Increasing Importance of Quality Engineering in Software Testing

How can a company win? One of the key criteria is to ensure good quality of its products and services. But the traditional testing and QC paradigm is not enough in the context of emerging technologies. It has proven to be inefficient: if some shortcomings are revealed, the product may have to be redesigned, requiring additional expenses and extra time. That is why something new is being executed in business — quality engineering solutions. Quality Engineering (QE) is the series of procedures by which software quality is analyzed and improved throughout the application or software development lifecycle. It differs from traditional Quality Assurance in that it prevents defects as well as discovers them.

The QE approach implies that every single stage of the product/ software development cycle is under a scrupulous test of quality engineers. Furthermore, the quality maintenance is offered long after the product is delivered. The execution o such strategy in manufacturing or software development procedures guarantees the sufficiency of the output from the very start reduces imperfections, flaws, and reduces potential losses. In other words, quality engineering is the analysis, development, management, and maintenance of diverse systems compliant with high standards.

What are the rewards of Quality Engineering?

With Quality Engineering, the core benefit for your application development cycle is that you are actually making all the proposed advantages of DevOps and Agile more real. Also the teamwork between developers and testers is more real, more in line with the agile ethos. It is also integrated with Test Management solutions so that the outcomes appear on the dashboard instantly, without a human trigger. With shortened release cycles, time to ensure Quality also reduces considerably. Testers have to be involved at the start of the cycle as they will be setting up the testing environment and framework which will be relied upon for all future sprints. Done right, Quality Engineering offers a great deal more speed in testing. It mainly relies more on Test Automation than manual testing. It is hard to imagine a Quality Engineering function that doesn’t have Test Automation at its center. Yet again, done right, it creates more flexibility and speed for the whole development cycle. It is not considered just functional and non-functional testing, but every single layer and integration that can and should be tested.

In current Digital era, a Quality Engineer should have experience in programming and be supposed to be able to write software as the situations demands. While the Software Development team focuses on constantly upgrading the application, the Quality Engineering team main responsibilities are:

  • Setting up new parameters and standards
  • Optimization of test cases, & improving automation efficiency
  • Identification of drawbacks
  • Generating a plan for improvement
  • Plan execution using different tools and methods
  • Assessing & implementing new technologies and tools
  • Following up to make sure that issues have been solved
  • Creating tailor automation solutions to address application specific use cases
  • Create frameworks & accelerators that help scale QE across manifold channels, Enterprise wide.

Quality engineering is driven by emerging technologies like AI (artificial intelligence), Big Data analytics and IoT. Automation is the driving force behind turning the traditional testing into an effectual quality support model.

Bottom line

Performance of the application/ software is of paramount importance. Every outage, crash, drawbacks, and even slowing down of the app or processing/ working on a client request has the potential to impact revenue directly. It is the responsibility of QE team to not only identify such issues, but also work on identifying/removing the root cause of such problems. This demands a sound understanding of app architecture, monitoring tools, several enterprise sub systems that are catering to the app etc. Overall, Quality Engineering team provides substantial insights about the root cause or issue and solved it in the fastest possible manner.

Artificial Intelligence Permeation in Testing

Software Testing is the process that ensures the customer is satisfied with the application and provides defect-free software. It allows testing an application under some conditions where maximum threshold and risks are involved in implementation. Testing ensures the quality, output and market efficiency of the software. Here comes the Artificial Intelligence (AI), which reduces manual effort and allows machines to write and execute test codes.

About Artificial Intelligence

AI allows the machine to read and process information at a very high-speed. They intelligently react to the environment changes and can learn things at a speedy pace. Some algorithms are applied that allow machines to analyze and identify data logically. It is a probabilistic approach applied to test the application. ‘AI Robots’ are introduced that performs testing with minimal human inputs. This will improve testing efficiency and decrease failure rates.

Benefits of Artificial Intelligence in Testing

  • Improved Quality: As testing is performed automatically, with assured security, the quality will be improved. It increases the market efficiency of the applications.
  • Effective: AI theories and algorithm focuses on reliable testing methods. It ends up reducing manual effort and intensive costs.
  • Timely Feedback: Since AI testing is automated it provides quick feedback on the application. It also reports the application’s efficiency.
  • Improves Trace-ability: AI checks the error by going through the code itself and leaves no error unattended. It resolves all issue and then proceeds forward.
  • Integrated Platform: Entire AI process is based on the embedded and integrated platform to run tests. Due to this, the website is launched easily by developers.

AI Robots take less time and capable to find testing paths on their own. They can be easily maintained. The bots are trained to process the data input and performs an action intelligently, like Android Auto Assistant. These bots are strengthened with time as the AI algorithms are continuously monitored to study behavior and input patterns.

Artificial Intelligence and Automated Tool

Intellectual decisions are bases for Artificial Intelligence automation when regression testing is performed. These are built on the algorithms with data and examples. The basis of AI Automation is the system’s intellectual decision-making ability. The information gathered by AI shows the application behavior, its stability, defect area, failure pattern and so on. The Artificial Intelligence System correlates the data information with existing test suites and also auto generates the test cases or test code by following the user story acceptance criteria. It supports code-less test automation on mobile or web applications. Artificial Intelligence mainly focuses on test management.

The following inputs are required to generate the tests automatically:

  1. Relevant data for the application
  2. Test results data for pass or failed use cases
  3. Requests and their valid data, that are to be run on production as well as the test environment
  4. Builds a version control monitor (can be SVN or others)
  5. Historical data, on which AI works

The names of the tools which are available to automate testing with Artificial Intelligence are: Testim, Appvance, Functionize, Endtest, Appitools.

AI Changing Test Automation

The machine learning AI is more of the statistics-based. It has transformed the way the test automation is performed. ML algorithms recognize all the patterns to predict the trends followed by an application.

Real-time examples that are following machine learning algorithms to embed AI:

  • Smartphones are using voice recognition software (e.g.-SIRI) that allow human interactions to do some action.
  • While online shopping, like in Amazon, list of recommendations to buy comes up as per previous experience is followed by Machine learning algorithms.
  • Visual Validation Automation Testing: This is an image-based testing technique done by visual validation tool. Like Applitools, it can find the differences that may be skipped by testers. This is required to verify if UI is as expected to the application users. It ensures that the UI element has correct position, shape, size, and apt color. It also tests if any UI element is not hidden and do not overlap too. For this, testers create ML test which detects visual bugs and validate the correctness. The AI system keeps screen-shots virtually in its mind to determine the state of the application.
  • Provides more reliable Selenium Automated Test: Let’s take a scenario where there are frequent changes (e.g.: changing the ID of Web element) to the application and Selenium tests fail as the element is not found. AI tools adjust to these changes automatically using Machine Learning algorithms and find locators, rather than doing changes on selector or path for the element. These AI tools start to learn about an application and understand the relationships among parts of DOM. It doesn’t break the tests and keeps track of the changes throughout time. This makes automated tests reliable and easy to maintain.
  • API Testing with AI: Some automation tools are available to remove complexity from the API testing. AI helps to simplify the process of API Testing. ‘Smart API Test Generator’ is a plugin embedded in chrome which helps to convert manual UI tests to automated API tests using artificial intelligence. It helps in building the comprehensive strategy to perform API testing. This tool identifies API calls, and then observes pattern followed and finally analyze the relationships among them. This process flow generates API testing scenarios.
  • Running more of precise test cases: When there is some change in code, it takes much effort to analyze the minimum number of tests to be run. For this, AI & Machine Learning is used to tell the precise number of tests to run. Also, AI is significant when the tester is unable to finish test-failure triage before the next build is released. Here, Machine Learning algorithm forms the ‘fingerprint’ of failed test cases in correlation with debug logs and system. It further predicts all the duplicate failures. This makes precision testing grow.

Effect of AI testing for Continuous Delivery

Testing allows developers to figure out if the application is working as expected in the real world. AI automation testing tools increase feasibility to identify the gaps in the application. AI enables testers to view wider issues, rather than just looking into repetitive ones. It offers the testers to customize the tests with combined information. These solutions are stored in metrics which tracks the success rate and perform execution cycles. The analytics collected is used to track issues in the software development cycle. Every industry is trying to learn and use AI supported apps that can automate tasks. Organizations may face multiple testing challenges when using ML and AI for testing application quality. AI algorithms optimize test suites, provide log analytics, traceability, and rapid impact analysis and get defect analytics.

Growing Demand from Performance Testing to Engineering

In the modern era, companies have been investing enormously in building next-gen products and platforms using cutting-edge technologies. Yet, there are the plethora of companies leave the assurance for scalability for quite late in the development cycle or do not follow the testing path enough. This in future lead to disruption in services and later can profoundly impact the customer loyalty, brand image, and ROI (or revenue). If the specific website is undergoing slow or poor performance, customers will have no choice but to explore alternating channels. As a better website experience is like a worthy brand, once gone astray, it becomes tricky to retain the customers. Considering the significance of speed-to-market for the success of the project, businesses need the appropriate processes, tools, and skills for an agile delivery. This is where most advantageous performance engineering and testing comes into the picture and assist your enterprise to think out of the box and stay ahead of the curve.

Why Implementing a robust strategy crucial?

Performance engineering, though, is a wide set of processes, and it is also an art based on years of scrutiny and observation that have led to proven practices. Putting into practice a robust strategy has been a cognizant and strategic decision for all types of enterprises operating across varied businesses. Today, validating and ensuring the responsiveness, speed, and stability of an application is absolutely business critical. The range of facets of Performance Testing has been adopted for the same, confirming that the app does not vacillate under unexpected conditions. Though, there has been a shift in conceptual thinking, where the awareness has shifted more from Performance Testing towards Performance Engineering. It critically refers to the techniques that are being applied in the application development lifecycle, which make sure the non-functional necessities. Some of the key necessities are ensuring usage, throughput, and latency of the memory. These features are required to confirm and to judge that the systems are secure, precise, user-friendly, and scalable over even in the long run. As recommended, it is a significantly demanding practice for Agile and DevOps teams to validate the presentation and efficiency of the applications. The careful application of the ideology of performance engineering makes it possible for businesses to support employees, please customers, and boost returns, all at the same time.

The growing recognition is because of the growing complications with new-age apps and the emerging technologies that are creating these manifold layers. Most of the apps these days engage with multiple third-party vendors and parties to drive innovation as well as growth for the customers. For this reason, it is no more a single action driven growth, it just getting increasingly complicated.

Some of the supplementary benefits are given below:

  • Reduced system & hardware expenses
  • Early detection of bugs and application defects
  • Guaranteed customer satisfaction
  • Enhanced revenue & profits with higher conversions
  • Lesser cost of change related to performance tuning
  • Improved experience & quality from a user’s perspective

Within the Agile process, the methodologies for Performance Engineering can be effectively aligned with the ‘shift-left’ approach. It helps to determine the issues way ahead in the product development process. In this fashion, bottlenecks can be identified and reasons can also be uncovered too. Furthermore, the overall system performance can be optimized in this procedure. The well-thought-out Engineering & Test strategy can enable teams to deal with all sorts of the critical challenges that are being posed by inefficiently performing applications. It aids in benchmarking the app performance and eventually assessing against business critical scenarios for efficient test. The digital sphere has countless aspects that keep challenging the app’s flawless functioning and predictable parameters.

ImpactQA’s comprehensive Engineering Solutions is consistent in mounting business revenues and dropping costs. The experts help in benchmarking the app presentation and helps you recognize each and every business-critical scenarios for tests.

Perks of Performance Testing Services offered by Specialist QA Company

As a result of the impact of consumerization from the end users, companies have moved towards a multifaceted application integration landscape with zero performance issues. For a rich user-experience, it is imperative for organisations to invest in performance and quality testing, which aids them to meet the expected software performance standards. A type of non-functional testing, software performance testing services evaluates, anticipate and manage software performance at backbreaking conditions. It also tests the stability, speed, and scalability of an application under a specific workload and ensures superior quality performance. Apart from figuring out the speed aspects of a system under a specific workload, tailor-made performance testing solutions is also used to reveal that the developed system meets the performance standard and criterion.

Best-in-Class & High-impact Performance Testing Services and Solutions

By offering the stellar application experience in the production, performance testing company reduce the adverse business effects for you. For a greater customer satisfaction, Specialist Company provides the improved version of performance and security with the efficient testing services. The unmatched testing method, which is an outcome of varied expertise work, provides key indicators and aids to detect any error and inaccuracy at an early stage, thereby, resulting in pro-active decision making. Their performance engineering framework enables implementing the techniques, right tools, and models, heightens performance dashboards and implementing supreme strategies for performance improvements.

Critical Concepts of Performance Testing

The comprehensive approach of expert Performance & Load Testing Services provider also helps track server-side, client-side, and application-side statistics helping systematize application performance. In order to make the best, expert QA firm also chooses the right tool to test a software performance by complying with the process of the specific product. Based on the factors like test execution, planning, data comparison, and bug capture, software performance testing tools can be categorized into Source Code, Functional, Embedded software, Database and Bug Tracking Tools. These tools play a critical role in testing the performance and accuracy of the software.

Performance testing Services Offerings & Types:

  • Stress testing
  • Load Testing
  • Volume Testing
  • Soak Testing
  • Benchmark Testing
  • Scalability Testing
  • Contention Testing
  • Configuration Testing

You can leverage the services to monitor the performance based on diverse parameters (throughput, response time, Memory Usage, Disk I/O, and Network I/O etc.) and get accurate inputs for fine tuning the performance. The highly skilled & experienced performance test engineers will provide a detailed and performance cycle testing using the holistic and unique approach on all platforms covering different aspects. Performance testing services and solutions are realistic & powerful and cater to met various business requirements.

To Shop or Not To Shop

Macy’s, Neiman Marcus, Lowe’s, Target, Belk and Best Buy…do you know what they have in common? Yeah! They are the big sharks; the premier retailers with iconic brands that cater to their customers’ needs through outstanding stores, robust online sites and mobile apps. But, that’s not it…they are also the very dignified retailers who over years were victims to the Black Friday and Cyber Mondaycrash-downs. They have all had the retailers’ worst nightmare and responsible for the worst Thanksgiving experience to millions of customers waiting to have a pumped up shopping extravaganza.


 website crash happened in November 2017 which lead to a number of Twitterati complaining via tweets about their disappointment. “@Lowes My cart was full and now the website is down!” complained a Twitter user. The retailer responded: “We apologize our web site is down for maintenance. It will be available soon.” A few customers trying to shop on Lowe’s website read a message saying: “The site is currently offline and will be available within the next hour.” A similar disaster happened in the year 2015 on a Cyber Monday and as the stats suggested it was a record online traffic as experienced by Target Wide & Co. that brought an intense displeasure to the tastes of people expecting the perks of a relaxed online shopping experience. Shoppers eyeing for bargains on were greeted with an unexpected welcome message: “So sorry, but high traffic’s causing delays. If you wouldn’t mind holding, we’ll refresh automatically & get things going ASAP.”


“Come on @Target get it together. How am I supposed to order anything on Cyber Monday if you can’t keep your website running?” Nikki Ferrell tweeted.On Cyber Monday, a little more than 121 million shoppers planned to shop online; the numbers down slightly from the 126.9 million who planned to participate the year before that, according to the National Retail Federation.Target’s shares were down 1.1 percent at $72.59 in late morning trading that year. Another name that must be added to this list is that of Macy’s. In November 2017, when the credit card system struggled to process the transactions nationwide on the auspicious shopping day of Black Friday, it brought out a massive frenzy in customers.

“Sorry shoppers! is temporarily closed for scheduled site improvements as we work to bring you a better shopping experience,” read a screenshot that was posted by a Twitter user.

The list would be incomplete without the addition of the names like Neiman MarcusBest BuyWalmartBelk and Flipkart.

On a regular uneventful day, there is no such situation that would be questioning the performance of your website or your app. But on days by the likes of Black Fridays and Cyber Mondays, when there is an unexpected spike in traffic, not having the exact idea about the numbers which might be clicking away on their computers and mobile phones, filling their carts with their wish list, it leads to the websites behaving erratically and disastrous situations of an inevitable crash down.One could probably go on and on with the endless list of such examples, but the only agenda behind it is to point out the fact that even companies and organizations with advanced technology and robust architecture can crash under unexpected load on their websites. History suggests that e-retailers have had a constant struggle with determining the number of customers who might visit them in this big bargain hunting extravaganzas. This leads to the downtime in websites and disheartened customers leading to a spoiled brand image. We are all aware of the obvious scenario, nobody has the patience of a saint while purchasing a product. No matter how many successful deliveries you have made them in the past, the moment your website gets stuck it may take them less than a few seconds to abandon your site and go somewhere else to make the purchase.Even with elastic and abundant infrastructure today, why do they fail to handle the swamped up traffic? With highly distributed architecture of applications and components, not to mention latencies introduced by mobile networks, we now have multiple points of failures in the system that could crack under load as resource contention increases. It is this challenge of pin pointing performance bottlenecks with accuracy, that performance testing and monitoring will help resolve.Performance testing helps you understand the behavioral aspects of your application under high load conditions and in determining the speed at which it responds. It ensures that before the launch, the website or application is working flawlessly at increased loads by ensuring that there is no dis functioning in the system infrastructure of the app or in user interaction with the same. It provides an insight into how the app will react in unfavorable situations   of amplified load, slow server speed and any kind of network issues. The most important benefit being that the website/app can be confidently released with the confidence of a trouble free experience for both end user and the retailer.Application Performance Monitoring during testing as well as in production gives us meaningful insights to the resource contention and latencies across various components of a complex transaction. These insights to the customers’ digital experience can help us fine tune application performance, improve the user experience and ultimately drive business growth!

So, prepare your website for expected/unexpected traffic such that everybody can only be thankful to the Black Fridays and Cyber Mondays with a happy shopping cart and a happier checkout experience. ImpactQA has partnered with leading technology platforms like Loadrunner, Blazemeter and Dynatrace to deliver best in class performance testing and monitoring solutions. The solutions are based on understanding the user experience and providing end to end visibility to application performance and availability.