Moving from Selenium to Protractor for Test Automation

Protractor is an end-to-end Testing Framework for testing Angular as well as AngularJS applications. It helps you runs tests against your application running in a real browser, interacting in exactly the same way a user would. The first version of Protractor was released in the month of July 2013, when the framework was just a prototype of a particular testing framework. Google, however, with the support of the testing community, is evolving the framework to follow the evolution of AngularJS and to meet the needs of the community that is using AngularJS.

Why use Protractor over Selenium?

Test Your Application like a User

Protractor framework is built on top of WebDriverJS, which uses native events and browser-specific drivers to interact with your application exactly like a user would. It is based on Behaviour Driven approach which allows even a non automation tester to test the application without expertise in automation tool. Example –

describe(‘angularjs homepage’, function() {
 it(‘should greet the named user’, function() {
   // Load the AngularJS homepage.
   browser.get(‘http://www.angularjs.org’);    
   element(by.model(‘yourName’)).sendKeys(‘Julie’);

   var greeting = element(by.binding(‘yourName’));

   // Used to assert that the text element has the required expected value.
   // Protractor patches ‘expect’ to understand promises.

   expect(greeting.getText()).toEqual(‘Hello Julie!’);
 });
});

Advantages over Selenium

JavaScript automation frameworks involve working on asynchronous execution, callbacks, anonymous functions and promise, which is a sequential activity just like finding an object and perform operations on it. Another advantage of transitioning to Protractor/JavaScript is that both the application and the test codebase would be written in the same language.

For Angular Apps

Protractor provides support for Angular-specific locator bindings, which allows you to test Angular-specific web elements without any need for additional setup effort. It has extra locators compared to selenium webdriver. Examples include model, repeater, binding etc.

Angular JS applications have some extra HTML attributes like ng-repeater, ng-controller, ng-model which are not included in Selenium locators. Selenium is not able to identify those web elements using today used Selenium code. Protractor on top of Selenium can handle and control these operations in Web Applications.

Example –

element(by.model(‘locator’)).sendKeys(‘text’);
element(by.binding(‘locator’)).click();

Automatic Waiting

When it comes to waiting for elements on a web page, there is no need to add waits and sleeps to your test. Protractor automatically executes the next step in your test the moment a webpage finishes all pending tasks. There is no need to worry about waiting for your test and webpage to sync in. Protractor, moreover, also speeds up your testing as it avoids the requirement for a lot of “sleeps” and “waits” in your tests, which in turn optimizes sleep and wait times.

Supports Extensibility

Since protractor is a node.js application, can utilize the wide variety of packages that are available in the node. One can extend the framework or add additional features by installing node packages. For example, if you need HTML report you can just use Jasmine HTML Reporter for the clean code you can install eslint or tslint. Likewise, you can install node packages of your choice.

Supports Control Flow

Application Programming Interface (API) is based on promises, which are managed by control flows and adapted for Jasmine. Protractor APIs are purely asynchronous. It maintains a queue of pending promises, called the control flow, to keep execution organized.

Jasmine System Architecture
Jasmine System Architecture

Asynchronous Behavior

Works on NodeJS, so that the asynchronous process helps to speeding up the execution.
Here is how you it is achieved.
 
1) Promise Manager/ Control Flow

It is an abstraction that makes every action to be called one by one, like a queue. Every action returns a special object – Promise. These represent the result of async operation.

2) Second way – async/await

It is new abstraction around promises objects and allows easily chaining actions one by one. The advantage in this is native language construction, instead of Promise Manager, which makes your code look like synchronized, with try/catch and other familiar constructions.

describe(‘angularjs homepage’, function() {
 it(‘should greet the named user’, async function() {
   await browser.get(‘http://www.angularjs.org’);
   await element(by.model(‘yourName’)).sendKeys(‘Julie’);
   var greeting = element(by.binding(‘yourName’));
   expect(await greeting.getText()).toEqual(‘Hello Julie!’);
 });

“await” is like “suspend code execution until a promise returned from the action is resolved”.

Images and Screenshots

Image comparison is very easy in protractor and it works great. Protractor helps you take screenshots on demand and create them in any place needed. You just need to specify the type of Reporter that you want to use.

Example –

jasmine.getEnv().addReporter(new HtmlReporter(){
this.specDone = function(result){
if(result.failedExpectations.length >  0){
//take Screenshot
}
}
}

Conclusion/ Summary

There is a big world of Protractor out there and there are hundreds of packages available in the market offered by NPM to add more features to your test in addition to simple test scenarios.

Which are the Frameworks for Automation Testing?

Test automation framework utilizes software for executing tests and after that find out final the end results and the projected results are the same or not. Each and every company needs software testing satisfactorily and fast too. To achieve this, organizations are changing to utilize automated testing strategies and methods. In short, the best framework or Automation Testing is a valuable mix of a few guidelines, coding ideas, coding standards, methodology, practices, hierarchies, modularity, test data injections, reporting mechanism, and so on to build automation testing. In this manner, the client can follow such core principles while automating application to take the advantages of beneficial results.

Types of Test Automation Frameworks

The best framework for automation testing is as follows:

Carina

Carina is chiefly a Java-based test automation framework built on top of the well-admired open-source solutions (TestNG, Selenium, and Appium) which allows reducing dependence on a specific technology stack. Unites every single testing layers: mobile applications (hybrid, native, web), WEB applications, databases, REST services; Assists each common and the famous browsers (Chrome, Firefox, IE, Safari) and mobile devices (Android/ iOS) – it reuses test automation code between Android/ IOS up to 75-85%; As far as this framework is constructed in Java, it is cross-platform. Tests may be simply executed both on UNIX or Windows OS.

Selenium

Selenium is an incredibly admired open-source automation testing tool. There are two important parts to Selenium. One is Selenium WebDriver, which is the base framework that assists you to deal things like click buttons, set text in fields, and check values on the screen. Another part is known to be as Selenium IDE, a plug-in for FireFox that you can utilize to record the actions you take and the export them to the language (any) to run later.

Serenity

If you are searching for a Java-based framework that integrates with Behavior-driven development (BDD) tools like Cucumber and JBehave (keep your test scenarios at a high level) while accommodating low-level execution facts in your reports, Serenity (also called as Thucydides) might will be the best tool. This tool is perfectly designed to make writing automated acceptance & regression tests easy. It acts as a wrapper on top of BDD and Selenium WebDriver tools.

Cucumber

It is a Behavior Driven Development (BDD) tool which is used for writing acceptance tests for the web applications. The key qualities are as follows:

  • Fast and easy set up and execution;
  • Allows reusing code in the tests;
  • Cross-platform;
  • Previously implemented in Ruby, extended to Java framework;
  • Both specifications, & test documentation, is uploaded in a sole up-to-date document;
  • Useful for the users not familiar with testing. In short, those who can’t read the code;

Cypress

Compared to other tools on this list, Cypress is a more developer-centric framework that significantly focuses to make TDD a reality for developers. It has a separate architecture than Selenium. The fact is while Selenium WebDriver runs slightly outside the browser, Cypress runs inside of it. It also makes it easy for dropping a debugger into your application, which in turn, makes it easier to use the developer tools while you are developing.

Watir

Web Application Testing in Ruby is the oldest framework which is perfectly designed to support users to automate testing a web browser. Just like Selenium, it is a group of tools. The different library in the WATIR suite offers exceptional functions. Whilst WATIR will only support IE running on the Windows Operating System, you can access many others using an exceptional execution of WebDriver called Watir-WebDriver

Appium

Appium is perfectly designed to test mobile applications. It is built with the plan that you shouldn’t be recompiling your application or modifies it in any way to test it.

Apache JMeter

Apache JMeter is flawlessly designed for load testing and can be used to test performance both on static and dynamic resources, Web dynamic apps. This specific tool can simulate a heavy load on a server, network, or object to test its strength or to scrutinize and calculate overall performance under diverse load types.

Robotium

Robotium is a test framework made to make the task simpler to write powerful and solid automatic black-box UI tests, particularly for Android. With the help of Robotium, developers are able to write system, function, & user acceptance test scenarios covering several Android actions.

These are the top test automation frameworks for 2019. It is always better to automate the testing process to save extra money, effort, time, and lessen the number of testing errors.

Trends of ERP Testing to Watch for 2019

ERP (Enterprise Resource Planning) systems no longer necessitate any sort of introduction. For businesses, investing in a good system no longer is an alternative. It is a necessity. Enterprise Resource Planning systems have been a part of the business software landscape for a long time. Ever since their foray into the world of business, vendors are incessantly evolving them, so they are more powerful, robust, simpler to use, and affordable.

The 5 Major ERP trends that we should consider in 2019:

1.Competition from Disruptors- The Enterprise resource planning behemoths that have conquered the industry are encountering stiff competition from new, often Software-as-a-Service (SaaS)-only startups & the proliferation of fresh trends threatening to upset how enterprises collect and process data, and also operate. Renowned companies like FinancialForce (already having more than 1,300 Enterprise resource planning customers) and Kenandy are creating solutions based on the Salesforce App Cloud to make them alluring to users of the popular CRM and sales automation tool. On the disruption side, data visualization, big data, and artificial intelligence (AI) top the list of newest technologies that threaten to alter the way Enterprise resource planning systems are built and used. Enterprises looking to update their Enterprise resource planning systems in the year 2019 will need to become aware of to how their new prospects handle such trends. Database performance will be the core performance indicator (KPI) for Enterprise resource planning in 2019.

2.Enterprise resource planning, SaaS, & Hybrid ERP- Enterprise resource planning apps are stored on your servers, which mean you are responsible for long-term hardware maintenance, hardware costs and data backup and recovery. SaaS-based applications are stored on cloud-based servers, which are much less costly, very fast to upgrade and scale, and don’t take up clunky servers. Hybrid ERP systems are becoming famous in some sections as long-time Enterprise resource planning customers enjoy the ability to move certain Enterprise resource planning functions to the cloud while sustaining tight, on-premises control over other facets, particularly those most vulnerable to compliance regulation.

3.Focused on Social Media and Digital Marketing- These days, Enterprise resource planning is specifically focused more and more on functions than marketing, but those modules will need to become social media-savvy by the year 2019. Future Enterprise resource planning systems will need to be able to integrate direct marketing & data gathering links across manifold social media channels to remain on the top list and highly competitive.

4.The Internet of Things (IoT) is going to stay- As more and more products and devices become connected to the internet, more data can be instantly funneled into the Enterprise resource planning system, and that’s an advantage that can’t be ignored. This trend offers better oversight over things like the supply chain and appliance performance, and it also gives overall data pool for good decision making.

5.ERP for the Subsidiary- As more Enterprise resource planning systems are being delivered via the cloud, it is becoming far easier to deploy such SaaS-based tools incrementally. Rather than replacing ERP whole-hog, big giant companies are selecting one slice of the business and plugging in SaaS Enterprise resource planning on a trial basis. This approach lets businesses observe SaaS Enterprise resource planning performance to evaluate how it might fit into the existing on-premises Enterprise resource planning implementation—or whether it should replace on-premises Enterprise resource planning throughout the whole enterprise.

Agile Digital Transformation

Let us understand what exactly AGILE is all about–

AGILE – A term coined in 2011 by a small group of people who were tired of the traditional approach of Software Management of developing projects.

Agile helps teams to provide fast and unpredictable responses to the feedback they receive on their projects.

The twelve principles of agile development include:

1.Customer satisfaction through early & continuous software delivery – Clients are happier if they don’t have to wait for extended periods of time and receive working software at timely intervals between releases.

2.Accommodate changing needs throughout the development process – Whenever there is a change in requirement or feature, it should not cause a delay in the development process and get accommodated easily in the software.

3.Frequent delivery of working software – As Scrum operates in software sprints or iterations, this ensures regular delivery of working software.

4.Collaboration between the developers & business stakeholders during the project – Better decisions are made when the business and technical team collaborate.

5.Support, belief, & motivate the people involved– The unhappy teams cannot deliver their best like the motivated teams. So, support and trust are needed on the team.

6.Enable face-to-face interactions– There is no miscommunication when teams are co-located which not only saves time but also gives better interaction result.

7.Working software is the prime measure of improvement– The ultimate measure of progress is delivering functional software to the customer.

8.Agile processes to support a consistent development pace–Agile process establishes a routine through which teams establish an iterative and maintainable speed through which they can deliver functional software, and they repeat it with each release.

9.Attention to technical aspect & design enhances agility– The apt skills and righteous design ensures the team can maintain the speed, constantly improve the product and back up the change.

10.Simplicity– Develop just enough to get the job done at the moment.

11.Teams which are self-organized encourage great designs, requirements, and architectures– Motivated and Dexterous team members who have the decisiveness, take ownership and interact regularly with other members of the team and share designs that deliver standard products.

12.Regular reflections on how to become more and more effective– Self-evolution, process betterment, advancing expertise, and techniques help the team members to work more coherently.

The aim of Agile is to merge development with the business needs, and the success of Agile is evident. Agile projects are customer-centric and advocate customer guidance and engagement. Because of this, Agile has grown to be an overall view of software development throughout the software development industry and an industry all by itself.

What is a digital transformation?

It is the unification of digital technology into all areas of business, radically changing how you utilize and yield value to customers. It is also an aesthetic change that requires organizations to continuously confront the status quo, investigate, and get comfortable with unfulfillment. 

Digital Transformation is the unprecedented use of digital technology to resolve conventional problems. These digital solutions capacitate inherently new types of innovation and artistry, rather than simply upgrade and support conventional methods.

What is AGILE DIGITAL TRANSFORMATION?

An agile transformation is an act of transfiguring an organization’s form or nature gradually to one that is able to accept and advance in an adaptable, cooperative, self-organizing, fast wavering environment. The Agile Manifesto values and principles can be followed and taught throughout any type of establishment as it does not just apply to development teams.

The whole establishment needs to interpret the clarity of an agile transformation and the value of it in order to gain from the rewards of achieving true, healthy agility. The whole cultural and organizational mindset must change to one that embraces a culture of self-organization and collaboration.

Principles of Agile Digital Transformation:

PRINCIPLE 1:  START WITH A TRANSFORMATIVE VISION

As per a recent Gartner survey, 63% of business leaders stipulated they don’t exactly know what would be the possibilities of next-generation technology. Not astonishingly, just 13% of respondents said they have discovered the next paramount digital business technology investment. The reason for this is that the company lacks a transformation vision that will plan out a digital strategy and, more importantly, give the business the ability to measure progress and make real-time adjustments to improve outcome. Superior management must create, be coherent, and interface the compelling future digital vision.  Transfiguration does not happen bottom-up.

PRINCIPLE 2:  FOCUS ON BUILDING DIGITAL CUSTOMER ENGAGEMENT

Successful digital transformations are always built on front-end customer experience, unlike traditional digital projects. There should be more and more exposure to new growth opportunities by adding digital features to products as well as by changing direction and considering how the products and their services adapt to the digital customer. To create a value we need not use technologies and tools as an integrated package instead there should be sets of applications that can automate the user experience through social, data, cloud and mobile.

PRINCIPLE 3:  SUPPORT THE VISION WITH SECURE DIGITAL PLATFORMS

The organizations must always prioritize risks germane as per their specific operation. As the hottest application in need is for security, there should be smart tools to manage the risks for detecting the intrusions quickly and to respond in real time. The key to liberating the existing IT assets and enabling digital innovation with growth is the interface to digital components. The security of assets and data is paramount, the right strategy will support the speed, safety, and growth required in today’s digital economy.

PRINCIPLE 4: DRIVE INSIGHT WITH DATA-DRIVEN VISUALIZATION

The growing digital organizations not only persistently collect data but identify and envision that data in a context that induces insights that can be acted upon. The solution to unlocking real-time data intelligence for zestful and unified customer engagement is comprehending and address customer personas and micro-segments.

Traditionally companies have a reasonably strong foundation of sales transactional data. However, this data often lacks the necessary dimensionality to create meaningful demographic, attitudinal, and predictive insights. In addition, data rarely is augmented by leveraging publically available and purchased data.

Many organizations are using data visualization to communicate information clearly and efficiently to users through statistical graphics, plots, infographics, and dynamic tables and charts. Effective envisions helps users in examining and reasoning data and documentation.

PRINCIPLE 5: EMBRACE DIGITAL AGILITY TO CREATE ADVANTAGE

Due to the constantly changing customer and market conditions, Business leaders often wrestle to execute extensive projects. The conventional business model features unconnected, unintegrated platforms by business function and projects with 6-18 month lifecycles. Oftentimes, by the time the project is accomplished, market and user requirements have changed with success criteria and ROI seldom realized.

To circumvent these perils, firms must grab adaptable differentiation by developing a “digital agility advantage” that allows a company to embrace market and operational changes as a matter of routine through the use of digital technologies. Digital agility initiatives are rooted in 30-day sprints with new iterations built better and faster. This allows a company to constantly evaluate and modify – the concept of learning, launch, re-learn, re-launch – rectifying the perspective in attainable iterations. Thriving organizations in the digital age must exhibit an awareness of how to be agile; only then, they would be able to execute in an agile way.

How AI Adoption Actually Bang and Turn QA Expectations?

Software testing industry is becoming extensive with every passing day. With the sudden boost in the technology challenges, apps are growing in complication which creates an incessant need for effective software testing. Software testing is the premeditated way where an app can be observed under definite conditions and where software testers can detect the risks involved in software implementation. Testing is an imperative process that guarantees customer satisfaction within an app and assists to safeguard against potential failures that may prove to be detrimental down the line. It is a planned procedure where the app is reviewed and analyzed under definite conditions to understand the overall risks and threshold involved in its implementation.

According to the State of Testing Survey 2017, the future is about the automated test as 62% of respondents believe it will boost in the next few years. According to the similar report, we can also expect testers spend extra resources and time on testing mobile & hybrid apps, with the time used on actual development shrinking. When it comes to automation tests, Artificial Intelligence is being extensively used in object app categorization for all user interfaces. Here, recognized controls are classified when you create tools & software testers can pre-train controls that are generally seen in out of the box setups. Once the hierarchy of controls is observed, software testers can create a technical map such that the Artificial Intelligence is looking at the HUI (Graphical User Interface) for obtaining labels for the diverse controls.

Artificial Intelligence in Software Testing

Simply said, Artificial Intelligence is the science behind computers performing significant tasks that are traditionally performed by individuals. It provides machines with the critical skill to process information about its conditions & learns to adapt to the changes and modifications. Machines are learning more rapidly than ever given the technology advancements. The computer is fed with a high amount of data to adapt as per a series of inputs so that it can recognize patterns and logic and as a result make an effectual connection between similar input & output pairs. It is all the way through machine learning that websites like Amazon and Netflix are able to bring targeted advertisements to their customers by using vast amounts of data based on the web pages the user searches. Machine Learning has to turn out a long way with people using it for driving cars without a human. Artificial Intelligence has become quite popular in the field of healthcare also as it is used to recognize high-end flaws and loopholes. As Artificial Intelligence begins to progress, technology experts around the world are finding means to leverage its potential in the software testing field as well. It is merely a matter of sometimes when training apps to be familiar with issues for agile and more efficient testing becomes a reality.

AI is one of the best choices for developers looking for speedy deployments with insufficient infrastructure. It is better to leave the arduous or strenuous work to the Artificial Intelligence-powered automation which leaves only 18-20% of the test work to human ingenious and cognitive ability. It would guarantee more fail-safe results as hand-crafted testing doesn’t just require long human hours but is also susceptible to imprecision’s and inconsistencies. Quite the reverse, Artificial Intelligence bots-based testing requires very less maintenance and is skilled enough to find out new trails through the product on their own. As industries realize the compensation of Artificial Intelligence and Machine Learning, developers are considering it to drive automation, facilitate decision making, and also perk up efficiency in the area of software testing. Machine learning and AI are unquestionably becoming vital components in Quality Assurance and software testing as well. By adding Artificial Intelligence to test creation, execution, and data analysis, expert testers can rapidly identify controls, spot links between defects as well as other components, and eliminate the requirements to continually update test cases by manual means.

Conclusion

The biggest “A-ha!” moment for us is when we realized that the complications we solve with AI are not deterministic. Machine learning gives software testers the opportunity to better understand their client’s needs and respond more rapidly than ever to their changing expectations. Besides, testers now also need to analyze more data and they are given lesser time to do that, while their margin of error and flaws decreases constantly. Tools like machine learning and predictive analytics offer the amazing means to address these challenges, either with in-house well-versed tester’s teams or, turning to QA outsourcing providers. Either way, this approach is set to fill the gaps of traditional techniques of testing and make the whole process effective and relevant to the customer’s needs.