Generative AI in Software Development

Software is an integral part of the business. You either have integrated products or enterprise apps. However, what’s stressing is the speed at which the software development space is changing. Software teams are under huge pressure to deliver more efficient, scalable, secure, and robust applications. With the traditional software development lifecycle phases, teams still struggle with quality tests, technical defects, cybersecurity vulnerabilities, and functional errors.

Thanks to Generative AI, the developers finally have smart coding assistants. Generative AI coding tools have reportedly reduced coding time by up to 30%. Moreover, these GenAI code assistant tools have resulted in a 25% reduction in software defects, helping developers build bug-free and efficient applications. AI generated code can significantly reduce coding time and software defects, making it easier for developers to integrate robust solutions into their projects.

From AI-assisted generation of architectural blueprints to automated code generation, bug testing, and streamlined CI/CD pipelines, Gen AI is transforming the entire software development space. This blog explores the role of Generative AI in software development and what the future has in store for the developers.

A new age of automation has come for businesses. Its time to shift from RPA to APA. Wondering what is APA? Read here.

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Top 5 Roles of Generative AI Tools in Software Application Development

How useful is Generative AI in software engineering? Reports indicate that Generative AI in software development can increase developer productivity by 20% to 50%. This makes a huge difference in the quality of applications and the ease of their development processes.

Here are the top 5 ways generative AI models are transforming software development and making coding, testing, and deployment a seamless experience for both developers and companies.

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1. AI-Backed Code Review

Let’s be honest, and the developer community will agree with me.

Code reviews are overwhelming and time-consuming. Manually reviewing, understanding, and analyzing code takes time, and often reviewers miss bugs or edgecases. Also, the lack of structured feedback and frequent changes frustrate the developers. Plus, all these are major bottlenecks in the software development process.

With generative AI tools, you can easily and quickly analyze existing code and get recommendations for improvement. Gen AI tools help developers do comprehensive code reviews and identify bugs, errors, code quality issues, security risks, and more. These AI-driven code review tools are complex, and your assistants help you ensure your code’s reliability, quality, and robustness.

Moreover, if you don’t want to depend 100% on AI to review your code, you can try a mix of human and AI code reviews for better results. One such tool is Reviewable, which automatically organizes code reviews into groups, helping you understand the context of code and feedback for effective enhancements.

Top 3 Gen AI code review tools:

1. Reviewable
2. GitHub Copilot
3. DeepCode
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2. Automated Code Generation

Writing code manually is time-consuming and increases the likelihood of syntax errors and bugs. Plus, spending time on mundane coding tasks drains the developers and reduces their bandwidth for solving complex problems.

AI code generation tools can do the heavy lifting for the developers while they focus on complex high-priority tasks. These tools can easily automate repetitive coding tasks, generating code and autonomously doing low-level coding.

Generative AI in software development becomes streamlined with auto-generated code, which enables you to generate boilerplate code in several programming languages. In addition, the AI coding assistant can also organize code structures, create configuration files, set up build scripts, and give specific instructions based on the developer’s chosen tech stack.

Best 3 AI code generation tools:

1. GitHub Copilot
2. Tabnine
3. Amazon CodeWhisperer
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3. Automating Testing and QA

QA teams spend at least 9 hours on a single test case for complex scenarios. The time can be extended based on the application’s complexity, code quality, integrations, and functionalities.

Software development teams can save 80%-90% of their time by automating QA processes with generative AI. One of the most useful roles of Gen AI in software development is automating and streamlining software testing and debugging.

AI-powered testing tools leverage deep learning models that can analyze your code quickly and identify bugs and functional and technical errors early in the development stage. These tools can efficiently modify data structures during the testing process, accelerating your code testing process by executing test cases at scale, flagging bugs, and pointing out security issues with high accuracy. This ensures that your software meets the expected standard and that performance bottlenecks are resolved before they become headaches.

Best 3 AI testing tools:

1. Testim
2. Mabl
3. Applitools Eyes
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4. Automated Documentation Generation

Documentation is often neglected over writing code, which results in poor-quality docs. Moreover, manual documentation is prone to errors, and often developers use different formats and styles, leading to inconsistent documentation. When it comes to large codebases, developers struggle with maintaining code flow with technical writing.

AI powered coding tools for automated documentation generation leverage natural language processing (NLP) and machine learning to simplify and enhance the documentation process. These tools analyze code, extract logic, and produce clear and standardized documentation.

Generative AI documentation automatically understands the code logic, structure, and functions to generate inline comments or summaries for methods, classes, and modules. It also synchronizes with code changes to avoid outdated documents. This saves developers’ time, maintains consistency, reduces errors, and improves team collaboration.

Top 3 AI documentation generation tools:

1. Sourcery
2. IntelliCode (by Microsoft)
3. GitHub Copilot Docs
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5. Security, Compliance, and Threat Detection

70% of applications have flaws that fall under the OWASP Top 10, which identifies critical risks to web applications. Also, 75% of applications have one major security flaw. These numbers show a widespread nature of security and compliance vulnerabilities in applications.

Generative AI in software application development can help you identify potential security and compliance risks and maintain the reliability of applications. Gen AI tools can instantly scan codebases for risks like SQL injection, XSS, buffer overflows, etc. Additionally, these tools help improve code quality by identifying security risks and providing detailed suggestions for refinement. Also, it can provide context-aware recommendations and flag potential misconfigures to enhance the security of the code.

In addition, generative AI tools can ensure policy enforcement, license complaint, audit trail automation, and data privacy monitoring so that your application is compliant to industry standards.

Top 3 Gen AI tools for security and compliance:

1. Snyk
2. Checkmarx
3. Darktrace PREVENT/Detect
   
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What Is Next For Generative AI In Software Development?

The shift from Gen AI to AI agents involves advancements in generative AI model technologies, which could change how we write and deploy codes forever. With the coming of AI agents in software development, we will potentially witness the autonomous nature of AI agents in developing, testing, and deploying codes. We can also have multi-AI agent systems where different AI agents can autonomously collaborate to execute coding tasks with higher efficiency.

AI agents will autonomously understand requirements, generate code, write technical documentation, put code through automated debugging, and improve it further to meet expectations without much human intervention.

Please note that we are not suggesting the complete removal of human contribution to application development. Instead, we are to witness the next level of human and AI agent collaboration to produce robust applications.

Wondering how Agentic AI can benefit your business and help you achieve your targets? Read this article that delves into the core benefits of Agentc AI in your business processes.

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Harness Agentic AI and Gen AI in Software Development

As we are moving closer to adopting sophisticated versions of artificial intelligence, AI agent platforms, and Generative AI development companies will play a crucial role in real world software development by building cutting-edge applications powered by AI.

Wondering where and how you can implement Agentic AI in your business workflows? Read here.

Businesses looking to stay ahead of the competition and break the market should invest in AI in their products and internal workflows. But finding the right tech partner to navigate the complexities of AI solutions is frustrating. You need someone who is not only technically sound but also receptive to turning your vision into a viable product.

Ampcome is one such Gen AI development company with a core AI team proficient in handling complex AI and ML projects and delivering outstanding results. We also have a low-code AI agent platform that enables businesses to build AI agents with pre-built templates customized to their data and needs. With our AI agent solutions, you can build AI agents and integrate them into your workflows to supercharge your teams.

Want to learn more about our Gen AI solutions or AI agent platform?

Book a meeting with our team now!

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