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The world of IT is evolving every day, and it is essential to learn about the latest industry trends and be relevant in your workplace. I am here to share my experience and learnings around RPA, Test Automation, UX, and DevOps that I have gained in the last two decades by working in both the product development and the IT services world!


An estimated 85 percent of the world's enterprise data is stored in an unstructured format, which is out of the reach of traditional automation, BI, and Analytics solutions. Slater Victoroff, CTO of Indico Data, shares his views on how data analytics, advanced artificial intelligence, and machine learning can analyze and process unstructured data. Slater also touches upon how insights and process automation capabilities can be used to accelerate business transformation initiatives.

Listen to the latest version of the podcast Automation Hangout to learn more:

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Updated: May 1

Artificial intelligence has impacted our daily lives and has moved from research to the mainstream in recent years. In this article, we explore how artificial intelligence can solve some of the challenges in software testing.

A combination of advanced technologies like advanced machine learning, natural language processing, and predictive analytics have impacted the software development cycle and helped engineers build applications better and faster. As a result, AI can improve decision making, improve the consumer experience by improving the overall quality of application, improve productivity, and help reduce overheads. The first question that might come into the mind of testers when it comes to AI is, "Is AI going to replace humans? ". The simple answer is "No," and the answer would remain the same for another decade. The currently available use cases around AI and testing only augment engineers with intelligence rather than replacing them.

You would have thought about why developers are not doing enough testing on their code at least once during your testing career. The primary reason is the lack of time to design tests. Writing a single unit test case takes somewhere between eight to twelve minutes. To get decent test coverage, a developer may need to write hundreds or thousands of test cases. As you currently work in agile sprints, three to four weeks in duration, developers do not get enough time to complete their coding. This results in primarily shifting the responsibility of finding defects to the test engineers within the team.

AI-based products like DiffBlue can analyze the project code and dependencies to build a map of methods and classes. After this, the unit test case is created for each method inside the application code. Then, you basically perform a test run to check the quality of these tests. Finally, a finalized set of test cases is created based on the test run results. This helps primarily in improving the overall coverage of unit testing. Still, you're only investing a minimum of time to simultaneously design these tests. This is an excellent example of how AI can improve productivity around test design. It also helps you improve the overall quality of applications because you're actually finding defects using white box testing techniques. This also allows you to reduce your overall cost of quality.

One of the critical opportunities for testers is to improve the pace at which feedback can be provided to the development team, especially around the quality of a build for testing. So what about a scenario where we can actually give the developer feedback on an application that has been sent for your testing in around 60 minutes? Currently, this is possible using autonomous bots like Certifaya, which can test mobile applications or multiple real devices and provide insights on functional and non-functional behaviors. The bots internally use AI technologies to crawl through the apps to identify workflows and validate the functionalities within each screen. And these tests are not created upfront and are actually built on the fly. The only input that the tester would have to provide is credentials like username or password.

And in addition to all these capabilities, the bot also gives you a detailed amount of information in the form of application screenshots and videos based on each of the testing sessions. And the reports prepared include information about critical issues such as crashes, memory leaks, high battery usage, and other scenarios. Many product companies are investing in building capabilities around autonomous bots. We expect to see more of these capabilities coming into action in the next couple of years.

How often do you review the production ticket that your application support teams are handling, or do you actually look at what your end customers are talking about your product on social media feeds like Twitter or Facebook? When this question is posted to testers, the standard answer is a big No 99% of the time. We tend to forget about the applications sent to production after the warranty support phases are over. But there are several use cases where AI can be applied, like analyzing production feedback and tickets to improve the overall quality of the application. Testing professionals can use the inputs to revamp the test strategy that one would have created for your application or product. For example, there is a lot of improvement that we can drive around defect analysis by using classification algorithms that would actually have the capability to classify defects based on the different functions of your applications. Or you can actually use algorithms to identify the best developer or support engineer who should be actively working on an issue that has been reported in production.

You can also go one step further to figure out the phase at which the defect was introduced into the product or carry out a high-level root cause analysis of an issue in production. Similarly, classification techniques and algorithms can also break down the end-user feedback based on the various application functionalities. For example, customer feedback can be captured from social media feeds like Facebook or Twitter. And if you have a mobile app, you can also look at the App Store as an excellent source for capturing your customer feedback. And the other technique that you can use to analyze customer feedback is to run customer sentiment analysis algorithms to figure out the happiness level of your customers.

But continuous monitoring of your customer feedback and tickets is an excellent technique that you can use to identify symptoms. Moreover, they can be extended to prevent such issues from becoming more significant later.

Have you ever wondered why you are executing thousands of tests to validate a small change? This is because we are not accurately identifying the impact of a code change that the development team was actually making. In addition, with the increase in DevOps adoption, one can expect more than a dozen build to come in each of the sprints you would be working on. So what happens is that you execute all your test cases on every build. As a result, you're wasting a lot of your effort in conducting tests. Therefore, one can think about the alternate approach to taking a risk-based testing approach.


Running all tests may not yield any defects, and you end up leaking defects to production if you decide to go with a risk-based testing strategy. But products like Sealights use AI and predictive analytics to scan through the application code to understand the impact of changes and then recommend tests that you should execute. Sealights can continuously map billions of correlations between tests and methods using artificial intelligence algorithms. The test can be a unit, integration, API, or regression and manual or automated. As a result, you get a wide range of recommendations that would even consist of suggestions to create new tests.

The platform can also understand and recommend the dependent kind of test you should be running. It also can identify the test that needs to be done to test the impact that the development team has actually created. The overall benefit here is to cut down on the number of tests you're running, which also helps you cut down your overall cycle time and cost. At the same time, one thing that we should not forget here is you're not actually compromising on quality. You're doing testing in a very scientific way by leveraging the capabilities of both AI as well as Analytics.

A lot is happening around the AI space, and it is essential to monitor the trends. We can expect several innovative platforms and solutions in the coming days that will use the capabilities of AI to improve the efficiency of software testing.

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Updated: May 1

The tech world is currently going through a phase of the revolution. From upgrading the legacy operations to transforming the way we interact with the technology, the change has been extremely rapid. However, the growing number of devices and dependency on the IT infrastructure have fostered the need for security. And achieving such goals need developers and programmers to make the best use of DevSecOps methodologies.

More importantly, meeting the goals surrounding DevSecOps requires centralization of the IT workflows while utilizing the best of DevOps practices. Also, when leveraged in a precise manner, it could help you attain all the flexibility and speed goals while overcoming any challenges related to redundancy and time.

Nevertheless, working on an idea that needs the adoption of change can be challenging, especially when you aim to foster a practice like DevSecOps to its extreme potential. And for this reason, there are so many business organizations that are struggling to align with DevSecOps culture.

Besides, there has been a huge community of non-IT people that are not aware of DevSecOps practices, the infrastructure requirements, and feedback capabilities. Even there are so many surveys that have shown the staff lacked any information related to systems causing discord between development teams, operation departments, and security experts.

All in all, it is vital that business agencies, right from the IT staff to their executives should understand the need for security to bridge the gap between Development, Security, and Operations. Before we jump to any best practices and benefits surrounding DevSecOps, let us quickly explore the four most important DevSecOps strategies that help adopt and sustain the DevSecOps culture. Let's begin.

Strategies To Sustain A True DevSecOps Culture

Cross-Team Collaborations

Running a DevSecOps culture into the workflow needs extensive focus on cross-team collaborations. More importantly, it is vital that collaboration should never be mistaken for communication as it is more a two-way process where all the technical and non-technical stakeholders prepare on the technology requirements.

In other words, fostering cross-team collaborations into DevSecOps needs efforts that do not bring non-technical stakeholders to the end of the development process. Rather it must be a collaborative approach that should involve the non-technical people at the very beginning of the process to share their insights and understanding on both development and security. This would not only aid in creating products with better quality but will help yield the functionality requirements that can upgrade the product goals for sustainability.

Open Work Environments

When we say open work environment, it is all about keeping teams in sync with the information. This has nothing to do with any actions that can lead to compromises, rather it is more about having a clear context for workgroups, grouped decisions, honest feedback, and delivering the right information at the right time. On top of that, creating an open work environment needs to give more visibility to programming and development teams with feedback. Besides, it needs you to have all the end-users and stakeholders involved in the development process, incorporating input, feedback, and active tracking of actions.

Upskilling Opportunities

The process of transitioning to DevSecOps is overwhelming and nothing that happens in the blink of an eye. It needs extensive upskilling efforts to help development teams with the best practices that can leverage security into the existing DevOps scenario. However, it is equally necessary that the entire process should be designed to adapt different learning styles while focusing on anything that helps the team get agile with both decisions and development. Such an approach towards upskilling and retraining could help yield teams that can master the functionality goals related to the software.

Responsiveness & Reliability

When we talk about DevSecOps, it is all about creating solutions that are repeatable and could be leveraged to automate tasks. Moreover, such an approach could help yield a save on time and resources streamlining resources and improving the workflows. Besides, a responsive approach could help establish practices that could help with version control, allowing easier self-documentation, improved audits, and better security.

DevSecOps Best Practices

Even if you are informed of all the strategies that could help you implement DevSecOps into the workflow, the inability to adopt the best practices can lead to loss of direction and failed initiatives. Here we have a quick list of best practices that could work for you on your way to digital transformations through DevSecOps.

Secure Coding

The concept of security coding is developing software that can resist any kind of vulnerabilities and threats. Otherwise, defining a code that does not involve secure coding practices could lead to security risks such as the breaching of confidential data. Therefore, it is necessary that all the teams working on the programming part could handle security goals even if it needs you to spend a little extra on cost and time as the end results would bring you secure, clean, and authentic code.

Bringing Automation Into The Picture

Automation is a vital part of DevOps' future and, therefore, for DevSecOps. The growing need for security within the fast-paced CI/CD environment needs every organization, irrespective of their size, to push their developers towards automation. The approach would not only aid in pushing code but will improve the way resources are consumed.

Besides, automation into the DevSecOps process could aid the security testing process eliminating any mistakes with the manual process. However, the only thing that might impact the results is the selection of the test tools that can automate and run tests continuously.

Incorporating Shift-Left Approach

The shift-left approach needs testers and developers to progress in a different direction when it comes to security. The shift left approach is all about inducing Static Application Security Tests within Sprints. Actually, the shift left approach is more of an Agile testing practice that helps you run static test within rapid development lifecycles.

Besides, shift left approach helps to yield security into the initial phase of development to ensure the product is developed with consideration to the highest standards. Moreover, such an approach helps to diminish any chance of potential loss that might happen due to vulnerabilities taking on the project in the middle or the end. It makes the entire process of fixing errors cheaper and avoids complications that can disturb the DevOps workflow.

Bringing People, Processes, & Technology In Line

Last but the most important step to fostering DevSecOps best practices is aligning people, processes, and technology. It needs the best of people and technology to define a process that has the potential to intensify the process. Similarly, the process and technology help people to get the direction they need when it comes to planning security while developing products that can meet the predefined requirements.

As it may appear like a task to bring together a large security testing team dedicated to running scans and tests, a self-service and collaborative approach for security help to reduce cost. More importantly, the collaborative actions could help the team to meet the efficiency benchmarks when there are multiple testing requisites to be tracked.

Though it may appear easy, it needs an understanding of process components, workflow standardization, documentation, and anything that can aid the security goals into the DevOps environment. Also, it is vital that the teams and workgroups taking care of DevSecOps should understand the idea of configuration management, host hardening, and compliance scans when needed to enjoy the most sustainable and secure outcomes.

Understanding The Benefits of DevSecOps

DevSecOps is a practice that has been adopted industry-wide in order to improve product sales. The process is meant to improve security while highlighting any vulnerabilities that might hit on the system through continuous monitoring of the code and functionalities. This means it helps you create products that are more secure and helps win the customer confidence and faster release to market.

Moreover, the approach helps to discover any points of failure in the development lifecycle while cutting off any costs that might incur on the way. This means improved accountability through teams that can work collaboratively on designing robust security.

More importantly, DevSecOps is the technique to overcome security bottlenecks while accelerating product delivery. Also, it helps to leverage compliance goals and industry-regulations related to the handling of data with a holistic view of framework and compliance requirements.

The Crux: Revolutionizing Security with DevSecOps

Undoubtedly, DevSecOps has helped developers, programmers, and testing professionals to revolutionize the way security works. DevSecOps is more of a perspective that can help organizations to adopt the cultural shift while overcoming all the budget constraints and ambiguity associated with security planning.

Though the initial response of the medium and small-sized companies working into the world of technology had some skepticality, things are changing as industry professionals have started to recognize all the good DevSecOps could bring in the long run. However, the only thing that will make the difference will be balancing the above-defined strategies with the best practices. After all, cultivating precision in the process is the only thing that can assure you of the likely outcomes.

All The Best!

Author Bio: Kanika Vatsyayan is Vice-President – Delivery and Operations at BugRaptors who oversees all the quality control and assurance strategies for client engagements. She loves to share her knowledge with others through blogging. Being a voracious blogger, she published countless informative blogs to educate audience about automation and manual testing.

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