Modern methods of analysis, software design and emerging implementation tools: challenges, opportunities and prospects

Abstract

Software engineering is undergoing a phase of rapid transformation driven by the combined influence of agile methods, DevOps, cloud computing, microservices architectures and generative artificial intelligence. This article analyses the evolution of software analysis and design methods, compares traditional and modern approaches, examines emerging implementation tools and discusses the technical, human and economic challenges, with a particular focus on the contexts of developing countries and the DRC.

The findings point to four main conclusions:

1. Agile methods now dominate modern software projects thanks to their ability to adapt to changing requirements.
2. Microservices architectures improve scalability and resilience, at the cost of greater operational complexity.
3. Generative AI boosts developers’ productivity (code generation, testing, documentation), but raises issues relating to governance, security and quality.
4. Low-code/no-code platforms accelerate application prototyping and delivery, whilst limiting customisation and portability.

By 2030, organisations that combine AI-assisted software engineering, automated DevOps, well-managed distributed architectures and continuous team training are expected to reap the most significant gains in terms of quality, time-to-market and maintainability.

Keywords: Software engineering; Software analysis; Software design; Agile methods; DevOps; Generative artificial intelligence; Microservices; Digital transformation.

Received Date: April 21, 2026

Accepted Date: May 12, 2026

Published Date: June 01, 2026

Available Online at: https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/737