We all know that integration testing is nothing but a type of testing that combines different components (both software and hardware) to confirm that they work properly together to meet the set expectations. By definition, Integration Testing is the same for both Agile and Waterfall. We also know they are an important type of testing that has to be performed irrespective of the software development model. But when it comes to integration testing in Agile, there is a lot more weightage for it as the DoD (Definition of Done) principle is a core concept in Agile. Being a leading agile testing service provider, we wanted to take a deeper dive and explain how integration testing plays a major role in being agile.
Agile vs Waterfall
In the conventional waterfall approach, integration testing would mostly happen at the very end of the development cycle. Performing integration testing for the entire application itself can be hard. Moreover, solving the issues or bugs that are found can become even harder as it might require a lot of rework. But since the agile methodology employs a more test-driven approach, we would test smaller modules of the application by using unit tests. Since we start integration testing in Agile during the early stages of development, we will identify any integration issues early on and resolve them easily in comparison to the conventional methods.
But the catch here is that these smaller unit tests are all isolated modules. So there is no way you can write them off as tested completely in agile until you have performed integrated testing. There is no point in each of the modules working well on its own. It should all be able to work seamlessly together for the app to function effectively. So integration testing will be an important part of your Definition of Done checklist. But you have to make sure that the modules that are about to be tested are bug-free. In addition to that, the workflow in agile is such that there will be various changes to the modules that have already been tested earlier. So regression tests and smoke tests would come in to verify nothing is broken after the changes.
How to do Integration Testing in Agile Right?
You should have the proper environment and sufficient data to perform effective integration tests. Without a proper test environment that doesn’t mimic the hardware and software configuration in which the app will eventually run when released will only provide unreliable results. So test data plays an important role in developing a comprehensive test plan that will be useful in creating the required test environment.
Let’s take a look at two metaphors now and once again answer the question of why Integration testing is important in both agile and waterfall methodologies. If you are using the waterfall method, then very late integration testing can break your app as finding the issues can be like finding a needle in a haystack. Likewise, if you are using the agile method and fail to perform integration tests during the early stages, then you would end up with a set of puzzle pieces that don’t fit. So we hope you now understand the importance of integration testing in Agile.
Testing is essential to produce quality software. Agile approaches aim to integrate quality assurance into product development from the ground level up by having techies heavily involved with testing right from the initial stages. The idea behind this process is that if problems can be identified and corrected earlier in the design process, then the companies will be able to create defect-free products at quicker rates. Most of the agile teams are flying blind without having any proper strategies or measurements to follow. But as one of the best software testing service providers, we have been able to put the agile approach to good effect. So in this Agile Testing Best Practices blog, we will be sharing some important aspects that will help improve your performance in agile testing.
In addition to that, we will also be focusing on the inherent challenges and the many advantages that the agile method brings to the table.
How Agile testing is different from traditional testing:
Agile testing is a core part of the agile software development process. It is also very different from the conventional testing methods. Traditional testing is done in a phased manner so that the end-product doesn’t get released until all the defects have been fixed. But on the contrary, agile testing follows an iterative approach. So defects are fixed in each sprint and released right away. Testers define the success or failure of the team’s attempts to be agile as they are a part of the delivery team, making them an integral part of any agile team. So the adaptability of testers in SDLC is very important in the agile approach.
Five things make agile testing different from traditional testing, and they are
- Continuous Involvement
- Essential Tools
- Multidimensional Skills
- Effective Communication
- Quick Feedback from Testing
Agile Testing life cycle:
1. User Story Analysis,
It is important to understand the release plan and plan the user stories across the sprints in a release.
2. Test plan / Estimate,
It gives the ability to have all the high-level scenarios, requirements, and estimates in one plan. It is created for each release, and it should also be updated for every release.
3. Sprint Planning,
The purpose of sprint planning is to define what should be delivered in a sprint and how that can that be made possible. The team assembles together to achieve the required velocity of the sprint.
4. Environment Setup,
Agile is a process that requires consistent teamwork and the work environment plays a huge factor in encouraging the team to work towards a common goal. So nurturing such an environment is one of the vital agile testing best practices that can make a difference. This can be accomplished by valuing each individual & their ideas and by healthy collaboration as the process demands frequent changes.
5. Implementation and Execution,
The creation of test cases across the assigned user stories and peer review is performed in this stage. For better quality deliverables, developers can take a look at these test cases and ensure that the overall scenarios have been enlisted. The distribution of various tests based on risk analysis is vital. So test cases must comprise of all test types like Functional, UI, Usability, cross-browser, etc. So once the test cases have been created, we have to ensure if the stories are ready for testing and execute the created test cases.
6. Defect Reporting,
The ultimate point of any form of software testing is to identify the bugs and report them so that they can be fixed. So it is important to devise an efficient method to report all the encountered bugs in an effective bug management tool. Healthy real-time collaboration with the developers can be achieved only when the defect log contains information like summary, description, priority, date of identification, steps to reproduce, name of the tester, unique identifier, etc. Such an in-depth report will enable us to conduct a triage meeting to plan and fix the bugs that have been logged.
7. Release Activity,
Once we are past all the above stages, the build can be deployed for UAT where testing can be performed with a few users. If the build clears the smoke tests that will be performed by the alpha testers, then the release can be given to the beta testers who will test the build before signing it off from their end and ship it to production.
8. Getting ready for the next release,
After the release, the team should prepare for their next release. Any and all business clarifications or issues should be raised and cleared during this phase.
The Quadrants for Agile Testing Best Practices
Agile testing can be simplified by using a system of quadrants that provides necessary classifications that determine which type of test should be run, how often it should be run when it should be run, and who it should be run by. Since there are so many types of testing like acceptance testing, regression testing, unit testing, and so on. Quadrants help reduce the difficulty in deciding which test has to be used where. It will also answer the question of whether manual or automated testing is better suited for the current iteration of the product.
So, now let’s find out how quadrants work their magic. Quadrants divide the whole testing methodology into four grids. These 4 grids help the whole team to communicate and deliver the quality product on time.
Quadrant Q1 – The tests in the first quadrant are unit level, technology facing, and also supportive to the developers. Unit tests and other component level tests that test the code belong to this quadrant. In general, the tests in this quadrant are automated.
Quadrant Q2 – The second quadrant consists of tests that are system level, business-facing, and help conform product behavior. Functional tests belong to this quadrant. These tests can either be manual or automated.
Quadrant Q3 – The tests in this quadrant are system or user acceptance level, business-facing, and focused on real-time scenarios. User Acceptance Tests belong to this quadrant. These tests are manual.
Quadrant Q4 – The tests in the final quadrant are system or operational acceptance level, technology facing, and focus on performance, load, stress, maintainability, and scalability. Special tools can be used for these tests, along with automation testing.
Agile Testing Best Practices to Overcome Challenges:
Let’s take a look at some of the most common challenges that agile teams will face during testing and see how we will be able to overcome them as well.
Changing requirements is an inherited challenge of the agile methodology. This means that even if a work is already completed or half done, it might have to go through some modifications or worst-case scenario, get scrapped as well. So this will most definitely will have an unexpected change in the scope of testing.
How to master?
Testers must be ready to react to the changes or modify the processes in agile methodology as the process is itself prone to changes. Whenever there is a change in the requirements, testers should share the information of what tests they have actioned and which part of the application they have not yet tested. This can help the team understand how to make the required changes.
Not Enough Information (one-line stories):
Sometimes product owners will just have an idea of what features are required. So business owners may not even be aware of the specific requirements. In such situations, testers will not have a good set of details about the user stories at their disposal. All they might have could be just single-line information which is insufficient to build comprehensive test cases. This causes a significant amount of hindrance to the testers.
How to master?
In this situation, the testers can collect all the minutes of each requirement before they start testing and they can even come up with high-level scenarios for the stories and confirm them with the author or product owner and then approach the test cases.
Lack of Communication:
Without effective communication between developers, testers, and the product owner no process can work. So effective communication is also one of the most important agile testing best practices. Lack of communication can result in different teams flying blind with no proper goal as to what should be accomplished.
How to master?
Daily standup meetings with the team are strongly encouraged. It is also important to make sure that the meetings are not too long. Daily standups help identify roadblocks and solve them on a day-to-day basis. It also helps to keep the developers and product owners on the same page as the rest of the team.
Frequent regression testing:
As features get pushed by developers continuously, testers would have to run regression tests very frequently as the chances of the new features breaking the previous code are much higher. The other major challenge is that testers would have to test the application’s functionality correctly for all the users. Testers would also have to check the application’s behavior on different devices.
How to master?
Automation skills can be a great help for this situation in agile projects. Automating the regression test can save you a lot of time, and Selenium is the most popular browser automation tool that might solve all your needs. Apart from that, testers can use tools like Docker or VisGrid to run their automated test scripts in parallel across various browsers and devices.
As software becomes more mature, the complexity increases along with it as well. Testers should be in a position to help developers with API testing, integration testing, and more. So having strong technical skills is one of the basic requisites of a tester who is working in agile.
How to master?
Being in the process of continuous learning always helps people excel in their respective fields. Likewise, testers can learn programming languages like Java, Python, C#, etc., and learn automated testing tools like Selenium, JMeter, and so on. It is also crucial for the team to comprise dedicated testers with professional experience. If you are looking for the best agile testing tools, then you could read our blog and explore your options.
We hope you have enjoyed reading this blog and that it has been informative as well. These agile testing best practices have helped us deliver the best software testing services to our clients, and hope it will enhance your testing methods as well. Obviously, these tips alone will not equip you to face any challenge that comes your way. But these general tips will definitely help you overcome the regular challenges and also help you find the right solutions for every new challenge you would face.
For a small team, a spreadsheet is sufficient to track bugs. However, for a geographically dispersed team and an organization which has multiple groups, it is not the right choice. A bug tracking system will allow you to capture several essential information about a bug, and your team will be notified when you log a defect.
An Agile team can decide how quickly a bug needs to be fixed based on its severity. Bug severity can be determined with the following questions:
- How many will it affect?
- How much money will the company lose if released into production?
- How costly is the time to fix the issue going to be?
An agile tester should discuss with stakeholders to decide the bug priority based on the above questions’ answers.
A bug report is one of the crucial deliverables from a tester. When a bug is understandable easily, then finding a solution will be easy. Defect Description provides a glimpse of the bug. However, screenshots/screencasts will provide more detailed information about the issue.
Another vital piece of evidence is how to replicate the issue. Your team members will refer to your defect. So they should know you have found the bug.
Developers should know what Workflow you have followed to find the bug because each webpage or mobile screen may be accessed from different workflows.
The software/app under test may behave differently on different browsers/devices. You need to provide what test data you have used and which device/browser the issue occurs.
Linking Useful Information
Modern bug tracking software has an option to link other defects and stories. Developers may get the following information from the Linked defects.
- Relevant Technical details to fix the issue from the closed defect.
- Comments in the linked defect from other developers may provide some precautions.
- Developers may get some optimized SQL queries.
We, as a QA Company, use Jira for bug tracking. Software tester can earn a good reputation from a quality bug report. Our QA testers add interested parties to the Watchers list whenever a new defect is created in Jira. When a defect has all the necessary information, then the developer can understand the issue quickly. If the defect is understood, then fixing will be commenced immediately.
Misunderstood defects will lead to confusion and waste your team’s valuable time.
The main discourse in this blog is to understand the automation testing pyramid and to match that with agile work model. Automation testing pyramid defines the types of tests to be conducted at various levels, their scope and how intense the tests should be. Let’s take a moment to understand about the testing pyramid and how automation testing is performed under the governance of testing pyramid.
Test Automation pyramid and its principles
On a brighter note, Automation testing pyramid is nothing newer than what we have studied in v-model that is mapping a corresponding testing in accordance with the development readiness. But the only difference that we see is the v-model strategy doesn’t tell how intensified a test type should be, but that is very well explained in testing pyramid theory also it emphasizes the value of test automation in each area.
Testing pyramid says that it’s best way to conduct through testing in the early life cycle such as in unit and integration tests in order to prevent the bugs then a few end-to-end tests that cover most customer likely scenarios.
Let’s deep dive in about each level of testing in a hierarchical fashion and see what testing type should kick start and how much focused that test should be and what’s the value that automation is adding.
We know that in agile model the development and testing should go in parallel. In agile the development is managed in small component level initially then they integrate and after they ensure the system is developed to ensure the feature is developed.
The best way to ensure the most of the unit tests are automated since that’s the test which can give us the feedback very early also they are easier to fix, because the bug that is seen is likely happening due to the code error present in only that specific module. These tests can be run more frequently i.e. as and when there are deployments of that module we can start execute the test cases. The degree of dependency exists for this test is relatively small.
In the midst development team integrates these smaller components to perform business logic. To test the communication between the services we must consider writing some powerful integration tests.
Basically these tests are conducted at API layer. This integration testing phase is vital because in the previous stage we have ensured that a component or service works better as a standalone but it could break when it is being integrated, so in order to verify that the communication is proper through API calls & business logic is performed and finally the information has stored in database. We need to write these tests.
System testing (end-to-end)
Now we have done testing at two levels, ensured the designed services were working intended when they were as standalone also they were performing needed business logics after successful integration. If we think this testing is needed we are missing something great here. For a moment when we go back to fundamentals of testing the high level definition says, the goal is to verify that the functionality is working as intended and it should serve the purpose of the requirement.
We need to consider the user journeys that are key and what we think that are executed in the field as often as possible. Automation can add great value here as well, because the execution in the end to end phase most likely happens on UI layer and it can help us find any defect before the application goes live. Being in line with the test automation pyramid there shouldn’t be too many end to end tests because these tests however can help finding defects, they add significant delay to feedback results due to the fact that these tests have to interact with so many elements and pages.
The fact is that though we find a defect it’s very costly to fix. When we say it’s expensive, it is mainly due to two things those are effort needed to identify where that particular bug occurs then understand the bug then fix it, the second one is it is found very late in the cycle. After given a fix for the identified bug a thorough regression testing is needed as we never know that the new code change will impact any other system which would have been working before.
Testing pyramid followed in manual testing
In case of manual testing the approach is followed as per the below figure, where developers write unit tests to ensure the module works, but these tests are very minimal in number. As we go past different level of testing levels we intensify the testing we start writing more tests. Finally we end up conducting through end-end testing by testing all the customer journeys or use cases manually.
The main drawback of this approach is that, we are finding the defects but not preventing. Yes, you read it correct, the meaning for that statement can be explained as since we are not conducting through testing there could be fair chance for a particular micro service or component that is being developed may break on certain edge cases and this was hidden and when it was found later the developer had a lot of code base to look into to understand what causes the bug it apparently takes more effort than it ideally should have taken during initial stage. Moreover we require lot of regression testing to ensure the given fix hasn’t impacted any other working module.
Holistically by following the anti-cone approach we are welcoming lot of redundancy by choosing the nook to corner testing at end-2-end phase. The amount of effort needed to write automated test cases for end-to-end is vague, also the amount of time that they take to execute and provide results is relatively higher. Its lot of overhead to do that at this phase as it has high chances to skew the deadlines towards right.
If we were to brief the and re-iterate the chronicles of the test automation pyramid.
1. Start with an intensified automated testing early in the life cycle probably at unit testing and integration testing levels
2. Don’t just limit the automation to the UI layer, we must consider automating at API layer as much as we can, given the TDD approach of development in agile SDLC model.
3. Don’t overload the test pack with too many end to end test cases unless they think they are likely executed by customer and it has some important business logic to perform, believing that the other requirements would have been covered under user story based testing in earlier phases.
4. The reveres cone approach is only helpful to find the defects but not to prevent them for occurring from earlier life cycles.
5. Devops integration is best matched with the test automation pyramid it helps both the development and testing teams to trigger their tests.
Thanks for walking through the content, hope there would have been some learning.
Agile is test first model, this defines how to kick start testing in parallel with the development. The main agenda of this blog is to relate the automation testing to this model. The discussion is mainly on how to develop the test pack model so that it best suites the agile velocity and with the sprint level expectations. We, as an automation testing company, create a concrete plan while bringing automation into Agile, conduct proper analysis then understands the feasible fashion of test script development.
Designing Automation Testing Framework Given the expectation that the testing has to go hand in hand with automation we must have a proper plan of developing scripts. Whether n-sprint approach or n-1 sprint approach to be followed? Let’s quickly look at how those sprints work.
In this model, we will have to consider all user stories that are listed must be automated.
In this model we likely trail by a sprint, whatever the stories those were developed in previous sprint are automated in current sprint. Despite the model, we should always make sure that the regression pack is kept up to the date in the same fashion we have to maintain the sanity pack too.
Types of Automation testing When in agile, we build the system in many iterations and we call them as sprints. It is obvious that we will have only smaller chunks built in linear fashion. The question here is – how do we accommodate the space for test automation when UI and the whole system is not available? Because when automation testing is said, 90% of the spectators talk about automating at UI layer as that has ROI which is better.
If we think automation testing is best deployed to test UI, not others we are missing greatly the ideology. What we are meaning to say here is that we should think of automating at different layers such as API & DB validations to ensure that the system is doing the right thing. If we can ensure that at the initial stage our job would be lot easier, also it helps the business greatly as we are uncovering the bugs early in lifecycle and which are not that expensive to fix.
For an illustration let’s consider that the development approach is a TDD one, we will not have the complete system to test, rather we will have smaller modules/micro services would be developed in an incremental fashion. To support the quick testing at that level we should consider designing a automation testing framework that can have tests based on module wise. We also need to understand what are the services offered by the component and accordingly write type of tests.
Write powerful integrated API tests in order to verify the micro service – micro service communication. Perform some data base table’s validation to see the business logic has been processed successfully and information stored at right table. We will apparently not have UI developed initially so as soon as that gets ready we should be ready in testing the flows that starts from UI.
Test Automation industry has taken a big leap from documenting the manually tested functionality as scripts for future execution to the purpose of serving the need for in sprint automation due to the agile parallel test execution expectation. With following the discussed practices and understanding the strategy of development and testing need, we can design a matching automation testing framework that serves the need of the hour. There is no standard or hard coded practice as such, rather it fully depends on the context of a specific project.
Software and automation testing service companies are gearing up for quality outputs at a consistent speed. Whether it’s continuous testing, Agile, or bringing AI into automation, the software development process must stay on track and in line with swift technological changes. So to stay ahead of the game, you should adopt practices like parallel testing, which will save you time and effort.
It is a semi-automated testing process involving cloud technology and virtualization, a new framework technique that carries out tests on software products against multiple configurations simultaneously. The costs and timelines are significantly lower than traditional testing methodologies, and the ultimate goal is to resolve the limitations while still assuring quality. The process involves using separate virtual machines within the cloud since parallel testing runs more tests. Invested testing time split by the number of test machines put into use can easily be a fraction of the time involved in sequential testing.
Speed – You only need the appropriate test scripts, so you don’t need extra hours or any more computers than you already use.
Affordability – Constructing and maintaining an internal testing infrastructure means that test time on a cloud service becomes viable as it is inexpensive in comparison to traditional testing methods.
Full compatibility – The limits of sequential testing often mean you can only test the most likely scenarios. Parallel testing is unlimited; this means you can check all combinations that are useful to users.
Continuous and concurrent timing – The process can test functionality both regularly and swiftly. New code can be submitted while testing is ongoing as it supports and optimizes the widely-used methodologies of Continuous Integration and Delivery (CID).
Current and updated – If you’re always using the latest versions of applications and software, it likely means that you believe in cloud technology.
Results-driven – Testing more scenarios in less time means there is more actionable data towards improvement.
Flexibility – You can revert to sequential testing whenever necessary and therefore make your testing process to suit your needs.
Adaptability – Transitioning to parallel testing in gradual steps is easier for companies.
Infrastructure constraints: The cost to set up the test environment can take a toll on the company’s finances as the infrastructure and maintenance cost quite a bit. Mobile and networking devices will also add up expenses. You will need to hire skilled professionals to maintain the setup as well. Instead, companies can opt for cloud-based services that can be accessed from anywhere anytime and get the desired devices to test on.
Dependency on data: It is difficult to make a strategy for parallel testing if the test cases are dependent on specific data. Test scripts that are data-independent should have required configured data for the test run, and then the scripts can be modified to run in parallel.
Test and QA automation services companies like Codoid, adopt parallel testing to establish dominance in the software industry in terms of qualitative outputs in shorter periods. Clients who employ a company like ours can be sure to reduce their costs and time to market quite considerably. Our suggestion would be to go in for a cloud platform to track issues better. You can connect your Github or Jira or set up continuous integration with Jenkins, automatically running tests with every new build. Parallel testing is thus an extension of the logic that applies to all IT sectors and radically transforms testing by focusing on practicality, ease, affordability, speed, and scale.