Next-generation software development (Next-Gen Dev) refers to the latest advancements and methodologies used to create software applications. It is the collective name given to development processes engaging with cognitive technologies, low-code platforms, and better cybersecurity and compliance measures, among other emerging trends.
The motivations for these new-gen software development is advanced workflows, automotive applications, low-code development, among others. Cybersecurity needs against emerging cyber threats also play and important role. The resulting software products serve complex service demands and customer experience journeys across industries. It’s no exaggeration when Gartner predicts that 70% of web and mobile application design and development will adopt Generative AI in some form or another. Here are some more trends that are nourishing the next generation of software:
We have seen a generation of software development that focused heavily on manual coding, monolithic architectures, and limited automation. Security often followed the development cycle as an afterthought, and the lack of agile methodologies resulted in slower deployment and iteration cycles. These are some aspects that seem more evolved in next-gen software development. Here are some visible impacts:
Business leaders must pay attention to any generation of software development to stay competitive, drive innovation, and enhance operational efficiency. Keeping abreast of software advancements ensures that organizations can leverage the latest technologies to meet market demands and improve customer experiences.
To measure the ROI of next-gen software development, one must first understand that ROI in software development generally quantifies the financial return from investments in new technologies and processes. ROI can differ across industries due to varying operational costs, revenue models, and market demands.
Common metrics include development speed, cost savings, quality improvement, user satisfaction, and revenue growth. For next-gen software development, these metrics may need tweaking to include factors such as AI and automation efficiency, cybersecurity enhancements, and the adoption rate of low-code/no-code platforms.
This ensures a comprehensive evaluation that reflects the unique benefits of next-gen practices.
The future of ROI in next-gen software development is promising, driven by advancements in AI, automation, and cloud-native practices. Businesses will see enhanced efficiency, security, and scalability.
The evolving metrics will better capture the value of innovation and speed in today's competitive market. Here are some possible avenues that can open up for next-gen software development:
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Product engineering is an end-to-end process of ideate, develop, test, and deploy software products that meet evolving market demands. It integrates cutting-edge engineering principles, design thinking, and project management to deliver scalable, high-quality, and user-centric solutions across industries. Product engineering ensures efficient development cycles, enhanced user experiences, and seamless innovation to help businesses stay competitive.
Engineering modern software products require expertise with the latest tools and technologies. For instance, generative AI is transforming product engineering by automating design processes, enhancing creativity, and accelerating development cycles.
As per the Gartner poll, 55% of organizations are in production mode if not already piloting with gen AI. With a focus on product design that offers aesthetically pleasing and user-centric solutions, product engineering skills now touch upon proficiency in cloud computing, AI/ML, and DevOps, among others.
Software development is the process that enables the creation, design, deployment, and maintenance of software using advanced technologies and methodologies. Demands by modern development projects are emerging with a strong focus on AI/ML integration, cybersecurity, cloud-native development, and low-code/no-code platforms.
By integrating advanced AI and machine learning tools for automated coding and testing software development experts help reduce development time and human error. Practices like DevSecOps are taking care of the cybersecurity front by protecting applications from evolving cyber threats throughout the life-cycle to create system software.
Reports suggest that globally, around 28.7 million people are expected to be involved in developing software by 2024. A big reason for this is that modern software has more complex demands that need more minds to collaborate. The software now needs to be scalable and flexible and that’s where cloud native architectures play a critical role.
Moreover, low-code and citizen development helps democratize this entire process to allow faster deployment and innovation. These advancements collectively enable organizations to respond swiftly and securely to market changes.
Software testing is the process of verifying and validating that a software application performs its intended functions correctly, meets specified requirements, and operates reliably under various conditions. It detects errors early, saves costs, and assures reliability, security, and performance. Various methods include performance testing, automation, regression, and exploratory testing.
This article explores manual and automated testing, tailored testing plans, and scripts for different software types. It discusses challenges in testing and emerging technologies shaping the future of testing improving the development life cycle. Understanding test automation techniques and selecting appropriate tools enhance software quality and mitigate risks.