird class, it will also inherit the fly method. As soon, as you set the fly function to do nothing, then it violates the LSP. Then Tom explains that from applying the Open Closed Principle, subclasses must follow the interface of the abstract base class. If the class has to be altered in such a way to account for certain classes then it also violates the Open Closed Principle of being able to extend a classes behavior without modifying it. In conclusion, two solutions are presented, one is adding a method to check for a flying bird or non-flying bird. The other which, he states as a better solution, would be to create separate classes to account for a flightless type, that way the fly method is not inherited from the superclass.

After doing assignments for CS-343 revolving around refactoring a pre-existing poorly implemented code by applying design patterns. I did not realize that we touched upon the Liskov Substitution Principle before reading the blog post. However, choosing this post, serves as a great source of review material upon topics covered in class. The assignment that incorporated multiple design patterns started off with a clear application of the LSP, as the original design had two instances of overriding to do nothing. However, the criteria for our first refactor requires the LSP and other inheritance reworks.  Since we were working with Ducks, you can imagine a QuackBehavior and a FlyBehavior, that incorporated real and inanimate ducks. So, the LSP application is similar to the second solution presented earlier, in which the fly and quack methods aren’t inherited from a superclass but rather an interface later implemented by the duck class. But even though the method still does nothing, it isn’t an override method, so it does not violate the LSP.

Like other OOP principles, these exist to help achieve code that is maintainable and reusable. By acknowledging the existence of these SOLID class design principles, it will hopefully prevent future projects from projecting these type of code smells. Also, by understanding them and utilizing them wherever they suit best, my code will be cleaner, easier to maintain and add new features.

From the blog CS@Worcester – Progression through Computer Science and Beyond… by Johnny To and used with permission of the author. All other rights reserved by the author.

https://www.codeproject.com/Articles/524235/Codeplusreviewplusguidelines

This week is another blog post on code review. Unlike the other article which gives suggestions, this article is an overview of code review. So, what is code review? This article defines it as a systematic examination of programming language source codes. It main intent is to find and fix mistakes overlooked in initial development phase. This helps to improves the quality of the software and also helps give critiques on the developer’s skills, which is always an advantage to improving their skills.

Why are code reviews important? We start with some statistics. The article lists that the average rate for detecting defect is 25%, the rate found through functional testing is 35%, and that found through integration testing is 45%. In contrast, the rate of defect detection through code review is 55% to 60%, indicating that code review is one of the most important aspects of code review. The article further goes on to list some important statistics on code review that I thought were extremely interesting. Before code review were introduced into the organization, it is estimated that about 55% of one-line maintenance changes were in error. After its introduction it decreased to 2%. After code reviews were introduced it was estimated that 95% were correct the first time whereas before under 20% were correct the first time. In an experiment, a group of 11 programs were developed by the same group of people. The group were split into 2 groups. The first 5 developed without code reviews. The remaining 6 developed with code reviews. After its release into production, the first 5 had an average of 4.5 errors per 100 lines of code. The other team had an average of .82 errors per 100 lines of code. Reviews were found to cut the errors by over 80%, which demonstrates the importance of code reviews. For this study however, I wonder if for both teams the individuals had equal experiences and skills. Were both sides equally weighted? An interesting statistics is the IBM Orbit project. IBM’s 500,000 line Orbit project used 11 levels of inspections and had only about 1% of errors.

Finally, we close off this blog post with a discussion on the main goals of code review. The article lists the main intent to spot and fix defects early in the development process. The second goal is to share ideas with other team members, so that everyone can share from one another. Sharing ideas then helps to maintain a level of consistency in the design and implementation. Finally, code reviews helps to build confidence in the stakeholder about the technical quality of execution. Code review overall, helps to create more confidence and reliability in the product, since as a team it is easier to catch bugs.

Overall, I choose this article because I strongly believe a good code review is always difficult to conduct. It takes practice to be efficient. This article emphasizes the importance of code review in software engineering, but still it takes time to develop the essential skills to be effective in code reviews. That is why I chose this article this week to emphasize the importance of code reviews and to learn about its main intents and advantages in software engineering.

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