How to pivot a culture of quality assurance

Alex Thompson Digital Engineering December 1, 2021

According to Gartner, even a single disruption could decrease an organization’s quality culture by 9%. Over the last couple of years, organizations across all industries have had to go through multiple upheavals such as the pandemic, shutdowns, technological advancements, and business model reinvention. Understandably, the culture of quality assurance in software development has evolved from finding errors to much more than that.

Modern QA teams have to focus on creating customer value, surpassing users’ expectations, and staying ahead of the competition, in addition to identifying bugs. This indicates that QA engineers and testing must align with business objectives and the larger picture.

While technology plays a vital role in the entire quality ecosystem, implementing a culture of QA will positively impact your company’s quality assurance practice.

Here are some ways to pivot to a culture of quality assurance in your organization:

Analyze Failures & Gather Evidence

Fixing bugs is a great temporary solution, but only by improving the entire process will you get actual results in the long run. Fixing the process requires a clear vision of what will work. But to know what will work, you must first identify what doesn’t work.
If your quality practice has trouble delivering consistent quality and you end up with a lot of rework, you should investigate why this is happening. Perform root cause analysis on the issues and proactively modify your processes to prevent the issues.

Document your findings diligently, implement the new quality system on a small scale and record the improvements. This exercise will come in handy when trying to get buy-in from all the stakeholders.

Create Stakeholder Value Chain

Identify the stakeholders of your organization’s quality culture. While quality culture is about creating one unified quality control system for everyone involved, first understand that every individual’s perception of quality differs. Every person could have a different pain point due to problems with quality, and it is this pain point that you must address.

For instance, do you know if your development team members have enough time to write codes? Or are they working in a hurry, causing poor software quality?
Does your QA team face any hostility from other teams for adhering to strict standards? Does this animosity affect their work?

Does your support team feel overwhelmed due to the complaints from the customers? What kind of complaints do they face repeatedly? Can those issues be prevented early on?

Asking and getting the answers to such questions helps you identify what is essential for each person and implement a quality assurance culture that addresses everybody’s concerns.

Keep Your Eyes on the Prize

You’ve managed to create a product that goes beyond your internal software quality standards. Great! But the real question is, does it meet the brief, i.e., meet your customer and end users’ requirements? Remember that the customer’s requirements and the end user’s expectations might overlap but not necessarily be the same.

If your customer okays the application initially because it met their needs, but the end users reject it, the customer might still blame you for not creating an engaging UX or not factoring in the end-user experience while developing the app. Put your user first and keep asking yourself if every step in the user journey makes sense. Ensure that you perform extensive tests before any fix or upgrade goes live.

An excellent quality assurance team always ensures that its quality standards satisfy everyone, from their delivery head to the end-user.

Foster a feeling of shared commitment

Drive a culture where different teams interact freely with one another. Begin by removing the fear that they might be held liable for even a small issue. Encourage managers and team members to help one another and provide constructive criticism. Set an example by having the leadership advocate and follow the culture. Help your employees get comfortable and bold so that they willingly take ownership and provide feedback on fixing issues or improving customer experience. Move on from a culture of punishing mistakes to a culture of openly acknowledging one’s mistakes, reflecting on them, passing on the knowledge to others, and improving quality in the long run.

Never stop increasing quality competence

Employees who feel confident in their competency feel empowered to take more ownership and help the company produce innovative products that disrupt the market. When you create value for your employees, you increase the value of your product and indirectly increase your company’s value by earning satisfied customers.

Conclusion

We at TVS Next feel that, like software development, QA testing is a constantly changing field, with new advancements every day. The need for dedicated QA professionals is only growing as businesses recognize the need to produce enhanced software quality in a heavily competitive market. The success of an organization’s products and their businesses as a whole depends on quality assurance.

Establish strong pillars of quality assurance and be future-ready.

Revolutionizing Quality Assurance Through Continuous Testing

Alex Thompson Digital Engineering November 30, 2021

Building an application, testing it, fixing the issues, then putting it out in the market or delivering to the customer, getting paid, and walking away may have worked at the beginning of the digital era. But that is not the reality today.

Even if you build something outstanding today, somebody might and WILL do the same much better tomorrow. Modern users know what superior functionality and user experience are like, and they will not settle for anything lesser. The volatile nature of today’s market and increasing user expectations demand a constant reinvention of products and services quickly from every digital organization.

Perpetually building and rebuilding codes and gearing them up for quick releases have made QA an indispensable part of every development team and mandate a superior QA strategy.

What is Continuous Testing?

The new and superior QA strategy is known as Continuous Testing. Continuous testing involves testing, discovering, and fixing issues early in the development cycle to prevent risks and reduce deployment times.

Contrary to popular beliefs, being quality conscious from the beginning of the development does NOT reduce the workload and increases the scope of work for the quality assurance team. To keep up with the huge workload and ensure quality as an integral part of the development from day 1, QA engineers have started wearing multiple feathers in their caps as SDETs.

With almost all development teams being agile, QA teams use a mix of automation and manual testing in their Continuous Testing strategy to keep up testing speed with the development speed.

What does Continuous Testing do?

It does just what its name suggests. Whenever a set of code is built, automated tests are executed. If the test deems the code as good to go, it is then sent for more exhaustive testing to ensure performance and functionality. If the code fails the test, it gets rejected, and the developer who built it gets notified.

Sending the failed code back to the developer who wrote it removes the problem of tracking the defect. Instantly notifying the developer of the issue also causes it to be solved quickly and minimizes chances of the same issue occurring later on during development.

As meta as it may seem, a continuous testing framework also needs to be continuously upgraded, and new test cases need to be added, and obsolete tests that take up time and yield no value have to be removed.

In all, continuous testing decreases your time to market, reduces testing times from months to days or even hours, empowers development and testing teams to work in tandem, helps companies circumvent significant threats in the early stages of development, and reduces last-minute pressure on QA teams. (We can hear you cheer for the last one!)

Conclusion

“Quality is not an act. It is a habit” – Aristotle.

The only way to beat your competition is to keep surpassing your previous records and making your product/service better every day than it was on the day before. And that is why continuous testing with automation is an essential requirement for an effective SDLC and your entire organization’s success in the long run.

Start your journey towards building a habit for better quality today. Get in touch with us to audit your QA function and make your QA practice stand out among the others.

Want to read more about assurance? Download our whitepaper on Accelerated Assurance: Leveraging Automation to Guarantee Time, Quality and Cost.

Everything you need to know about QA and Agility / SDETs – The point where QA and Agile Meet

Alex Thompson Digital Engineering November 19, 2021

In a market where most software is constantly being improved and equipped with better features in every release, traditional testing certainly is a huge hindrance, and it is considered the #1 bottleneck in software development, according to a Gartner Report on QA. This is why a continuous approach to quality assurance, where quality is a part of the software development from the beginning, becomes crucial.

Software development in an agile method improves how testing is performed. The agile methodology includes quality assurance in every stage, and QA engineers perform continuous testing and provide rapid feedback throughout the development cycle.

Then we go one step further and look at mature agile teams. Multiple organizations with mature agile teams have at least one common factor: skilled software pros who multitask and keep upskilling themselves to adapt to the market demands, especially from a quality assurance point of view.

SDET or Software Development Engineer in Test is a role performed by a hybrid software developer involved in both development and testing, and sometimes more in the Software Development Life Cycle (SDLC).

Why SDET? / The need for SDET

An SDET oversees the entire SDLC and ensures that the project requirements are met. They can work as developers as well as testers and have the capability to think from both perspectives. Therefore, SDETs will be able to eliminate silos in traditional testing where development and testing do not work in tandem.

Besides identifying the root cause of issues, SDETs can also work on the code to fix the issues. The quick fix of issues facilitated by SDETs translates to faster release cycles without too much dependency on multiple team members. The need to develop and release high-quality software in a short period seals the deal and mandates the presence of an SDET in the team.

What does an SDET do? / Typical roles and responsibilities of an SDET

Although the responsibilities assigned to an SDET may vary depending on the individual’s skills and the organization/team structure, here’s a list of typical duties of an SDET.

Understand customer requirements
Create test cases
Perform testing
Create and maintain reports on development and testing
Perform debugging
Regularly communicate with all stakeholders
Analyze and identify technology gaps and recommend/design tools to improve the product.

Differences between testers and SDETs

A tester is not expected to have programming skills, but an SDET should test and code. Effectively, a tester points out the issues, but an SDET identifies and fixes the issue. Testers are involved only in the testing stage of the SDLC, whereas SDETs are engaged from the beginning of the development process. A tester’s work is independent, and all they have to do is to test once the development is complete.

Therefore, a tester does not have to communicate with other team members. On the other hand, the role of an SDET involves communicating with customers, end-users, team members, and the company management. A tester might perform manual testing or automation testing. An SDET develops the tools and test cases required for such testing and performs testing using their developed tool.

Skills required for SDET/How you can become an SDET

To become an SDET, you must develop the following skills:

Become a skilled developer in one or more programming languages
Understand intricate technical specifications down to the last detail
Possess knowledge of different test methodologies
Be able to design test cases
Understand and perform project management
Build test automation
Work within Agile method of development
Understand business requirements
Ability to communicate effectively with the team as well as the client
Continuously upskill and keep up with the trends of the market

Other Career Options as an SDET

A quality assurance engineer does not necessarily have to be a developer to become an SDET. Listed below are some areas a QA can learn and the kind of teams they can fit into:

Expertise in cloud platforms and services like AWS or Azure – The Cloud deployment team
DevOps knowledge – The DevOps team
Product management and ownership – The product team
Design Skills – The design team
Automation expertise – The Java / Angular development team
Business operations knowledge – The Acceptance / Operations team

If you’re a quality assurance engineer, choose a field that interests you in addition to quality assurance, specialize in your preferred area, and transform yourself into an indispensable resource for your organization as an SDET.

Give a list of different fields SDETs can get into, and they can choose whichever area they have exposure/interest/skills in and specialize in that and become an SDET, who will be an indispensable resource for any company.

Manual testing may be a thing of the past, but Quality assurance as a practice will live on forever. People who have multiple skill sets and keep learning and updating themselves will always find a lucrative career in quality assurance.

QAOps – Is This a New Trend?

Alex Thompson Digital Engineering October 6, 2021

What is QAOps and what is the buzz about it?

Rapid changes and new trends are emerging in this era of software testing and development, where technology advances at lightning speed & every organization wants the best product in the market. To take the lead, an organization must adopt the latest trends in software testing to offer the best software products in the market.

There’s a new trend emerging in software development and testing, and its name is QAOps. A method of testing that assures both speed and quality.

QAOps is a new-age testing practice that is changing the way quality assurance works. With the emergence of big data, cloud and AI, a new testing method that works with complex technologies emerged

Being a new-age practice, it helps to integrate quality assurance into the software delivery pipeline; in other words – QAOps combines Quality Assurance (QA) and software operations (Ops). QAOps, also known as DevTestOps can be defined in terms of two key principles:

Quality Assurance operations integrate into the CI/CD pipeline.
QA engineers work closely with developers, IT Ops engineers, and anyone involved in the CI/CD pipeline

QAOps Framework & why does it matter?

Any good business should know how & when to use a QA framework along with the pros and cons. QA framework can be applied at any stage – design, development, production, post-go-live, etc.

QAOps is the process of setting up the testing platform, which involves three major steps Trigger, Execute, and Report.

Achieving QAOps in Testing Process – Basic Practices:

QAOps framework is in the below high-level areas:

Automated Testing – Test automation maximizes efficiency, speed, and application quality.
Regression Testing – It reduces the effort when updating and re-releasing a product.
Parallel Testing – Running multiple tests at once.
Exploratory Testing – This focuses on discovery and depends on feedback from the individual tester to uncover defects.
Test scalability – This is non-functional and helps measure an application’s performance or behavior of a system based on the number of users, i.e. how the product behaves under different request loads.
Integrate Dev and Ops with QA – This involves integrating the QA process in the CI/CD pipeline.

Components Covered

The four core components covered in QAOps are Planning, control, management and insights.

When all these four components are used at the correct time and place, QAOps can drastically decrease the amount of QA time needed.

Clarity between testers and developers is important. Setting up a continuous & integrated framework that focuses on continuous builds, continuous validation, and continuous delivery improves productivity. When this framework integrates with DevOps, we can achieve the transparency of the workflow and product release.

Testing Types

A good product for any organization supports multiple platforms, which is the need of the hour. Most of the customers have numerous clients that work on – Mobile/Web or API.

Best Practices to be followed

Tool Integrations with CI
Automation expertise
Approaches & practices to improve the test case quality.

The Benefits

Quality – Though QAOps is new, it is gradually gaining popularity as DevOps is becoming more used among businesses. Since the main focus of QAOps is quality, this is one of the most important reasons why organizations should start adopting it. Compared to the old traditional methodology, with QAOps, the developed products are more likely to be of high quality, which is one of the key elements & a plus point.

Great teamwork & collaboration among Teams – It boosts teamwork and productivity. Since the teams are fully involved in the process and the delivery pipeline, it results in good co-operation and a better understanding of the requirements.

How to Evolve with QAOps

The organizations need to understand and realize what it offers at large and educate & evolve the testers with the QAOps use tools, use cases to work on, techniques to follow, collaborations, and discipline associated with the application life cycle.

Conclusion

QAOps ensures:

Quality is not neglected in the SDLC even after being a new trend. In just no time, it allows the automation of processes between software development, IT, and QA to deliver software faster coupled with better quality.
Implementing QAOps any day gives any organization an upper hand over the competitors in the software development industry since it works on enhancing the process with quality with speed.
Speed of delivery doesn’t negatively impact the quality of software. Here is where QAOps comes into use.
Not even a doubt, QAOps is one of the fast-paced rising techniques for testers and a revolution in testing continuously by covering all end-points of Continuous Integration & development.
Testers work on enhancing their skill level for the testing concepts and the Integration and deployment of continuous builds.
“Investment in quality early on is an example of the right efforts put at the right time”

Empowering Quality Assurance With Artificial Intelligence

Alex Thompson Digital Engineering September 3, 2021

Artificial Intelligence has crossed its nascent stage and is gaining rapid momentum. Organizations are looking into investing in AI for immediate intelligent insights that will result in long-term cost savings. Gartner predicts that augmenting artificial intelligence will create $2.9 trillion of business value in 2021 alone.

There has never been a better need for Quality Assurance than now. All kinds of applications are constantly being released and are continuously updated to provide more functionalities and better experiences to the end user. QA teams are expected to be agile, multi-skilled, be involved from the beginning of the development, and deliver high quality.

Leveraging artificial intelligence in quality assurance is a new wave to help QA engagements become predictive and analytics-based.

When it comes to combining quality assurance with artificial intelligence, it can be done in two ways: using QA while building AI & using AI to build QA.

Using Quality Assurance while building Artificial Intelligence

84% of CEOs think that AI-based decisions can be trusted only if they are explainable. More often than not, AI systems are not trusted easily.

For an artificial intelligence system to be deployed, it has to be proven accurate, secure and reliable. Building such an AI model is no easy task. It involves lots of data training, and rigorous testing and tuning. This process requires highly skilled domain-aligned QA to make the training success.

Using AI-empowered Quality Systems

Quality assurance automation has already been a key tool for many software building enterprises. QA automation software is used to make the product market ready at lesser costs in shorter intervals.

Bringing an AI-empowered quality system with superior predictive capabilities into the automated testing arena elevates the testing approaches and takes quality assurance to the next level.

Some QA use cases where AI can empower QA teams

High accuracy

Even the best QA teams could possibly overlook some defects during the most proactive quality control processes. This issue can be resolved when using artificial intelligence in inspection to help the QA teams. QA teams can leverage the test cases generated by AI based on pre-conditions and past coverage and reduce software bugs.

Predictive Analytics Based on Pattern Recognition

Rather than testing after the code has been written, artificial intelligence can predict potential defects that could occur in a particular module. Based on previous defect history, it can predict which team or person is likely to produce more bugs in the code. Thus, making a huge impact on achieving proactive quality.

Root Cause Analysis

When large or multiple teams are involved in building a software, although ownership may be assigned to each team/individual, it is difficult to point to the origin point of a defect. AI can be used in this case for software quality assurance to find the root cause of the issue, and point to the team or member who can fix the issue, thereby saving time for everyone involved.

Faster Release Cycles

Artificial intelligence testing can generate results very quickly, even for large codebases, thereby reducing the product release times. The bot can run unsupervised during nights, and developers can begin work the next day based on the results of the AI testing.

Test Data Generation

Test data generation takes up a lot of time during software development cycles. This test data is used to test the software and ensure that all the components are working as expected. AI can be used to generate test data that is very close to actual production data that will be fed when the software goes live.

Conclusion

In a highly competitive digital landscape, it’s important to stay relevant and deliver unmatched user experiences, regardless of whether you’re a B2C or a B2B business. Augmenting quality management through AI-driven Quality assurance is an integral part of running businesses of the future that can help mature your QA teams from being a reactive QA organization to a proactive & cognitive QA organization.

With TVS Next as your AI-based QA partner, you can deliver products and services that stand out among the rest and with business clarity through scalable quality management systems. To know more:

Can a Monolithic team handle Microservices?

Alex Thompson Digital Engineering August 14, 2021

As monolithic structures become too big to manage, many companies are drawn to migrate to microservices. It’s a worthwhile trip, but it’s not simple. To do this well, we need to start out with a simple service and then build services based on vertical capabilities that are essential for the company and are subject to frequent changes. Such services should at first be broad and ideally not depend on the remaining monolith. We should ensure that every migration step represents an improvement on the architecture as a whole.

Migrating from a monolithic architecture to microservices is an epic journey. Those who embark on this journey have aspirations such as increasing the scale of operation, accelerating change pace and escaping the high cost of change. They want to increase their number of teams, allowing them to deliver value in parallel and independently of each other. Companies want to experiment with their core capabilities rapidly and deliver value faster. They also want to escape the high costs of changing their existing monolithic systems.

Which capacity to decouple, when and how to migrate incrementally – are some of the architectural challenges of decomposing monolith structures to microservice ecosystems. In this write-up, we discuss how a monolithic team can handle microservice applications.

Tools are Only Enablers

Teams stepping onto the right path still need to master using DevOps and CI/CD pipeline to democratize their development. Microservices enable scaling for DevOps team. DevOps enables development and deployment of Microservices application without any interference. It eliminates bottlenecks that were prevalent with the traditional approach.

Knowing how to use a tool is only a journey begun. It brings up the issue of managing the compartmentalization. Tools are enablers for its users, and they need to be put into use with right intent and purpose so that it gets to the destination faster. Developers and architects need to be experts while designing and developing the system, moreover, be capable of coordinating across multiple teams and services. Each compartment should be able to run independently and, at the same time, be prepared to shut off when running into issues with a higher level of fault tolerance in the system.

Automating continuous delivery and testing pipeline requires the right know-how to foresee challenges. Scripting your infrastructure and testing to be run on automated requests makes it easier to manage the system-level changes and better handle issues.

Cloud-Native Development

While deploying applications on cloud is more of a norm these days, so is cloud-native development, which allows to take advantage of the cloud computing model. This makes containerization & orchestration more manageable while helping detecting errors before releases. While most teams already know how to manage cloud applications, cloud-native development still needs upskilling.

Model Microservices Team

Just by changing the way of writing a mammoth-sized application into smaller manageable chunks, it doesn’t fix the issue of writing incorrect code or having poorly tested applications. Previously, where you couldn’t bring in an expert team to handle the non-core part of your application, now it can be readily developed with the use of external teams.

This also enables an accelerated approach to shift the mindset with model teams. While we expect Microservices to allow the development of various services simultaneously, we can’t have teams incrementally upskilling to handle Microservices and DevOps. Outsourcing plays an active role in maintaining your development’s velocity and momentum while raising the benchmark for your existing team. This combined approach has helped many customers see value early in their lifecycle and become flexible in handling changing circumstances.

Structuring the A-Team

A large portion of this transition to Microservices and DevOps still banks on the organization changing its way of collaborating and developing applications. New age product companies that started with Microservices ecosystem in their culture still run into problems because of this fundamental shift lacking. Most companies end up creating horizontal teams to handle services. Why? Because that’s easy to put on to the Project Management tool and look at productivity charts.

Now that we have established teams as the enablers of change, it is necessary for some reshuffling in the thought process and thus the way teams are structured:

Accountability: Having compartmentalized services also means having compartmentalized responsibility. Accountability starts with detailed specs being written and communicated to all parties involved. This makes outsourcing chunks of work to external teams easier and efficient.

Vertical Teams: Giving up the traditional horizontal team structure for APIs, Data, Front-end, and Back-end services, instead of adopting siloed and independently-run teams that take ownership of each of the services, becomes the apt practice. This leads to the rise of full-stack developers being able to manage different aspects of the services. Each service team will thus have its API members, developers, data engineers, and testers.

Communication via API: Think of running the services as a mini software and communicating with other services using APIs. Communication between services becomes crucial for compartmentalization and the only way to measure the overall application’s performance.

Rise of Integration Testing: It’s time to give some rest to the old methods of testing while giving the mantle to integration testing. As system failure gets compartmentalized, the points of failure are detected at the integration points for your team to identify issues. This also gives the commandment that each service should be written keeping in mind that the service in its entirety can be rewritten or fixed within a day.

Diversity in Technology: Due to the modular nature of Microservices, it becomes easy and obvious to choose the right technology or framework for the service instead of relying on a single technology for the development of an entire application. The technology preference of your team takes huge precedence in the selection. CTOs are often asked to choose a technology based on the team’s preference, while in a parallel world, there are those CTOs who restrict the technology giving stability an important consideration over team’s preference. This goes to say that CTOs have a huge role in foreseeing challenges even before they occur.

Distributed Governance: Similar to how testing is simplified at the service level and priority is given to integration points, governance can also be managed at the aspects of communication between services. This can be handled with well thought out planning and an effective method to handle changes. When you distribute or decentralize governance, don’t forget to impart the importance of responsibility from each team member.

Conclusion

Microservices are far-reaching, but should not be taken lightly because the greater the reward, the higher the risk. New Age Product companies made incredible strides in embracing the microservices ecosystem and Digital Enterprises chartered their 2-year roadmap to revolutionize the strategy to software development. There is still a lack of adequate talent to scale Microservices to its true potential, however. Upskilling and outsourcing should be seen as parallel courses of action instead of alternatives for an effective change in strategy.

This is how TVS Next helped a client implement microservices to drive innovation

Our client, a leading player in the education space, had a monolithic structure and was facing issues restricting the team from innovating. Scalability, inability to incorporate new business requirements swiftly and many other problems in the deployment infrastructure had to be overcome, rapidly.

After a comprehensive assessment and due diligence that encompassed all aspects of their business and technology landscape, TVS Next helped them migrate to Microservices application.

The processes of development, testing, deployment, troubleshooting, upgrading, and maintenance became more streamlined and efficient.

Robust processes governed the execution & governance structure with constant stakeholder reviews, and the transformation from legacy monolith to robust Microservices was established in 8 months.

Scale yourself: Use Agile

Alex Thompson Digital Engineering March 19, 2021

What is Agile & why is it Important?

This way of working has become the most talked about topic in the past few years and yet unknown to many! One would be living in a stone age of Technology if this term is still unheard. Agile is everywhere: You name it and there you have it.

Since Agile is not a methodology but a mindset, there is still room for it to grow not only in the software development spectrum but across other businesses as well such as manufacturing, food & beverages, automobile industry and more. Agile mindset is a great asset to help businesses grow and come up with new products & services. Although Agile does not fall under the traditional business management techniques which are generally taught in top-notch business schools around the world, the good part is that the Agile mindset will not only survive in the coming years, but it will also show us the way to develop our mindset in business.

It`s not a surprise to hear why the new age organizations are trying hard to implement this. So, it’s important to understand what Agile means and why it is important.

Agile History: From where it all started

Going back to the history, the term Agile is derived from the Latin term “agilis” which means “nimble or quick,” and from the term “agree” which means “to set or keep in movement”.

Why is it becoming popular?

Agile has completely restructured the way the software industry works. This way of working has definitely boosted the success rate of projects by creating a great and new age work culture. With respect to the other ways of working, Agile process is quick enough to adjust to changes requested by the clients throughout the development lifecycle.

What is Agile Project Management?

– As per the Agile Manifesto (2001) approach, Agile project management is an iterative approach to product delivery & it incrementally starts from the very start of the project instead of trying to deliver the entire product at once near the end.
– Agile works by breaking projects down into little bits of user functionality, prioritizing them, and then continuously delivering them in 2-4-week cycles called iterations or sprints. The customer’s priorities are well analyzed, prioritized and the team estimates how much time work will take in an iteration, as well as how to do the work.
– Performance is measured by customers at the end of the iteration. The lessons learned in each iteration are captured in retrospectives and used in future iterations. In this way, the products are constantly improved and the process for developing them also improved.

Need for Agile Principles and Agile Methodology

Do we know why some organizations are tending toward Agile Project Management?

Agile Project Management helps:

– To create a High-Quality product
– In providing Higher Customer Satisfaction
– Faster ROI
– To increase Product Control
– To help increase team performance, improve customer satisfaction and increase project versatility
– To be able to respond to market dynamics well

– Companies to embrace the idea of delivering business value early in the process making it easier to lower risks associated with development.
– During the project, end-user involvement is encouraged, providing visibility and transparency. There is continuous planning and feedback throughout the process, delivering value to the business from the beginning of the project.

Need for Agile Trainings:

– Agile trainings can clear up many misconceptions / misunderstandings about the operations of Agile.
– It can also help expose the underlying Agile concepts and clarify the differences between the various implementation method.
– Having all project team members (both technical and business) attend common training, ideally in the same class, can eliminate some of these problems. The shared understanding among the team members strongly increases the probability of the team inspecting and adapting together using a common language and practices, thus reducing conflicts in the future.

Conclusion: “Future in the Market”

Agile ways of working have become mainstream today and most of the organizations which leverage Agile ways of working and the culture of Agility are going to dominate their industries in coming future. Those organizations that do not take advantage of Agile are going to struggle to retain both customers and talented employees. At some point, their lack of business agility is going to threaten their very survival. Think about it, scale yourself because it’s now or never!

And it’s rightly said:

“Agility is principally about mindset, not practices” – Jim Highsmith

Future of Virtual Assistants: Is it the rise of machines already?

Alex Thompson Digital Engineering October 21, 2020

The term Rise of Machines should bring you memories of the movie Terminator series and Skynet.

Virtual digital assistants (VDAs) are rapidly gaining traction in both consumer and enterprise markets. So, what are these VDAs? Virtual digital assistants are nothing but automated software programs or platforms that help the user through understanding natural language in written or spoken form. Going by the virtual assistant demand, the device is poised to digitally transform the user experience.

Apart from smartphone-based virtual digital assistants, which are widely popular, VDAs are also beginning to enter the ecosystem of smart home assistants and other device types like fitness trackers, PCs, and automobiles. This rapid proliferation of virtual digital assistants is due to the accelerated innovation and scalability of associated technologies like AI and NLP (natural language processing).

In the future, you will be able to chat with your car about the best locations to visit. Your car will display the best possible route after analyzing driving time and getting your preferences conversationally. All these advancements will be due to the tremendous power and rise of digital assistants.

From the consumer-oriented virtual assistants like Siri, Amazon Echo, etc., to dedicated software for business use cases, future virtual personal assistants are going to digitally transform the customer experience. Thus, an enterprise must build a VDA to stand out from the crowd. Here are some of the steps to build an effective virtual assistant.

Step 1: Build a flawless speech-recognition system. This process requires acoustic modeling, voice modeling, and a speech recognition engine

Step 2: Enable Natural Language Processing (NLP) which is the basic intelligence required to process semantics of a user’s speech input.

Step 3: Integrate machine learning or AI to improve the intelligence of the virtual digital assistant. This allows VDAs to learn, understand, and adapt based on the information available.

Step 4: Since responses should be instantaneous, VDAs need large scale systems that provide the power required for processing large amounts of data.

Step 5: Finally, all these modules should be secured using an API gateway to interface with several other systems. It is worth mentioning that, VDAs should be designed for a mobile-first and cloud-based environment.

HOW WILL THE FUTURE OF VIRTUAL ASSISTANTS IMPACT CUSTOMERS AND BUSINESSES?

VDAs would soon lead to the era of high customer satisfaction. With VDAs, there is tremendous opportunity to better engage customers and employees alike.

The consumer side of virtual assistants will become more proactive. Virtual assistants will learn more about you from your texts, searches, emails and it will start suggesting or predicting what you need, even before you ask.

Will Automation Eliminate Manual Testing?

Alex Thompson Digital Engineering October 21, 2020

We live in an era where software development has been revolutionized by AI (Artificial Intelligence) & ML (Machine Learning). It is expected that manual testing will be taken over by automation with its new developments and advancements, but that is not the case. Software manual testing has been around for many decades since initial software development, and the industry has taken multiple shifts. However, its scope remains the same. In this article, let us explore the impact automation testing has on manual software testing.

Why is manual testing still relevant?

New Projects: Projects in pilot phases that begin as a concept and take shape during early sprints require manual testing. Using automation testing during the initial phase of software development would be expensive as it undergoes continuous changes. But, leveraging direct human involvement in testing through manual testing would be cost-efficient and easy to accommodate changes.

End 2 End Testing: Automated testing can be used to test single systems or integration levels in detail. Whereas End 2 End testing involves multiple systems and requires manual testing. Automation testing that runs an End 2 End test scenario has many challenges, especially systems that have different tech stacks. Design changes involving systems in End 2 End testing impacts maintenance cost.

Maintenance Cost: For small projects or components, automated testing costs are higher than manual testing. Performing quick manual testing would suffice for smaller projects/ components that undergo frequent changes rather than updating test scripts after rerunning those tests manually.

UX Testing: Maintenance costs are proportional to UX changes. With each UI/UX change, test cases break and raise a false fail. When changes are encountered in a script, there is rework / maintenance to achieve the test pass. This impacts the next UI changes again. So, for an application with frequent UI/UX changes, automation testing is costlier than manual software testing.

Visual Testing:

While there are few automation tools available in the market, AI & ML are incorporated with visual testing to achieve 100% test resulst. But the number of hours required to train AI to understand minute changes in UI would be expensive than performing manual tests. Sometimes, human eyes can find a little misaligned text box, which could be challenging for an automation tool. Such automation tools with AI & ML are expensive compared to the advantages of manual testing.

User Acceptance Testing: There is no way usability testing could be automated. Beta users/client teams must experience the end product by simulating user experience using manual testing.

How automation testing can be leveraged?

Let us discuss the areas where automation has to be implemented to support manual testing benefits.

Regression: When a part of the product is regression and the product or UI changes, tests have to be automated using open source software. Using automation testing can therefore save manual testing time.

Integration Testing: API level automation can be quickly created like manual testing. Manual software testing tools like Postman enables us to create tests that can be automated using the runner feature. When manual testing is performed, requests are stored as a collection. This stored collection can be run any time as a test suite to rerun the test scenarios.

Smoke Test on CI/CD: Automating test scripts for smaller projects are expensive. However, using smoke test scenario would reduce the cost. Smoke tests undergo changes to get added to CI/CD pipeline for project code deployment capturing blocker/showstopper issues during code deploy to QA/Stg environment, before the code is released to production.

Conclusion:

Manual and automation testing complement each other. Manual software testing services are as important as automated testing, and there can be no project that is purely manual. There will always be an area where automation can be leveraged with open source tools that are no-cost and low maintenance. No project can completely use automation testing as client expectation keeps changing; manual testing is the way to handle frequent changes and ad-hoc testing requests. It is up to the project management to decide how and where automated and manual testing have to be implemented to provide a customer satisfied product delivery.

Can you be Agile without Continuous Delivery

Alex Thompson Digital Engineering October 21, 2020

Can-you-have-Agile-without-Continuous-Delivery

Challenges During Agile Transition

Organizations performing an agile transition are often unhappy with the results. Usually, they follow scrum structure and build cross-functional teams with all the skills required.

Agile coaches and scrum masters explain the three foundations of scrum — transparency, inspection, and adaptation. They also help us understand the different scrum activities such as sprint, daily scrum, sprint planning, sprint analysis, and sprint retrospective.

Teams are mentored on the value of quality improvement and they are demonstrated that every scrum procedure is an opportunity to inspect and adapt.

Despite these efforts, the business value delivery seems to take far longer than expected and enterprises are not reaping the agile transformation rewards or promises.

Software Development Evolution

A usefully simplified description of the advances in software development are listed below:

Waterfall claims that a team would only start getting the software ready for releases after all the release functionalities (i.e., ‘full feature’) are created.
Agile insists that the team will be ready to release its software throughout development. Most types of agile assume that this will happen regularly.
Continuous delivery requires the team to keep the software always ready to be released during development. It is not ‘traditional’ agile as it does not require waiting and making a special effort to build a releasing framework.

Agile Software Development

Agile software development is not a methodology in the strict sense of the term. It is more of a culture or an approach where you recognize the needs of the situation and adapt to it accordingly.

This technology requires adaptive planning and evolutionary development in addition to early delivery. Hence, there is a need for continuous improvement as it encourages a flexible response to the changes in the surroundings.

Applications of Agile: Simple Examples

Agile software development has a variety of applications in diverse fields. You can sense the difference in the technologies involved in activities we do almost every day. Take the internet or mobile banking, for instance. Transferring funds from one account to another is a regular activity for any person or business. You need security layers to be in place to ensure the safety of your funds.

Now, these security layers need constant updates so that hackers are not able to crack the code. Hence, based on feedback received from industry experts and consumers, the mobile banking app developers keep updating their systems. Therefore, you find something new every fifteen days or so. In the early days, there were only passwords as a layer of security. Now you have additional layers like grid combinations, 2-way authentication measures like OTP and so on. The process of improvisation is continuous.

This is agile software for you. They cannot wait until something drastic happens. The process of delivery has to be continuous. Agile software specializes in identifying threats or problems before they materialize. Thus, it is ready with a solution beforehand. However, having a solution alone is not enough. The critical aspect is the delivery and utility of the solution. Thus, one can say that agile software is of no use unless there is continuous delivery.

Hence, you can see that continuous improvement is always necessary for every industry.

Continuous Delivery — A Subset of Agile

The very definition of agile software development says that it is a group of software development procedures that are based on iterative and incremental development. There is a continuous evolvement that requires collaboration among various factors. Therefore, agile software cannot work without continuous delivery. There has to be a constant and continuous change in the circumstances.

You can see the application of agile software in a project management process. Breaking down a large project into smaller doable actions is the best way to approach any project. In this way, you will always be ready to change your plan of action should anything go wrong somewhere in between. Web designing is also an excellent example of the application of agile. You keep on improvising the design to suit customer preferences. You gauge these preferences by interacting with the customers at frequent intervals. Thus, you can see that agile is all about flexibility and adaptability.

Conclusion

This brings us back to the question ‘Can you have agile without continuous delivery”? You can see that it is just not possible to do so. The principal characteristic of agile is adaptability. Now, adaptability means continuous change concerning the situation. When the situation demands a particular solution, you need to adapt. This is what makes agile an exciting piece of software development process.