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Welcome to the 4th edition of our Annual Testing Report. This time we've taken the liberty of reaching out to experts in the field of Artificial Intelligence and App Testing...
It is necessary to check cross-browser compatibility to ensure that the app is working fine on all the web browsers. Sometimes when you open an app on a web browser it might not look or feel convenient and there might be some issues like image/test overlapping, navigation, alignment, etc. These issues degrade the user experience which will eventually lead to low traffic and existing user attrition. This is why cross-browser testing is an integral part of the QA process and should not be avoided.
Automation has reduced the time and effort put into cross-browser testing by 80 percent. The only human work goes into writing the initial test script and selecting the tool. Let’s look at the reasons why we should automate cross-browser testing.
Run Multiple tests simultaneously: When it comes to regression testing and running multiple tests for an app, automated testing saves the day. So if your app is already in the market and you launch a new version then automated cross-browser testing helps you to deliver faster. When a new feature is to be launched in the app and the build is sent to the testing team, they will take some weeks to perform all types of testing. This time can be reduced to a few hours using Automation testing tools.
Improved test accuracy: Even the experienced testers can make an error while testing the app manually. Although in Automation testing the accuracy is very high and the detailed reports are recorded. Testers can review the testing process and create new Automated test with the help of those reports.
Save Time and Money: Cross-browser testing require repetitive tests and so it can be a boring and time-consuming process. These repetitive tests can be automated to save time, effort and return on investment. You just need to make sure that everything is included in the test script to avoid gray areas in the app functioning.
Better Test Coverage: The time taken to perform any web app testing is dependent on the type of feature or functionality you have to test. The length of the test affects the cross-browser testing process. For example, end to end testing can be difficult if done manually. It will take much time and effort to do so. This why automation testing can be used if you have to run the test on multiple devices with multiple browser-OS combinations.
There are many types of devices in the market with different screen sizes, OS versions, Browsers, etc. To create the desired test environment, you will have to have all these combinations and you will have to set up a device lab. This will take huge investments and efforts to maintain the lab. Also, there is an issue of geographically distributed teams accessing the devices. Apart from that, you will have minimum flexibility as scaling up or down will be difficult.
Advantages of Cloud-Based Cross Browser Testing
There are many Cloud-based cross-browser testing tools in the market which will help you achieve your testing goal without investing a lot. This is one of the reasons why cloud-based cross-browser testing is better than setting up a local test environment. Let’s have a look at some other advantages which will give you a reason to opt for cloud-based option.
Multiple Test Environment Support: Heterogeneity in the operating system versions, device screen sizes, browser versions makes it necessary to perform tests on many combinations of device/OS/browser. This means a lot of effort will be put in to test the functions of an app on multiple devices. This could be avoided by testing the app on a cloud-based device platform.
In the cloud-based testing platform, you will be able to select the devices of your choice and perform parallel testing on multiple devices without buying one. This will save you money and effort to put up a device lab. While running the test in parallel on multiple devices with different OS browser combination will save time, it will also increase the accuracy significantly as compared to testing the app feature manually.
All time access to resources: The testing team can access the tool at any time by just logging into the tool and selecting the devices according to the market research report on popular devices in the region. Testing can be performed at any time which means there is no foundation and this comes in handy when the deadline is near. Having all time access to the device cloud will contribute to continuous testing and ensure faster deployment.
Scalability: While handling multiple projects the team might have needed many devices at times and very few on some occasions. This means that most of the devices in your device lab might rarely be used and sometimes you might have to buy more to add in the environment. This improper management of resources can be avoided by using Cloud-based device platform. Here you can select the devices which you actually need to perform the cross-browser testing and as all the devices are virtual, there is no worry of managing the extra devices.
Collaboration: There are tools to communicate and collaborate with the team which impacts on your productivity in a good way. Test reports can be generated which are elaborate and provides all the information about the health of the app. These reports can be shared with the team online to analyze and resolve the issue.
Initial time and cost: To set up an actual device lab you will require dedicated cloud/network expertise and suitable infrastructure. On the contrary, if you use cloud-based platform for cross-browser testing then you don’t have to worry about the infrastructure and initial setup cost. Also, you will save a lot on maintenance cost and everything is preconfigured.
Comprehensive testing: To perform thorough cross-browser testing, you need a permutation and combination of mobile devices with different screen size, OS, browser, other features relevant to the app function. This will make a big hole in your pocket if you wish to buy that many devices. This is why cloud-based testing platforms are the best option.
There are three types of cross-browser functional testing, multi-browser testing, multi-version testing, and concurrent testing. Let’s get familiar with all three of them.
Multi-Browser Testing: The application under test is opened on different browsers like Chrome, Safari, Opera, UC Browser, etc to check if the app works consistently across all the browsers. The app feature can be tested on multiple devices of different configurations and browser combinations.
Multi-Version Testing: In this type of testing the AUT is tested with different versions of any browser to check if the functioning is smooth. So if your app supports chrome version 40.0.2214, then the app must be tested on all the versions of chrome after 40 to check the functionality. One tester can perform the task and multiple devices will be used to perform the testing.
Concurrent Testing: In this, the application under test is checked simultaneously on different web browsers. There are four variations of this testing – single browser distributed concurrent testing, multi-browser distributed concurrent testing, Multi-browser concurrent testing, and single browser and single browser concurrent testing.
Cross browser testing combined with cross-platform testing will ensure that the app works smoothly in any type of environment. Especially for web apps, cross-browser testing cannot be avoided. Studies have suggested that people uninstall the app after using it once if the UI is not user-friendly. Even the app ratings on App Store and Play Store are affected by the user experience, leading to a lower number of downloads. Enterprises can save a lot of money and build a good report among the users by proactively testing their app thoroughly.
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Testing framework plays a crucial role in the success of any automated testing process. Choosing the right test automation framework is important as it will maximize the test coverage and improve test efficiency which means a better return on investment.
There are some key points you need to keep in mind while choosing a suitable python testing framework. The framework should justify your testing needs and it should be easy to use. Check if the framework has integrations with other tools and frameworks that you might use. The features, support, stability, and extensibility are also important. So let’s compare the most popular python testing frameworks to make it easier for you to choose the right one.
It is still the most popular python testing framework that uses a keyword-driven testing approach and is used for acceptance testing. To run Robot you will have to install python 2.7.14 or any later version, python package manager, and a development framework like Pycharm.
It is an opensource tool developed by the team that made Selenium. Gauge is immensely useful while integrating continuous testing in the CI/CD pipeline. It is gaining popularity as it supports many plugins like python runner, IDE plugins, build management, java runner, etc.
Although Pytest is used for different types of testing, it is more preferred for functional and API testing. There are no prerequisites needed for Pytest, just knowledge of python will be enough to get started. It has a simple syntax which makes test execution easier.
It is a unit testing framework much like Junit but for python language. Also referred to as unittest, it has five core modules. The test loader class is used to load all the test cases and test suites. The test runner shows the result of the test executed using an interface. The test suite is a collection of test cases that are clubbed logically based on the functionalities. A test case contains the actual implementation of the code and the test report contains the organized data of the test results.
In Behave, test cases can be written in simple language and lets teams execute behavior-driven development (BDD) testing with ease. Behavior-driven development encourages quality analysts, developers, and business managers to work in collaboration to achieve higher efficiency.
All the above-mentioned frameworks have their specialties like Pyunit is used for unit testing and Behave is good for behavior-driven testing. Although Robot framework is the best tool for a beginner to learn the nuances of automation framework. It’s always better to jot down your requirements based on their priority and then choose the right python testing framework.
Test cases are the first step in any testing cycle and are very important for any project. If anything goes wrong at this step, the impact gets proliferated in the entire software testing process. This can be avoided if the testers use proper procedure and guidelines while creating the test case template.
In this blog, I am going to share some simple yet effective tips which you could use for writing effective test cases. These tips will save you time and effort while optimizing the use of resources.
Let’s have a look a the tips to write better test case template.
Domain knowledge in information technology means deep knowledge of business and operational dynamics, the risks involved and the opportunities in that particular project. It is required to follow the best practices in the domain.
It is better to break the test case into a group of smaller ones if it has too many steps. It would be easier for the developer to backtrack and repeat the test steps if an error occurs somewhere in the test script. If not done than there are high chances that the developer will miss the bug.
Before starting on the test case it is suggested confirm all the assumptions that apply to the test and the preconditions that must be met before execution. There can be data dependency or the dependencies on the test environment or any other test cases.
Relevant artifacts should be attached to the test cases. This can be done using a test management tool. At the time of product delivery, It will help to track the changes in the application. I will be easy to understand the flow of the function when there is a change at any step which will not be easy to relate otherwise.
While writing a new test case a tester can share test data wherever applicable to be used for the Test Case within the test case description or add with the specific test case step. This will save time as there is no need to look for the test data anywhere else.
If the values are to be verified then testers can specify the value range or describe what values are to be tested for a particular field. Choose a few values from each class which will give good coverage for your test.
It’s better not to mention the real test data value but the type of data which is required to run the test. In projects where multiple teams use the test data and it keeps changing, mentioning only the type of data will be a wise choice.
Use a test management tool to manages your test cases instead of using a spreadsheet. There are many test management tools that can be used to organize the test cases in one place which will increase the productivity of the team.
It is better to refer to the specification document. Assumptions about the features or functionalities can lead to disagreements between the client and the developers. This gap between the client’s requirement and the application under development will impact the business.
To write tests which are easy to understand, we have to stop coding on autopilot and pay attention to the naming conventions. It is required to name our test classes, fields of our test classes, test methods and the local variables while writing automated tests for our application.
It does not matter which team member wrote the test, others will know what feature is tested under what scenario without even looking at the test code.
If the testers miss a bug or write test cases that do not relate to the real world scenarios then it’s just a waste of resources and time. The goal is to meet the customer’s expectations and that can be attained only if the testers think from the users perspective.
It is important to write well-defined test case verification steps covering all the verification points for the feature under test. To make sure that the test Case covers all the verification points match your test case steps with the artifacts given for your project.
Do test automation when needed as it will reduce the manual effort and save a lot of time. The test scripts should be written in such a way that they can be used afterward for some other project.
Create test case template which could be re-used in the future by other teams. Also, before writing a new test case for your module, find out if there are similar test cases written already for some other project. Doing this you will avoid any redundancies in your test management tools. Call the existing test case in pre-conditions or at a specific design step if there is a need for a particular test case to execute some other test case.
Test cases should include all the features and functionalities mentioned in the software requirement. Requirement traceability matrix will help in finding the untested functions of the application.
A test run is a collection of test cases that testers should execute in a particular order. Test cases are often grouped in test runs. It’s preferred to put preconditions at the beginning of a test run rather than inserting them into each test case.
Actually, only a few of the test cases need preconditions, so the field is often left empty. A test management tool will help to customize your forms and create a test case template which will save your time and effort when writing test cases. Another thing to keep in mind is to avoid writing the same instructions several times by moving repeated preconditions to a test run.
The test cases should be well defined with comments where ever needed so that any other software tester can work on it in the future. Whatever project you work on, when designing test cases, you should always consider that the test cases will not always be executed by the one who designs them. Therefore, the tests should be easily understandable and to-the-point.
In a scenario where the person who wrote all those test cases leaves for some reason and you have a completely new testing team to work with, the entire effort spent during the design phase could go down the drain.
In the description, the testers need to mention all the details about what is going to be tested, what needs to be verified, the test environment and test data.
The information mentioned below should be there in a well-written test case description:
All the test cases should be updated with the new requirements so it’s easier to execute them in the future if there is a need. Even if some other tester wants to use the test case he/she wouldn’t have to go through the details of the script.
The tester needs to have good domain knowledge and should write presentable test cases from the users perspective. A good test case template will make it easier for testers to write good test cases. If there are only a few test steps, consider making a checklist instead and have a look at some relevant test case examples before working on your test case. A test case example will be helpful in creating test case templates too. A test management tool will definitely help in improving the way test cases are created and managed.
Today, there are many smartphone users in the world and so is the popularity of mobile apps. In order to be competent enough, mobile apps have to be unique and should provide the best user experience to increase the user base. With the users getting more informed and intelligent, the apps built should keep up with the pace. In order to be impeccable, the mobile app should undergo a rigorous testing process and during that process, the testing team faces many challenges in this aspect which will be covered in this blog. But before we dive in, let’s look at the different types of apps that are available in the market.
The creation of mobile applications is a fantastic approach to boost brand recognition, attract new clients, and improve the user experience for existing customers. In light of this, let’s examine the three primary categories of mobile apps: native, web, and hybrid.
Native mobile applications are ones created exclusively for a given operating system. As a result, software created for one System cannot be used on another, and vice versa. Native applications are more effective, quick, and offer greater phone-specific functionality. Thus, the difficulties of testing mobile apps for compatibility with native user interfaces of devices involve ensuring that such traits are preserved strictly.
Similar to native apps, web applications do not require users to download them. Instead, the users’ web browsers on their phones can access these apps because they are incorporated within the website. So, it is envisaged that web applications will operate flawlessly across all platforms. Testing teams must carefully examine the application on a wide range of real devices and browsers to ensure high app quality. Yet in addition to taking a lot of time, this operation is essential because failing to work on a few devices can severely reduce the app quality and incur heavy losses when the app doesn’t function as required.
The features of both online and native apps are available in hybrid apps. These are essentially web applications that mimic native apps in design. These applications are easy to maintain and load quickly. Teams that test mobile apps are in charge of making sure hybrid applications don’t lag on some devices. Any operating systems with the capacity to support the said features have access to all their functionality.
While each of these app types are slightly similar to each other the technical teams face a different challenge with each type of mobile application. Combining these challenges greatly increases the complexity, making the entire procedure laborious and time-consuming. Let’s quickly look into what some of these challenges are?
There are different types of operating systems available in the market such as iOS, Android, Windows etc. Also, these OS have different versions too. So, it becomes challenging to test so many versions of the mobile app in a shorter period of time. One app that works well in one type of OS may not work well in the other. It is very important to test the application with all supported platforms and their version because we don’t know where the user is going to install the application. As per research, iOS users upgrade quickly as compared to Android but in Android the device fragmentation is larger. That means the developers have to support older versions and APIs and testers also have to test accordingly.
Android comes with a mix of features and variations in pixels densities and ratios which varies in each screen size. Even in the case of Apple, the screen new size was introduced with the launch of the iPhone 6. Now, it is not just about being picture perfect screen design rather designing an adaptive screen design. Well with such a variety in screen sizes, the role of the tester becomes serious as they need to check if all the features are working well in different screens and pixel and aspect ratios are maintained well.
The picture below shows the number of devices in the market by different brands. The number of device manufacturers has increased. According to OpenSignal, there are around 1294 distinct Android phone manufacturers alone, imagine if we add up other brands. The pace with which this data is increasing is a bit alarming for the testers as the testers have to check the app performances on different devices, they would probably need a device library to do the same. The challenge remains in context to functionalities like Complex user interactions on touch screen and keypad devices as well. Having a device library is certainly is a costly affair unless emulation is adopted which can simulate multiple device types and testing can run easily on it.
Image Source: venturebeat.com
The QA team also faces challenges when it has to test the devices connected to different networks. Generally, there are 2G, 3G,4G mobile data available. These provide different data transfer speed and transmission. These varying speeds of the networks by various providers remain a challenge for the testers even today. In this case, testers have to check that the app must perform well at different network speeds and connectivity quality and a check on bandwidth usage of the app. This remains a challenge as it is partially controllable based on different network providers and connectivity access in different geographies.
Mobile Operating Systems keeps changing. Both Android and iOS have more than 10 versions of their operating systems. They keep enhancing and updating their versions for better performance and user experiences. This frequent OS release comes as a testing challenge as the testers needs to validate the complete application with each of new OS release. It is very important to test the application with the latest OS release otherwise the app performance would be a major issue and consequently loss of users using the app.
Another major challenge of mobile testing is what we call scripting, the method of defining a test. Script execution can either be manual or automated. You can write down the scripts in a document, which is then used by a test engineer who manually interacts with the test environment to determine the result, else you can run automated scripts that in turn drive interaction with the device and app, and record the results.
Automated scripting needs to be kept away from the device to be of any real use because there are so many different devices with different interface options. A script that follows strict keystrokes on an Apple iPhone would not have any chance of working on a Samsung device, because the UI is different. Fortunately, most real device automated testing software provides high-level scripting that operates on the text, image, or object layer. Device emulators can automate testexecution using a higher-level, abstracted scripting language that is not device dependent. When you use automated scripting, the cost of setting up the script will typically be higher than the cost of a single manual execution of a test. But if it is a test script that you run on a periodic basis, every time that you subsequently run the script, the more time and effort you will save. You will eventually recover the cost of initial scripting If you run the script enough.
So to conclude, to build a better user experience, an app tester needs to work had in overcoming the challenges of testing. By adopting some analytical skills and methods, testers can really cope up with these situations. For eg. Testing only those apps and OS which are mostly used by their user segment, by adopting a strong testing strategy to take situational decisions eg. Decisions regarding when to choose Automation and manual testing. Strategically, the challenges can be overcome.
The Android world is not simple. The variety of different aspect ratios and pixel densities can be overwhelming. With the launch of iPhone Xs Max which has a screen size of 6.5 inches, Apple brings new screen sizes to the iOS world as well. Though iOS developers are used to pixel perfect screen design, they now need to change their mindset to the adaptive screen design instead. For testing, it means that we need to check on various devices that all the necessary screen elements are accessible with different screen sizes and aspect ratios. There are many phones with a screen size of 5 inches which are still popular.
Traditional testing tools like selenium and QTP weren’t designed with cross-platform in mind. Automation tools for web apps and mobile apps are different. Operating systems especially Android further adds to the complexity with API level fragmentation. The most common automation testing tools for mobile app automation testing are Appium and calabash. Each tool has it’s own advantages and disadvantages and you need to choose on the basis for your app’s functioning.
Weak Hosting Controls is one of the most common issues. The server on which your app is hosted should have security measures to prevent unauthorized users Weak Encryptions can lead to data theft which will impact the trust factor of the users. Most of the mobile apps require user data such as email ID, password, age, location etc. This data should be encrypted and stored with proper security. Hackers often use this kind of data to get money out of users account online. Encryption will make it difficult for anyone unauthorized to intrude and retrieve that data rather than keeping it in plain text.
We haven’t seen much innovations in the mobile battery but the mobile usage and specifications are increasing rapidly. People are using more apps nowadays and the apps are more complex than ever. This is why testers need to test the apps power consumption because if the apps use lots of CPU cycles and some apps will also run in the background than the battery will drain out quickly. We need to make sure that the app uses less battery power so that users can use it for a longer period of time.
Mobile apps are evolving with device technology and user expectations. Developers are emphasizing on reducing the app size and battery usage. Testers play a major role to ensure that the app works smoothly and does not crash or have bugs. This is why testers must be aware of the latest trends in mobile app testing to deal with the mobile app testing challenges.
As we all know that Appium is the most preferred test automation tool for mobile applications. It is the first choice of the testers because of its flexibility i.e. it is open source, it has the best supported and highly active community of experts, Appium works across different platforms and works well with different scripting languages. Even after gaining such popularity and having a strong community base, surprisingly, the users still make mistakes while running the mobile test automation with Appium.
Here are a few common mistakes that Appium users encounter while using Appium Mobile Test Automation Tool:
1.Unrestricted X Path Usage:
Over usage of X Path could be found in case of Selenium as well but when it comes to Appium world, it has more outrageous effects because X Path is a more dynamic way to unearth the elements. But the biggest stumbling block in this scenario is its huge performance cost due to which it becomes elusive an area. This is because Google and Apple do not provide XML or XPath related queries in a way we would need them to be. All of this hospitalizes an unmanageable cost finding elements using X Path. Undoubtedly, X Path is the most trusted method but there are several other better locator methods like ‘Accessibility IDs’ that can be used in this sitch.
2. Neglected usage of Accessibility IDs:
The accessibility ID locator strategy is formulated to read a unique identifier for a UI element. For both iOS and Android, getting an element by their accessibility ID is the best method. Most importantly, it is preferable because it is quicker. It should be noted that semantically accessible IDs are different than the Web IDs. However, the two shouldn’t be combined. In many cases, the accessibility IDs are used only for the purpose of testing even though they have a larger purpose. So, in order not to spoil the accessibility of the applications just for the sake of testing, the bigger purpose of the accessibility IDs should be known. If the accessible IDs are set up on the elements to make the apps testable, the app accessibility also increases, provided that the accessibility labels are sensible to the users using them. But the foremost criteria not to make automation efforts a failure is to make the application testable in the first place.
3. Not making a testable App:
Developing an app should be a forecasted move where in the developers, even before writing the first line of code, plan to develop an app keeping the automation in mind. This they can achieve by keeping in mind the hooks and the unique IDs for the elements in order to make the app more testable. This strategic approach would be a reason for a successful mobile app test automation. Apart from this, there should also be a concentration on the different testing scenarios in order to elude the chances of overlapping before even getting into Appium coding. An open discussion forum with the development teams to discuss the plotting of right accessibility IDs, labels or Unique IDs for the application’s elements would reduce many test automation reliability concerns.
4. Disregarding Application View States:
One of the challenge faced in Mobile Test Automation is not setting up the application. Most of the developers do not set up the application in order to access specific views and user states rapidly. To quote an example given by Jonathan Lipps,one of the key contributors to the Appium project.
A shopping cart functionality of the app might have ten different tests, and ninety percent of the tests might go through the same steps of logging in and searching items to be put in the cart which is a huge waste of time.
So, your team should be able to set up an app’s state and start the test in that apposite state, straightaway. This is highlighted in Appium scenario due to the fact that the mobile simulators and emulators are slow and take longer than usual to reach to the right position on the test.
5. Query for every element visibility:
Not querying for the visibility of every element is another way to speed up the run-time of the Appium test scripts. This leads to an additional load of calls and waiting time for Appium while in the every activity of retrieving an element. The lag can be reduced by only requesting the element attributes which are important in perspective of the test code.
6. Native Testing tools – Always better?
According to some developers, usage of the native testing tools is the best way to get unfailing mobile tests. For example- Espresso in case of Android and XCUITest in case of iOS. This is not good advice as neither of Google or Apple are going to release and new automation technology. When the question is of stability, the stability of code should be chosen rather than technology and in this scenario, Appium is the best choice!
As an exception, if the development team writes the tests and it’s most comfortable in mobile SDK language, using Google and Apple providers to build development environments. Also, when the constricted test-app or test code-app code integration is needed, then Appium might not be of much help. The utmost value is that Appium provides the WebDriver layer on top of the technology, which means the code can be written in any language and acts as a stable interface to that specific automation technology. Also, being a cross-platform tool, Appium allows to saves a lot of code and architecture in case of testing both iOS and Android devices.
7. Appium is slow:
Appium might be slower in some circumstances and also there are points in Appium codes where it does not seem efficient. Appium backs upon technologies that are slower than Appium and the curators of Appium have strategically chosen to utilize slower strategies for specific instances. For eg: Appium will certainly be slower if you are relying on XPath. The efficiency of the tool depends on how it is being used. Mostly, Appium is favored because of stability than the speed.
8. Not Using Appium Documentation:
The earlier Appium docs were not very user friendly. As a result, they weren’t used as much as they needed to be but the new Appium documents have been completely redesigned and reorganized. Information about the API reference to Appium, client libraries, supported drivers and Appium commands, code examples which was not provided before is all documented in the updated version. It deserves a revisit due to its newness and can be accessed at Appium.io.
9. Not creating reusable code
Repetitive or duplicate code can cause several issues for Appium mobile testing process. When the same code is repeated in several test scripts, any updates or modifications must be copied across all instances. This increases the chance of failures and complicates the debugging procedure. It also increases the maintenance cost for the organization.
Duplicate code makes identifying the primary reason for a test failure challenging. It can be difficult to pinpoint which occurrence of the code caused a test to fail if the same code is used repeatedly throughout several test scripts. This could increase the duration required for debugging the software and expand the market time.
Therefore, it’s crucial to use appropriate coding principles to prevent these issues. This includes creating simple reusable code, utilizing libraries and frameworks, and modifying code to remove redundancies.
10. Ignoring the Test-driven Deployment
Test-driven deployment is an Appium mobile test automation approach that stresses developing automated test cases before writing application code.
It lets the developer test all the application features before being deployed. This way, they can detect and resolve any bug in the early stage. This saves not only the organization’s time but also valuable resources.
Not just this, Test-driven deployment also helps developers in developing more reliable and enduring codes. By allowing them to understand the needs and provide a solution accordingly. Which lets them create more modular, maintainable, and error-free codes.
11. Choosing the right tool for API testing
APIs may have several endpoints, each with a unique set of parameters, methods, and authentication requirements. Writing and maintaining tests that accurately reflect the behavior of the API can be challenging due to this complexity.
Another difficulty is the requirement to simulate various scenarios and inputs. Testing for different response codes, error messages, and payloads might be part of this. To ensure the API can manage a high volume of queries, developers might also need to simulate load and stress testing.
Developers use a testing framework or library like RestAssured and Postman, which provides integrated support for API testing. These tools streamline and simplify the testing process by providing pre-build methods for common API testing scenarios, these tools streamline and simplifies the testing process. Alternatively, they can mimic various scenarios and inputs using mock data or a staging environment.
Developers can test their API in a safe setting before releasing it for production. Moreover, they can evaluate the API’s capacity by simulating heavy requests using load-testing tools like JMeter or LoadRunner.
12. Need to follow a good design pattern.
In Appium mobile test automation, the Page Object Model (POM) and the Page Automation Layer Model (PALM) are popular architectural patterns. Both techniques increase automated tests’ maintainability, scalability, and reusability.
POM is a design pattern that emphasizes the creation of reusable and modular code by isolating the application’s user interface from the test automation code, making it simpler to update tests when UI changes are made. POM builds an object repository that holds all the web elements and methods.
PALM is another design pattern that builds upon the principles of POM. But unlike POM, which focuses on UI elements, PALM emphasizes creating an abstraction layer between the test automation code and the application’s business logic. This approach distinguishes the test automation code from the underlying implementation. Thus making it easier to modify the test code without affecting the business logic.
Technology and innovation are two sides of the same coin. Technology is the power that lets the mankind turn ideas into reality within no time. At pCloudy, the power of innovation has led us to stay aligned and be in pace with the dynamics of the mobile app industry. We cannot afford to let our customers stay deprived of any technological advancements happening in mobile app testing. Once again we are back with another new feature called QR code scanner and we are proud to announce that it is already launched on our platform.
Nowadays many mobile applications use QR code scanners for a product or user identification. The QR Code scanning feature in pCloudy enables users to test the QR code feature through mobile applications on multiple devices present in pCloudy. This feature ensures the smooth functioning of the QR code function present in the mobile application. To use this feature, all you need to do is upload the mobile app under test, a QR code image file, and with the help of some simple steps, you can smoothly perform testing of the QR code scanning function of your mobile application.
The app will scan the injected QR code. You can scan multiple QR codes while testing your app on different mobile devices. So from now on you can easily perform QR code testing in pCloudy. This feature is supported on Android 5.0 devices and later versions. Supported QR Code file formats are .png,.jpeg and jpg.
Watch our video on QR code scanner feature:
Android uses a centralized system for all logs and application programmers can also write custom log messages. The tooling to develop Android applications allows you to define filters for the log statements you are interested in. Log analysis is a phase of development and developers encounter it from time to time. Bug log helps in identifying the bugs in the Android application while in the development phase. Once the app is released into the market, the support engineers analyze the bug logs to resolve the issue. There are for different types of Logs available in the Android Eco-System – Application Logs, Android System Logs, Event Logs & Radio Logs.
The logging system consists of a kernel driver and kernel buffers for storing Android log messages, C, C++ and Java classes for making log entries and for accessing the log messages, a standalone program for viewing log messages (logcat) and the ability to view and filter the log messages from the host machine (via eclipse or ddms).
There are four different log buffers in the Linux kernel, which provide logging for different parts of the system. Access to the different buffers is via device nodes in the file system, in /dev/log. The four Android log buffers are main, events, radio and system. The main log is for the application, events is for system event information, radio is for phone related information and system is low level system messages and debugging.
Each message in the log consists of a tag indicating the part of the system or application that the message came from, a timestamp (at what time this message came), the message log level (or priority of the event represented by the message) and the log message itself (detail description of error or exception or information etc).
What Each Android Log Type Contains:
1. Application log
use android.util.Log class methods to write messages of different priority into the log
Java classes declare their tag statically as a string, which they pass to the log method
The log method used indicates the message “severity” (or log level)
Messages can be filtered by tag or priority when the logs are processed by retrieval tools (logcat)
2. System log
Use the android.util.Slog class to write message with different priority with its associated messages
Many Android framework classes utilize the system log to keep their messages separate from (possibly noisy) application log messages
A formatted message is delivered through the C/C++ library down to the kernel driver, which stores the message in the appropriate buffer(system buffer)
3. Event log
Event logs messages are created using android.util.EventLog class, which create binary-formatted log messages.
Log entries consist of binary tag codes, followed by binary parameters.
The message tag codes are stored on the system at: /system/etc/event-log-tags.
Each message has the string for the log message, as well as codes indicating the values associated with (stored with) that entry.
4. Radio log
Used for radio and phone (modem) related information
Log entries consist of binary tags code and message for Network info
Logging system automatically routes messages with specific tags into the radio buffer
Device Logs on pCloudy Platform.
Log format on Android
A common log format in android:
tv_sectv_nsec priority pidtid tag messageLen Message
tag: log tag
tv_sec&tv_nsec: the timestamp of the log messages
pid: the process id of where log messages come from
tid: the thread id
Priority value is one of the following character values, ordered from lowest to highest priority:
V — Verbose (lowest priority)*
D — Debug*
I — Info*
W — Warning*
E — Error*
F — Fatal*
S — Silent (highest priority, on which nothing is ever printed)
There are several directories where Android log (including those from crashes) stores and it are not standardized (i.e. some may be ROM-specific). I am putting some of common here.
/data/anr : Dalvik writes stack traces here on ANR, i.e. “Application Not Responding” aka “Force-Close”
/data/dontpanic : contains some crash logs including traces
/data/kernelpanics :- Stores “kernel panic” related logs
/data/tombstones :- may hold several tombstone_nn files (nn is a number from 0 to 10 and after 10 again repeat it)
‘Log’ command line tool
To capture Android log from the devices/emulator Below is the some command line tool. In real life project there are log capture application/tool used to capture the logs on user device and shared it back to Developer/maintainer for analysis .
adb logcat (shows all type logs for current android system
adb logcat -v threadtime (it will include date and time)
adb logcat -v threadtime> logfile.txt (Store logs in logfile.txt)
Useful filter patterns
You can use below filter in your adb command to filter logs. You can also use this filter to search your logs file(Android logs provided by user device).
adb logcat -f Save all logs into a file
adb logcat “*:E” Get all errors and fatals
adb logcat | grep -i “foo.example.” #get all logs related to “foo.example.*” tagname
adb logcat “application_or_tag_name:*” “*:S” Get all logs by application name
adb logcat -b events “gsm_service_state_change” “*:S” Get all GSM state changes
adb logcat -b radio Get all Radio events
In this blog we got the basic understanding of the Android Log System. While analyzing the Android logs from your app you can divide it in two parts, debug Logs – file coming during development and testing phase and production Log – file coming directly from end user. The best way to do it is by using useful Filter Patterns and by using Some Tool like GoogleLogTool and SonyLogTool.
We all understand the importance of software testing and how it transforms the goodwill of the business by enabling delivery of quality product to its clients in shorter delivery cycles. It becomes challenging to run the test cases manually by evaluating the quality of each line of code at every step of the continuous Delivery process. This is where Continuous testing in DevOps comes into picture.
In traditional ways of testing the software used to pass through different development and QA phases which took more time until the final delivery of the product. According to a research by Gartner, Continuous testing in DevOps is aimed at providing early and quick detection of signs of risks related to the product release. DevOps Continuous Testing is an inevitable activity of the delivery process rather than just a mere stage in the delivery process. The main purpose is to inculcate quality into the CI/CD pipeline by utilizing the key benefits of continuous testing in DevOps.
DevOps Continuous testing is a critical aspect responsible for seamless Continuous Delivery. It involves the usage of agile development methods and processes into the QA process further providing a productive testing process.
Here are a few points to understand the benefits of Continuous testing in DevOps at the deeper levels:
a. Provides Sustained Risk Analysis:
There has never been any code build that is error free and in a ready-to-release form. Even if the final release candidate has come without any glitches, passes all the tests, it has to be ‘prepared well’ for the final release and approved by the business leaders. Continuous Testing evaluates the code at a deeper level to estimate all the possible risks connected to it so that a corrective action could be taken at the right time without breaking the ‘continuous delivery’ chain.
b. Cuts down the feedback cycle:
The key benefit of continuous testing is that it evaluates the code layer by layer at each stage of delivery pipeline, allowing testers to understand the source of the problem. The actionable insights helps the QA team to act on time and avoid longer queues
c. Broader Test Coverage:
A broad range of tests can be applied throughout the testing process with the help of continuous testing tools for DevOps such as Selenium, etc. It covers both functional and non-functional testing types to increase test coverage by emulating testing like cross-browser testing, API testing, regression testing, integrated testing, unit testing and non-functional testing like security, reliability, scalability, usability and many more.
d. Delivering High Quality Product:
‘Test-early-test-often’ is the key mantra of continuous testing which is self explicable. In order to ensure delivery of high-quality product to the end user, there needs to be a process to continuously monitor the progress along the entire delivery pipeline. Achieving high product quality is the result of continuous testing that strives to finding and addressing risks effectively and by gaining feedback at the early phases of software development lifecycle.
e. Faster Software Delivery:
The whole point of introducing Continuous Testing in DevOps is to speed up the product delivery cycle. Following a multi-point testing at different stages allows the QA team to detect the glitches early and take quick corrective actions so that the final delivery is not impacted.
f. Easy Integration with the DevOps Process:
Continuous testing seamlessly integrated with the DevOps process right from the early stages of the development process rather than functioning just before the release. Continuous integration into the software pipeline enables quick fixes so that the development process can be aligned with the business requirements on time.
For a seamless experience in the entire CI CD process, Continuous testing has to be supported by the best tools for continuous testing in DevOps. For performing smooth Continuous Testing, the Automation Framework has to be integrated with the CI tool, version control and various automated continuous testing DevOps tools to execute different types of testing at various stages of the process. For example, :
Apart from these there are many other trusted DevOps Continuous testing tools available in the market for an efficient continuous testing, like JIRA, Jenkins, Bamboo, Docker, Appium, SoapUI, PagerDuty, CodeCluster etc. The concern is that not all the tools support comprehensive automation solution. Some organizations prefer to create self-made automation frameworks depending upon the version control used to enable complete automation of the CD pipeline.
Since Continuous testing is the most critical aspect to be covered by the business in order to achieve quality product release, it has to be backed by the choice of right, suitable tools and frameworks to achieve speedy and quality delivery.
Even after understanding the advantages of adopting continuous testing in the DevOps process, many organizations face the challenges of successful implementation of it. Establishment of an efficient automation framework is a daunting deal as it involves a huge investment, expertise and effort. Moreover, the organizations are not equipped with the scalable infrastructure to run tests continuously. Also, without a strong coordination among the product, development and testing team, this seems even tougher. Although there are challenges in successful adoption of Continuous testing, with a little sensibility one can overcome it. Here are a few of the key points to comply in order to overcome the challenges :
By now we all know how significant continuous testing in DevOps for any business. It essentially brings together all the stages of designing, developing and deploying the software. Merely providing a software product does not help but providing best products faster than the competitors would be the key differentiator of your business. If practiced earnestly, it provides consistent insights about the software development to ensure speedy delivery.
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In this competitive digital era, there has always been a constant demand for continuous digital improvement. Even if automation is a prominent keyword nowadays, a recent report says that only 30% of the organizations have adopted automation testing. Although the organizations invest a considerable amount of time and money in transforming their development processes, they fail to reap the benefits of the shift in the right direction by choosing only a few aspects of testing.
Change is inevitable in the software development lifecycle and in order to go hand in hand with the ever-changing dynamics and produce high-quality software, it is important to rely on implementing an effective Continuous testing Strategy. The development teams have to be focused on optimizing the delivery cycles and provide uninterrupted business experience.
Continuous testing is a type of testing in which involves evaluating the quality of software often at multiple stages of the continuous delivery process for early detection of errors ultimately providing quality software and business continuity. It involves testing in multiple developments and QA phases to achieve continuous quality and improvement. Continuous testing plays a key role in DevOps using automation tools that help developers in getting quick feedback on the defects and make changes accordingly.
Organizations want to frequent deployments but the majority are unable to even reduce their software development cycles because of a lack of effective continuous testing delivery strategy. The success comes when there happens to be a mix of both manual and automated testing consistently throughout the delivery process. It becomes really important to automate every step to move fast in aspects like test design, test orchestration, execution, etc.
Test automation strategy is the backbone of the final product that a business delivers. It should be strong and flexible enough to bear the impact of any change and every variable of the testing process. Let’s discuss how optimizing continuous delivery testing strategy helps improving the testing process and to increase the software quality:
Research says that the majority of the organizations mostly focus on specific forms of testing. For example, few businesses focus on API integration testing and UI testing and a few focus on both individually. But what they lack is a detail oriented automated continuous integration testing strategy that involves all of the above types of testing. Choosing a specific type of testing is right in some business scenarios but a business should always be equipped with a plan that can accommodate any type of testing which can be used whenever the need arises. The real comparison of continuous testing vs test automation will always persist considering the scale and requirements of the business.
Introducing unreliable and lengthy test cases in the process leads to a huge wastage of time and effort putting the QA teams to get indulged in an ineffectual analysis of each code commit. Instead, the QA teams can do a bit of testing by adding nominal test suites in order to avoid big risks and check its impact along the way. Gradually adding stable test cases. It is important to have more stable test cases than counting how many were executed especially in DevOps.
Building a comprehensive continuous testing strategy is a mandate but choosing the right test automation tool is of critical importance for achieving complete stability. It is insignificant to even think of a failure caused merely because the test automation tool couldn’t perform on the assigned UI control on the application being tested. The acceptable reason for a failed test could be either bug or design change but not because of an automation tool. A good automation tool would always add value to the organization by activating continuous release and deployment, by reducing time and maintenance costs, by increasing the reusability of the code and by providing a higher return on investment.
In order to handle complex integrated applications, introducing modular testing is the best way to breakdown application functionality. Breaking down the app functionality into modules provides a road map and makes it easier to rearrange the functionality into testing representing different workflows. Amorphous tests can be easily redressed by introducing modular testing and decoupling test data, test flow and element locator mappings.
When analyzing the test results to find out the causes of test failure, screenshots of the test execution is the best reference in order to dig deeper into the cause of the problem. A reliable automation tool automatically generates screenshots of all important interactions happening during the test run. Screenshot recording is not supported by all the automation tools; In that case, one should reconsider selecting another test automation solution to reap the maximum benefit of this feature.
Major trends like Continuous testing, automation and DevOps and demand for faster continuous delivery have raised the standards for quality software so high that everyone is trying hard to stay competitive by optimizing their continuous testing and development strategy, that too while maintaining low costs. In this situation, balancing the test execution costs cannot be ignored. At some point in time, test coverage needs to be scaled up, teams have to opt for cloud usage which is expensive and acts as a major cost burden. The best idea would be to separate high and low level test requirements i.e performing more advanced integration and compatibility tests on cloud and executing the low level tests on-premise to maintain cost balance and getting the best automation ROI.
When the development and operations teams work together, they face many operational challenges. Developers are focused on pushing a new update and testers- on maintaining the reliability of the service delivery. Connecting these two points is challenging and these challenges are overcome by introducing continuous testing and DevOps. In the long run, a business should always invest in a system monitoring tool that will help to detect the causes of the gap and back outs more efficiently.
Outsourcing the QA process extends an additional support system, giving an extra edge in delivering quality service. The veto in the world of continuous testing is that it gives and extra nudge by providing an exposure to the more specialized areas of testing like impact analysis, performance and security testing etc. It acts as a source of energy given to a focused area of the development life cycle. As a result, it becomes a win-win situation for both developers and testers.
Continuous Testing and Delivery is not a luxury but a necessity in today’s era. A well designed continuous testing strategy is the foundation of continuous testing and quality service delivery. Although the journey is full of challenges if planned meticulously, the businesses would be able to streamline and reap the maximum benefits of test automation and continuous testing.
Some testing teams set up their own staging environment to test internal servers but as there is no public access which makes it difficult to perform local testing on remote devices. So how would you test your app which can be accessed through your internal network? We launched a feature called Wildnet, that enables you to test private or internal servers using pCloudy. You can test your privately hosted apps on any Android or iOS devices and implement continuous testing to ensure reduced release cycle.
Some times testers want to test their internal servers to protecting unsecured data and credentials, hide new features, and general security. But if an app hasn’t been made public, it should not delay testing across environments. When the Wildnet feature is enabled, a secure connection is created between your machine and pCloudy remote devices so you can perform testing even if the devices are connected remotely.
User should be registered on pCloudy platform
Executables can be downloaded from below links
Manual Process to enable Wildnet
1. Run the below mentioned executable command on the terminal:
.\pCloudyWildNetWindows -i Emailadress –k accesskey -u URL
./pCloudyWildNetOSX -i Emailadress –k accesskey -u URL
./pCloudyWildNetLinux -i Emailadress –k accesskey -u URL
./Win-Wildnet -i email@example.com -k pass123 -u https://app.pcloudy.com
Note: Please use below mentioned URL for-
Public cloud(India): https://device.pcloudy.com
Public cloud(US) : https://us.pcloudy.com
Private cloud: https://private-cloud.pcloudy.com
User will get authenticated as shown in the below screenshot
This is how users can initiate Wildnet.
2. Go to the Device page in pCloudy platform, connect the device and click on Enable Wildnet as shown in the screenshot:
Open any local URL that you wish to test and enjoy local testing on pCloudy platform.
3. To disable the service simply run ctrl+c to exit
Activating Wildnet for Appium Automation
1. Run the below mentioned executable command on the terminal:
.\pCloudyWildNetWindows -i Emailadress –k accesskey -u URL
./pCloudyWildNetOSX -i Emailadress –k accesskey -u URL
./pCloudyWildNetLinux -i Emailadress –k accesskey -u URL
./Win-Wildnet -i firstname.lastname@example.org -k pass123 -u https://app.pcloudy.com
Note: Please use below mentioned URL for
Public cloud(India): https://device.pcloudy.com
Public cloud(US): https://us.pcloudy.com
Private cloud: https://private-cloud.pcloudy.com
User will get authenticated as shown in the below screenshot
2. Once the user is successfully authenticated, they need to add the capability mentioned below, in the Appium automation script.
capabilities.setCapability( “pCloudy_WildNet”, true);
3. Once the capability is added, users can perform local testing on pCloudy devices and verify the execution in live view page.
The most important advantage of Wildnet is that you can be confident about the application as you can rectify all the defects prior to delivery. Try it yourself. Use Wildnet to find more bugs and defects in your internal server before deploying it to production.
You've made the right choice in choosing the most diverse and reliable Digital Testing Playground. We are sure to transform your App Testing Game.