integration testing

Testing has always been a crucial part of software development. Some programming languages are created without much focus on that aspect, but then there's Golang. The Google Team made sure testing is easily performed for apps and software written on Go. We like that. Dive into the review of Golang testing fundamentals as our QA professionals share a few tips on testing Go code from their personal and practical experience. Testing in Golang: Why? Writing thousands of test cases to make sure your software works flawlessly is time-consuming. Due to that, proper and detailed testing is neglected during development and only carried out at the final stages. This may end up as a problem for both the developers and the customer. Thousands of bugs, slow performance, and constant crashes are the most common resulting issues when testing is disregarded. They can lead to a tech debt, and nobody wants that to happen. Avoiding these inconveniences is possible, but definitely requires your time and attention. Now, let's figure out what can be done with the code you've written. Namely, go test! Go unit testing Unit Testing (UT) is a fundamental starting point which helps you gain an overall understanding of the processes if you are new to testing. It is probably the most effective way to search for all undesired elements in your code snippets while testing the overall output at the same time. UT is considered time-consuming in general, but everything changed when Golang was introduced the world. Thanks to the package "testing" you can nail it in a couple of minutes. Let's get down to business and create a simple unit: package mishmash import ( "strconv" ) func mishMash(num int) string { div2 := (num % 2) == 0 div6 := (num % 6) == 0 if div2 && div6 { return "MishMash" } else if div2 { return "Mish" } else if div6 { return "Mash" } else { returnstrconv.Itoa(num) } } In Golang, managing testing files is quite easy. You just create a doc "file_test.go" and locate it in the same folder where the code that needs to be tested already lies. Let's take a look at our "mishmash_test.go". We will create several test cases in order to check whether the output corresponds to our expectations. package mishmash import ( "testing" ) func TestMishMash_Mish (t *testing.T) { if mishMash(2) != "Mish" { t.Error("Expected returned string to be 'Mish'") } } func TestMishMash_Mash (t *testing.T) { if mishMash(6) != "Mash" { t.Error("Expected returned string to be 'Mash'") } ...

Software defects are fixed easier when appropriate actions are taken as soon as the bug is spotted. Layers of additional code on top are making this task difficult and time-consuming. In fact, QA processes that take place later on after functionality is complete tend to toss businesses into deep pits of technical debt. Why Continuous Integration (CI)? Simply consider the following, one line of cold fix code costs about $3 and there might be thousands of defects in any system. Surely majority of those is of poor importance to both performance and business requirements, but any solution would operate better off without them, right? And such treatment of software development, when combined with poor decision on defect prioritization leaves many broken pieces of an app untouched thus opening doorways to usability issues, crashes ad hack attacks. Luckily there are practices like Continuous Integration in existence that are designed to test and verify all changes that are taken within development thus delivering value of decent QA and spreading it throughout the entire project. CI is also a great tool for reporting current state of things to business owners thus granting better levels of assurance in product’s stability. Being sure every single feature works exactly as planned is a significant boost in planning and marketing activities. Challenges of CI Regardless of everything stated above CI is not perfect (unlike many believe). Otherwise other methodologies and development/QA practices would seize from existence by now, right? Continuous Integration processes still seem to be overfilled with challenges like: It’s hard as hell to actually ensure all of the product’s tests are run from accurate, fresh git clones or any other SCM checkouts. If you require accurate build results treat your CI server like one of juniors that are fresh in every possible aspect and this here is their first rodeo. Use appropriate scripts to educate your server about the application under development. Every single build needs to begin from clear definitions and must remain as independent as America itself. Standalone checkouts are a great solution for small and simple apps however growth in functionality may bring chaos to such a process. Such activities can only ne tended at the beginning of the process. Large teams tend to awkwardly operate CI. The more the merrier saying does not fit in Continuous Integration. Deploys are literally in danger when there are too ...

iOS is a great platform that offers rich functionality and is amazingly designed from the Agile Development concept with a slight difficulty. Agile is centered on automation tests and requires lots of them when iOS cannot boast with a vast range of possibilities and tools on this frontier. However there are several splendid frameworks available for your use and comfort granting you the ability of choosing the best fitting one. But you do have to know your cards before you begin hence we are providing this little comparison just for you. KIF We are seeing an objective-C based framework designed for acceptance testing. This framework was originally written in Square. Now, that the introductions are over let’s get to the strong sides of the framework and it’s weaknesses: Pros: The framework itself encourages the Actor model for your testing sessions granting a great abstraction level straight to your tests. You are writing your tests in Objective-C, right? This means you will not have to make any switches nor will you have to constantly go from production to unit test code. KIF 2.0 made all that even simpler by implementing with XCTest directly. It is also integrated with Kiwi and Specta, which is nice. Cons: The development cycle. Square, the people who were starting this project abandoned it and development was done after by a certain mysterious ninja guy nobody knows of. He has also disappeared over time. Then somebody else took over. Although the person currently in charge is doing a great job I do realize keeping an entire library alone is somewhere in between hard and hellishly impossible. This may not end up in a good manner. KIF is not consistent at points. False failures are something that happens way too often with KIF and if you cannot trust your own tests why run them in the first place? Conclusion: If Objective-C tests is what you love need or will be using for whatever else reasons you may go for KIF. Frank Frank gives itself the credit of being the Selenium for iOS. Although I’m not buying that the framework however deserves some attention. If you want a piece of Frank you will require injecting a small framework sample inside your apps special build. The framework will be doing the job of a local server. You will be able of interacting with that server throughout your testing session. Commonly tests are written either in Ruby or Cucumber. Pros: There are many people who love Cucumber and Ruby and ...

Surely there is a difference between tests known as Integration and Unit tests (U tests). Yet this difference is not too obvious in many testing laboratories. So where does the border lie? To answer that we are to understand what are Unit tests exactly and what do testers mean by integration tests? Any Unit Test is There simply are several qualities that are making U tests truly Unit:  U tests are repeatable, meaning same test may be run for dozens of times or more U tests do not change. Meaning it’s result is to be the same regardless of how many times is a tester running it U tests require independence of whatever is not in memory (changing values) like data bases, networks, file systems, etc. If it takes longer than, maximum, half a second for a U test run it’s not a good Unit test at all U test is testing but one tiny peace (use case). Not more, otherwise things are getting over complicated. That’s exactly the reason why they are called U tests.   If all those required conditions are not met at their best tests will be of poor value as they would either be way too long to waste time on or will be false-positive in their majority meaning such tests are not to be trusted. Now that we are clear with unit tests… Any Integration Test is Every other test that is not fitting under the description given above. Integration tests vary from one another. There are system tests, performance tests, acceptance tests, whatever tests. They are all Integration as long as they are not Unit. What are the exact differences here? Integration tests are using data that is changing constantly Objects with little control over may be created Integration tests often reach out to local or external system dependencies The same test case may be testing multiple things at same time   This is making Integration tests: Much slower than Unit Tests are Harder to recreate and more difficult to run fully There may be more issues with collecting result data   Does all of the mentioned above make Integration Tests useless? Surely, if they had zero value whatsoever no one would be using those now. Integration tests are best used when they were written beyond Unit Tests as an additional regression level. Or they are great with legacy code issues that was written before one started using Unit tests. And I am quite sure you may think of much more cases when Integration tests are to be used, right? Share ideas in ...

Whenever there’s a talk about test automation, everybody seems to talk about unit tests. But then they want you to run integration tests, too. What’s the difference between the two and why would you want to write them? Read on to find out. Start digging here At a closer look at the two test types, there’s seemingly no clear distinction. Most people tend to describe a unit test as the one that tests just one class. However, a unit can just as well consist of many related classes with the same purpose. Others even suggest that unit tests are the ones that are fast, etc. Integration tests aim to check if several units can work well together in a team. People are usually afraid to write these as they think they’ll need to test all the system through. For those who don’t like writing tests for UI, there are two options: to get a testing framework making UI testing easy, or to start testing right one level below your UI. The first way will make sure the UI is integrated correctly with the system, and the other way will let you isolate your UI from design and allow for improving your system design. To be brief, there’s one general rule: integration testing raises your confidence while unit testing improves your design. As you can now see, it’s possible to include as many classes as you wish in your test, including even some external services, and call it whatever the current trend tells you to. Unit tests explained If you agree with the opinion that laziness drives progress, you’ll like the idea of unit tests. The thing is when writing unit tests you’ll want to be very lazy, because you’ll need to make sure you’re writing code as little as possible. Next, you also need to become overly sensitive to the code that’s not absolutely required to write in order to test this of that piece of functionality. Once you adopt this way of thinking and let it guide you through the test writing, you’ll find that the code gets easier to use, improve, fix and even understand. The basic idea of how this happens is the smaller tests you write, the smaller classes being tested you get. Since each unit test only covers a small piece of functionality, it also gives you the benefit of knowing which system’s part exactly doesn’t work, when it breaks. Integration tests explained All devs usually write unit tests while newbies tend to create integration tests without even knowing about it. Besides, despite common disbelief, these are sometimes written more easily. All you need to do ...