Gen AI: Transforming Software Engineering in the Digital Age
If you are following the trends in the realm of Gen AI, you would notice that every day, a ton of LLMs and tools are being introduced in this space. The opportunity unleashed by the Gen AI space is promising and disruptive but the initial models are confined to the space of producing text, images, code, videos, speech and music with some investment also made in the game and 3D objects.
However, when it comes to employ the new Gen AI capabilities in the software engineering discipline, caution should be observed since the space is flooded with hyped up Gen AI offerings where only few live up to the promise. In this blog post we take a quick peek at some of the key areas where we at Visionet believe Gen AI will disrupt the market and the Gen AI enabled tools will offer operational excellence and become crucial for technology services companies from market sustenance perspective:
User stories writing:
It all starts with a good user story. Gen AI can assist in crafting detailed and relevant user stories by analyzing patterns from the existing project data and user feedback. We believe that this avenue will be heavily transformed by the inclusion of Gen AI tools that facilitate the Business Analysts and Product Owners to define the prioritized backlog that is seamlessly translated into the user stories.
A good amount of software development effort goes into establishing the right CI/CD pipelines. Gen AI can not only streamline the DevOps pipeline by automating repetitive tasks, it can also optimize resource allocation. In the very future, we foresee this space to be exploded by the tools that will provide data-driven insights for continuous improvement.
Code Generation & Completion:
Almost everyone has heard of GitHub CoPilot or OpenAI Whisperer. But one area where Gen AI has already matured a lot is the code generation and completion where the power of code patterns and LLMs collaborate to give rise to clean and crisp code. Even as of today, Gen AI accelerates development by generating code snippets and suggesting context-aware completions. At present, a developer equipped with Gen AI tools is able to complete the same task faster than a developer who isn’t but we reckon this trajectory will continue to flourish.
Code Audit & Refactoring:
With the Gen AI tools available in the market today, Gen AI can conduct comprehensive code audits, flagging potential issues and discrepancies. However, it is only a short span where the complete code audits shall be carried out by the Gen AI agents. These Gen AI enabled agents will seamlessly plugin in the integrated development environments (IDEs) offering actionable recommendations to enhance code quality and maintainability. Similarly, Gen AI can aid in identifying complex code segments, suggesting efficient refactoring strategies, and transforming codebases for improved readability and performance.
No technology today solely relies on manual testing of the vulnerability assessments. We already put the invasive and non-invasive tools to carry out the vulnerability assessment. However, what Gen AI enabled tools can offer in this space is to simulate potential exploits and vulnerabilities based on the patterns of usage of the applications and code styles. For example, a Gen AI tool can monitor the traffic patterns and fortify applications in real time prior an actual attack is launched by simulating the potential attacks in the lower environments and assists in designing effective testing scenarios for robust security.
In this blog post, we outlined some of the key stages of the SDLC that we at Visionet believe shall be heavily impacted by the inclusion of Gen AI tools. We also discussed that as the existing Gen AI models and tools will get sophisticated and the multimodal models (models combining more than one capability) shall evolve, various tedious and complex software development tasks that are performed by engineers today shall be taken up by these tools.
As a software engineering first and services provider company, we constantly evaluate, validate and embed the Gen AI capabilities in our Software Development Life Cycle (SDLC). This ensures that we not only leverage the best-in-class tools that add value to our esteemed delivery capabilities, this inclusion also makes us more efficient and helps us serve our customers better.