Why Software Quality Is Key To Digital Transformation and How AI Can Help?

Software quality is essential for the success of a digital transformation project. It's not just about writing code that works, but about building software with value for the users in mind that defines the success of a digital transformation initiative.

Definition: What is Digital Transformation?

The easiest definition of Digital Transformation is that it's the process of using new technologies like mobile, AI, IoT, and Cloud, etc., to transform a business model or a service. This could mean anything from using cloud-based technology to create a new app, to using artificial intelligence (AI) to improve customer service, or even automating manual processes in your business with robotics. Amazon, Uber, and Netflix, etc., are some of the classic examples of digital transformation of businesses.

Definition: What Is Software Quality?

The term software quality has a variety of meanings, depending on the context. In the context of the users or customers, it often means the usability, reliability, and security of a software or application. 

Software QA Testers typically use software quality as a measure of fitness for use or compliance to standards. Quality can be assessed by such measures as test coverage, code complexity, fault injection results, and the results of static analysis tools.

Software quality is also used in the context of product development methodologies such as agile software development, where it is associated with attributes such as simplicity and minimalism. These are different from traditional measures of quality because they are not as concerned with functional requirements as they are with other attributes that may be desirable for particular classes of products.

How Software Quality Defines Success or Failure of Your Digital Transformation Project?

At the heart of every digital transformation project is a platform or a suite of software and apps that needs to be developed and deployed. The focus lies on providing the best experience to users, in addition to catering to their needs and requirements.

The end-user experience will determine the success or failure of a digital transformation project. Truly successful digital transformation projects focus on not just the company’s but the user's needs and preferences. 

A great user experience can help you develop an innovative product that consumers love and that drives revenue and profits. A poor user experience can sink an otherwise promising product.

User experiences are created through interactions that users have with products and services, whether physical or virtual. But those interactions depend on several factors — including the quality of the software and how easy it is to use.

It's important that the new software deployed works correctly, is reliable, and is easy to use. If the quality of the software is not up to the mark, users will not be satisfied, which could result in the failure of your digital transformation process. Software Quality Management is therefore an integral part of Digital Transformation projects. 

But in order to adapt to the radical changes associated with digital transformation, it is not enough to change the development processes of existing software products. Since the software is at the center of this shift, the first step is to create a strategy to adapt your software development infrastructure to the demands of the all-digital age.

Software Quality Strategy For Digital Transformation- Key Considerations

As you consider your software quality strategy for your business’s digital transformation initiative, here are four key considerations: 

  • Software quality is a customer experience issue. It's all about the user experience, which includes how much time it takes to perform tasks, how intuitive and enjoyable the software is, and all the other elements that make the difference between a great software experience and a terrible one.
  • Software quality is a business issue. Poorly-written software projects take longer to complete, run over budget, and ultimately don't deliver value to your users or the business.
  • Software quality is a talent issue. Digital transformation requires new skills from your IT staff, who will need to work with end-users, designers, and other stakeholders to build applications rather than just maintain them after they've been built by someone else
  • Software quality is a continuous process issue. If you treat your software quality program as a project rather than an ongoing initiative, you'll never get to the level of quality you need for successful digital transformations

How Can AI Improve Software Quality?

Software quality improvement is a complex matter at best. In order to successfully improve software quality, it is important to understand the full scope of the challenge. This includes understanding the risks associated with software and how to mitigate those risks. One way of mitigating risk is through AI-driven automation.

Artificial intelligence (AI) uses algorithms to perform tasks that normally require human intelligence. AI is also used in software testing to improve the quality of software products. And, AI can also be used to identify software defects by monitoring usage behavior post-deployment.

The use of AI for software testing improves the quality of software products in several ways. It ensures that every requirement is covered by executing all test cases, reduces human errors, and improves communication between different departments within the organization.

Here are a few ways in which AI can improve software quality:

  • Static Analysis: Static analysis tools perform an automated code review that examines source code for defects and deviations from coding guidelines. These tools analyze your source code without running it and provide a report of their findings. They can be used to identify potential defects, vulnerabilities, and other issues before development starts or even after it's complete.
  • Test Generation: Software testing is a critical aspect of quality control, but it's resource-intensive and time-consuming. Test generation tools create test cases automatically through algorithms that examine the source code for defects. The resulting tests are then run against the application under development by the developer themselves or by an automated testing platform.
  • Monitoring: Debugging applications in production is harrowing work at best and next to impossible at worst. However, AI-driven monitoring makes it possible to detect anomalies within the running application and correct them before they spread. Better yet, you can use machine learning to detect some classes of problems automatically with no human intervention needed!

Qualetics- An AI-Driven Software Quality Analytics Platform

Qualetics AIMS is an all-in-one analytics platform that provides you with Software Quality Analytics along with User analytics, Product Analytics, Embedded AI features, and more, to give its platform users the most complete picture about not only the quality of their deployed applications but also the overall impact of software quality on the usage of the applications. Powered by AI, it helps you collect data from multiple sources and process it in real-time to extract actionable insights. To learn more about our Software QA platform or to book a demo, contact us here.