Optimizing Software Testing with Amar-AI: A Faster, Smarter Approach

software testing

In today’s digital era, where businesses increasingly rely on digital tools for their day-to-day operations, web applications have emerged as the backbone for sales, logistics, and customer interactions. For industries such as banking, insurance, e-commerce, and many others, the seamless functionality of their digital infrastructure, available 24/7 without interruptions, is paramount. To ensure this reliability, software testing takes center stage, being a critical process that stands at the forefront of quality assurance.

Software testing is the unsung hero behind the scenes, dedicated to identifying and mitigating potential flaws and vulnerabilities in digital applications. It’s the systematic process of evaluating software components and functionalities to ensure they meet predetermined standards and deliver a seamless user experience.

A $60 Billion Future

Recognizing the pivotal role of software testing, companies have been investing significantly in testing services. Consequently, the global market for application testing services is projected to reach a staggering $60 billion by 2025, growing at a compound annual growth rate (CAGR) exceeding 13% between 2021 and 2025.

The complexity code

Modern software applications are becoming increasingly complex. They encompass multiple layers of security, support cross-team collaboration, and feature sophisticated fraud detection mechanisms. With ever-expanding processing power and storage capabilities, software now handles a wider array of functions. However, this heightened complexity also makes it considerably more challenging to identify potential faults and their consequences. As a result, reinforcing quality assurance processes, particularly Software Quality Assurance (SQA), has become a necessity.

Think of these complex software applications like intricate puzzles with many pieces. These pieces (called nodes) are connected to each other through various ways (input and output data). To make sure the software works perfectly, we need to test it thoroughly, which means checking all possible paths in this puzzle-like structure. But here’s the problem: there are so many paths to check that it would take an incredibly long time to test them all.

This is where Computational Complexity Theory comes into play. It’s like a set of rules for solving problems with computers. In this case, the problem of testing every path is classified as “NP-complete,” which basically means it is extremely hard to solve efficiently with today’s technology. In simpler terms, it would take too much time and effort to test every possible way the software can work.

So, because our computers are not super-fast enough yet, it is really tough to do complete testing for complex software applications. This dilemma underscores the need for innovative solutions that can help streamline the testing process and maintain the delicate balance between software complexity and affordability.

Efficiency vs. maintenance

In response to this challenge, SQA teams employ a method of filtering and planning the paths to be tested, which are referred to as test cases. The decision-making process behind generating these specific test cases is intricate, given the high volume of test input data and interdependencies between data sets. To expedite and standardize the testing process, SQA teams often resort to test automation. However, this introduces a new challenge: automating test cases needs the development of additional code to test the application’s software, which must then be maintained post-generation.

Consequently, the development and maintenance of automated software tests consume a significant amount of time, often on par with the application’s own development timeline. Since testing typically marks the final phase of software construction, it can be a major bottleneck delaying product releases. Some companies resort to launching applications before achieving the desired quality levels, a practice that has led to more than $2 trillion loses in the U.S. in 2020. Therefore, the central challenge facing companies today is to enhance their testing capabilities while reducing the time investment required.

A game-changer in software testing

To address the pressing challenges of lengthy app development cycles and associated costs, our research and development project introduces Amar-AI, an innovative expert system poised to revolutionize the creation and maintenance of software test automation code. Our primary goal is to empower SQA teams with an intelligent support system that harnesses the potential of artificial intelligence. Amar-AI’s core mission is to eliminate the need for manual code programming and significantly expedite the generation of test cases for web applications.

Decoding Amar-AI

The crux of Amar-AI’s solution lies in its seamless workflow. SQA teams kickstart the process by inputting initial checks they want to conduct in the software (calculation parameters). From there, the system takes the reins, autonomously analyzing the application graph. Imagine it like this: Amar-AI looks at the software and figures out on its own which parts to test and what data to use, all based on what the SQA team asked for. It’s like having a super-smart helper that knows exactly what needs to be tested.

The result? Amar-AI effortlessly generates the required test software code while curating a selection of the most pertinent test cases from a vast pool of possibilities, tailored to the importance of specific parameters. This revolutionary approach optimizes SQA team capabilities and accelerates testing procedures.

Effortless testing, boundless savings

Amar-AI transforms how we approach software testing, bringing some important advantages:

  • Automatic Test Creation: Bid farewell to the arduous task of manually developing test cases. Amar-AI handles this automatically and intelligently.
  • Code-Free Testing: With Amar-AI, there’s no need for coding expertise to make your tests work. The system generates the necessary code effortlessly.
  • No More Manual Testing: Manual execution of test cases becomes a thing of the past as Amar-AI takes charge of the testing process.
  • Adaptive Test Case Maintenance: Should your application undergo updates, Amar-AI seamlessly adapts by automatically repairing the test cases, ensuring they remain effective.

The implications of Amar-AI are profound. By harnessing the power of this system, companies stand to reduce the time required to ensure application quality by up to 30 times. This translates into substantial cost savings, potentially reaching €300,000 per year for each project.

In essence, Amar-AI is not just a technological innovation; it’s a game-changer poised to redefine software testing, ushering in a new era of efficiency, cost-effectiveness, and unparalleled speed for SQA teams and businesses alike.

Implementing quality actions requires alignment of business teams and technologies. Our teams are trained to avoid potential blocking points to help you release new functionalities and keep up with the market. Learn more about our Quality & Assurance Center of Excellence here!

Project Details

Project title (original)Desarrollo de un sistema inteligente para optimizar los procesos de testing de aplicaciones web
Project title (in English)Development of an intelligent system to optimize the testing processes of web applications
Project IDIDI-20220939
Entity Amaris Consulting Spain
Project duration2022-2023
Project typeResearch and Development
Co-funding bodyCentre for the Development of Industrial Technology (CDTI)
Co-funding ProgramPID – Research and Development Projects
Implementation areaSpain

This Project has received CDTI funding from the Ministry of Science and Innovation.

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