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AI for software development in 2024: Use cases, risks, and tools

AI for software development in 2024: Use cases, risks, and tools

Tabnine Team /
7 minutes /
May 26, 2024

How is AI used in software development in 2024?

Artificial intelligence technologies are being used to automate and enhance various aspects of software engineering. This includes tasks from coding to testing, debugging, refactoring, and creating code documentation. The integration of AI into software development aims to make these processes more efficient and less error prone, and to free up time for human innovation.

Using natural language processing technologies, most notably large language models (LLMs), AI code assistants are helping developers build applications faster, reduce manual tasks, and address complex problems more easily. Modern AI tools are trained on vast code datasets, and are able to learn coding patterns, best practices, and generate human-like code, dramatically streamlining software development workflows.

6 use cases of AI in software development 

1. Code generation

AI-driven code generation tools are revolutionizing the way developers write code. These tools, powered by LLMs, can generate short code completions, entire code snippets, or even complete programs based on existing code or natural language prompts from the developer. This reduces the time spent on boilerplate code and allows developers to focus on more complex and innovative aspects of their projects.

How Tabnine helps

Tabnine is the AI code assistant that accelerates and simplifies software development while keeping your code private, secure, and compliant. It provides accurate, highly personalized results for generating code, writing unit tests, creating documentation, explaining legacy code, fixing code, and much more.

Tabnine delivers highly personalized recommendations by utilizing the context from locally available data in your IDE as well as your organization’s global codebases. Additionally, Tabnine offers model customization to further enrich the capability and quality of the output.

With Tabnine, you can generate new code using natural language. As you continue coding, Tabnine provides inline code completions, offering real-time, context-aware suggestions that seamlessly blend with your coding style.

2. AI pair programming

AI pair programming involves an AI-driven assistant that works alongside human developers, offering suggestions, completing lines of code, and providing real-time feedback. This concept is akin to traditional pair programming but with AI in the role of the collaborating programmer. It leverages natural language processing and LLMs to understand the context of the project and the developer’s intentions, offering appropriate code suggestions and optimizations.

This collaborative approach enhances productivity and learning, as developers get instant feedback and suggestions. It also helps in maintaining a high code quality, as the AI assistant can identify potential issues and suggest improvements based on vast databases of coding patterns and best practices.

How Tabnine helps

Tabnine is fully integrated in all the major IDEs, including Visual Studio Code, JetBrains, Eclipse, and Visual Studio, and supports over 80 programming languages and frameworks. It offers in-line code completions for full-line, whole functions, and generates code from comments in natural language. Tabnine Chat is an enterprise-grade, code-centric chat application that allows developers to interact with Tabnine AI models using natural language and supports numerous use cases, such as code generation, code explanations, documentation generation, AI-created tests, and more.

3. AI testing

AI testing refers to the use of artificial intelligence to automate and improve software testing processes. AI-powered testing tools can intelligently generate test cases, predict where bugs are most likely to occur, and suggest fixes. These tools can also analyze code changes to prioritize testing efforts and optimize test coverage.

AI significantly improves the efficiency of testing, reduces the manual effort required, increases test coverage, and catches more errors before they make it to production. This contributes to more stable and reliable software products without an increased investment in testing.

How Tabnine helps

Tabnine assists with software testing by offering predictive suggestions for potential test cases based on the code being written. Ask Tabnine to create tests for a specific function or code in your project, and get back the actual test cases, implementation, and assertion. Tabnine can also use existing tests in your project and suggest tests that align with your project’s testing framework. Tabnine can write unit tests and identify edge cases, common bugs, and necessary validation points that the developer may have overlooked. This can help improve test coverage with minimal effort. 

4. Catching bugs and coding errors

AI significantly improves the bug detection process in software development. By learning from historical data, AI models identify patterns and anomalies that indicate potential issues, catching bugs that manual reviews might miss. Most importantly, AI tools integrated into IDEs can flag coding issues while developers work, making remediation effortless.

AI tools provide contextual insights rather than just flagging errors. They suggest optimal solutions based on best practices and previous projects, streamlining the debugging process and enhancing code quality.

How Tabnine helps

Tabnine can fix detected bugs and coding errors, offering real-time suggestions as developers code. It can resolve syntax errors, suggest corrections, and provide contextual insights to help developers resolve issues quickly. Drawing from a vast code knowledge base, it identifies antipatterns and common pitfalls, suggesting best practices that improve overall code quality. By seamlessly integrating into your IDE, it allows developers to address these issues on the fly.

5. Refactoring code

AI helps with code refactoring by analyzing existing code bases and suggesting improvements for efficiency, readability, and maintainability. This involves optimizing code without changing its external behavior, making the software easier to understand, reduce, and extend.

AI-powered tools can automate much of the refactoring process, identifying and implementing safe refactoring opportunities. Although suggestions still require review by human programmers, this can dramatically reduce the time needed to refactor a complex codebase.

How Tabnine helps

Tabnine Chat can refactor code using human language (e.g., “Add type specification,” “Change convention,” etc.). It identifies refactoring opportunities, such as optimizing loops, eliminating redundant code, or improving function modularity. Tabnine also learns from your project structure and coding style, ensuring that the proposed changes align with your coding standards.

6. Code explanation

AI enhances code comprehension by providing explanations for complex code snippets. This is particularly useful for maintaining and updating legacy systems or onboarding new team members. By interpreting and explaining code behavior, AI tools bridge knowledge gaps and facilitate smoother project transitions and collaborations.

These AI-driven explanations also serve as an educational tool, helping developers understand new coding techniques or languages quickly. This continuous learning environment contributes to a more skilled and versatile development team.

How Tabnine helps

Tabnine helps developers understand complex code snippets by generating easy-to-understand explanations. You can ask Tabnine to explain specific code snippets, which is especially useful for legacy code or unfamiliar languages.

Its advanced language models analyze a codebase, providing meaningful summaries that help new team members get up to speed quickly. Whether deciphering legacy code or learning a new function’s purpose, Tabnine’s explanations help developers quickly understand code logic, bridge knowledge gaps, and improve code comprehension

4. Summarizing code and documentation

AI tools can effectively analyze and summarize complex codebases, automatically generating concise documentation. This not only saves developers time but also ensures documentation stays updated, enhancing code maintainability and readability. In addition, many AI tools allow developers to request specific information from predefined code repositories or documentation sets, and LLMs can synthesize a precise information summary.

How Tabnine helps

Tabnine’s documentation capabilities help create formal documentation for classes, functions, comments, and in-line documentation. Tabnine can assist with summarizing code and documentation by analyzing your codebase and auto-generating concise summaries. These summaries are both accurate and contextually relevant, ensuring developers can quickly understand the purpose of various functions, classes, or modules. This is especially valuable for maintaining updated documentation that aids in troubleshooting, onboarding, and project handovers. Tabnine can also generate relevant code comments and detailed code documentation.

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Will AI replace software developers? 

The emergence of AI in software development sparks concerns about job displacement. However, rather than replacing developers, AI acts as an assistant, automating mundane tasks and augmenting human capabilities. This partnership allows developers to increase their productivity and focus on more strategic and creative aspects of software development.

While AI advances, it still requires human intuition, creativity, and oversight to tackle complex, abstract problems. In addition, AI tools often make mistakes, either by misinterpreting instructions, lacking understanding of the broader context of a task, or by “hallucinating” and creating incorrect or nonfunctional code. 

The collaboration between AI and human developers leads to innovation and efficiency that neither could achieve alone. The future of software development lies not in replacement but in the integration of AI and human expertise.

The risks of AI in software development and how to mitigate them 

Using AI code tools in an organization raises several important risks:

  • Proprietary code leakage: AI tools are often allowed to access and analyze existing, proprietary code, or even entire proprietary code repositories. This poses a substantial risk of exposing sensitive business logic or proprietary algorithms to third parties.
  • Security: AI tools are trained on vast code datasets, which might include insecure, out-of-date, or even malicious code libraries. Thus, these tools could generate insecure code in their outputs. 
  • License compliance: If AI trains on datasets that include code with nonpermissive open source licenses (known as “copyleft”), it could generate code similarly protected under nonpermissive licenses, creating legal issues for the organization. Using open source code with copyleft licenses could limit the ability to commercialize a software project. 

How Tabnine protects your privacy, security, and IP 

Unlike other AI code assistants, Tabnine gives you complete privacy over your code and data. We offer a zero data retention policy and offer on-premises air-gapped or VPC deployment options. Your code is never stored and is never used to train our models. And only you can access any custom enterprise models pretrained on your code privately in your environment. 

If you decide to select enterprise SaaS for your deployment, we take several steps to protect your data and privacy. Tabnine uses end-to-end encryption for any data transmitted between your users’s machines and our servers, along with transport layer security and compliance with data handling policies. We don’t retain any of your code on our servers. By leveraging ephemeral processing, we handle requests to provide coding suggestions and then immediately discard any data. 

Tabnine eliminates concerns around IP infringement from the get go. We’ve trained our proprietary models (Tabnine Protected for Chat, and the universal model for code completion) exclusively on code that is permissively licensed. This ensures that the recommendations from Tabnine never match any proprietary code and removes any concerns around legal risks associated with accepting the code suggestions. We’re transparent about the data that was used to train our proprietary model and share it with customers under NDA. Additionally, we offer an IP indemnification to enterprise users for peace of mind.

Tabnine: The AI code assistant that you control 

Tabnine is an AI code assistant that helps development teams of every size use AI to accelerate and simplify the software development process without sacrificing privacy, security, or compliance. Tabnine boosts engineering velocity, code quality, and developer happiness by automating the coding workflow through AI tools customized to your team. Tabnine supports more than one million developers across companies in every industry. 

Unlike generic coding assistants, Tabnine is the AI that you control:

It’s private. You choose where and how to deploy Tabnine (SaaS, VPC, or on-premises) to maximize control over your intellectual property. Rest easily knowing that Tabnine never stores or shares your company’s code.  

It’s personalized. Tabnine delivers an optimized experience for each development team. It’s context-aware and delivers precise and personalized recommendations for code generation, code explanations, guidance, and for test and documentation generation.

It’s protected. Tabnine is built with enterprise-grade security and compliance at its core. It’s trained exclusively on open source code with permissive licenses, ensuring that customers are never exposed to legal liability.

Tabnine provides accurate and personalized code completions for code snippets, whole lines, and full functions. Tabnine Chat in the IDE allows developers to communicate with a chat agent in natural language and get assistance with various coding tasks: 

  • Generating new code 
  • Generating unit tests 
  • Getting the most relevant answer to your code
  • Mentioning and referencing code from your workspace
  • Explaining code
  • Extending code with new functionality
  • Refactoring code
  • Documenting code
  • Onboarding faster with the Onboarding Agent

Learn how to use Tabnine AI to analyze, create, and improve your code across every stage of development:

Try Tabnine for free today or contact us to learn how we can help accelerate your software development.