How to speed up software development with ChatGPT, GitHub Copilot, and Tabnine.

Jun 19, 2023 |
Tech |
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AI tools are causing a lot of arguments about what will happen to jobs, education, technology, and software development in the future. Leaders in the tech industry are thinking about the risks to security and the possibility of AI tools breaking the rules of intellectual property when used for coding help. On the other hand, people who have a lot of influence in the tech world on social media sites like Twitter and LinkedIn are talking about how AI-powered tools can make us more productive and trying to guess which jobs will go away first.

Since the industrial era, there have been concerns about job losses caused by advancements in technology and automation. Today, these worries are resurfacing, particularly regarding software development. People question whether those without coding experience can build software and if AI will replace human developers. However, the answer is no. While AI and machine learning tools can accelerate code writing, bug fixing, and aid in learning new programming languages and frameworks, they won’t entirely replace the need for human developers.

We will examine the effects of employing AI tools in software development, such as OpenAI’s ChatGPT, GitHub Copilot, and Tabnine, in this blog. We gathered data from academic articles and discussions with engineers who provided concrete examples of how these technologies aided them in accomplishing significant programming jobs. We will also include resources to help users learn more about using these tools and comprehend the concepts and history of AI.

ChatGPT

The AI chatbot ChatGPT was created by OpenAI. The chatbot, which was first made available for demonstration reasons, has been widely utilized for a number of tasks, including analyzing and summarizing text, filtering material, and producing code.
According to Goldman Sachs analysts, it just took two months for the company to reach the milestone of 100 million users. The app’s sudden success has made AI adoption a hot topic for businesses and entrepreneurs right now.

Let’s find out what the main character of the tech news in 2023 thinks about using ChatGPT to accelerate software development and boost developer productivity.

How can ChatGPT speed up software development?

As stated by ChatGPT, it can:

  • Give code recommendations that make sense in the context of the current code;
  • Find mistakes and defects and provide solutions to remedy them;
  • the creation of code for standard activities such declaring classes, class variables, constructors, and other procedures;
  • Publish the code documentation.
  • Give non-technical professionals and developers access to natural language inquiries.

Boilerplate code, or pieces of code that must be included in numerous places with little or no modification, is one specific instance where ChatGPT is most effective. AI aids in creating previously unimagined ideas, according to a YouTeam developer study. Additionally, it is quicker to inform ChatGPT of the developer’s requirements and then adjust the code when dealing with well-known code structures and techniques.

The chatbot is also fantastic for senior citizens and those just learning how to program, who utilize it to investigate certain subjects or get quick answers to questions rather than searching them. In actuality, a person would have to choose an appropriate topic from the search results, go to the website, turn off unnecessary cookies, and sift through advertising banners to locate a well-explained programming article on Google. If the response falls short of expectations, the developer must return to the search results and attempt to locate the data on a different website. With ChatGPT, however, a search can be completed in a matter of seconds; all the developer needs to do is start a new chat and pose the query.

What are the pitfalls of using ChatGPT for software development?

Software engineers caution that the OpenAI chatbot may dream up an absurd response to some questions, such as specialized Azure and AWS information. In these circumstances, the chatbot typically just invents names for crucial tasks that aren’t listed in the documentation.

Additionally, detractors of ChatGPT claim that while the tool excels in arranging words in a statistically significant sequence, it is unable to comprehend the meaning or determine whether the claims it makes are true. Additionally, the majority of the URL sources and citations sent by the application when you request them are either invalid links or point to unrelated subjects.

Github Copilot

OpenAI Codex, a machine learning model that converts text from natural language into code, powers GitHub Copilot, a cloud-based AI application. The source code from publicly accessible sources, such as GitHub repositories, was used to train the model.

How can GitHub Copilot accelerate software development?

On its website, GitHub Copilot lists the following features:

  • creating codes out of natural language commands;
  • recommendations for multi-line functions;
  • generating tests more quickly;
  • removing frequent coding patterns that are vulnerable;
  • preventing ideas that match open source code.

As users define the desired logic, Copilot automatically integrates into code editors like Neovim, JetBrains IDEs, Visual Studio, and Visual Studio Code and suggests code and whole functions. This is particularly advantageous when the user is exploring new area. They must, for instance, export data as an XLS file. A software engineer must spend several hours learning ExcelJS, a JavaScript library for reading, processing, and writing spreadsheet data in the XLSX format. Programmers can use Copilot to post comments outlining their needs, and Copilot will subsequently recommend possible lines of code.

The conversation mode was also included by the Copilot X plugin, which was released in March 2023. Users may now mark code in the editor and then ask Copilot questions about it, use it for refactoring, or request debugging assistance.

GitHub Copilot can also translate code between programming languages and write code descriptions in English.

What are the pitfalls of using GutHub Copilot for software development?

Copilot is charged with breaching intellectual property rights, same like ChatGPT was. A class action lawsuit for software infringement was brought against GitHub Copilot in November 2022. According to the plaintiff, the tool occasionally makes code suggestions that are an exact replica of the open-source code that Copilot was trained on.

Additionally, developers must carefully examine the code the tool suggests because some of its snippets may have security flaws that might be abused by injection attacks. The business advises utilizing the tool in conjunction with testing and code review procedures, security tools, and the developer’s own discretion as the generated code can also contain references to out-of-date APIs or idioms, according to GitHub.

Additionally, there is a chance that software engineers will lose interest in learning to program through reading, taking classes, reading scholarly articles, and attending workshops as they grow too reliant on the AI tool.

Tabnine

Software developers’ helper Tabnine employs generative AI to anticipate and suggest the following lines of code based on the context and syntax. According to Tabnine, it has created language-specific native AI models for code that are pre-trained on the language and offer more accurate auto-completion.
The company further asserts that only open-source code with permissive licenses is utilized as training data and that only private code models are ever trained using developer input and generated code. Additionally, as stated on its website, Tabnine’s servers don’t save any user code for a period of time past that required for training.

Finally, Tabnine offers both a free and a premium plan, however the free subscription only includes rudimentary short code completion.

How can Tabnine increase developer productivity?

The developer’s own model is trained by Tabnine’s coding assistant using their particular code patterns. Similar to GitHub Copilot, the tool supports the most widely used programming languages, libraries, and frameworks, and provides whole-line and full-function code completion as well as natural language input.

What are the pitfalls of using Tabnine for software development?

Similar to Copilot, there is a chance that software engineers will become overly reliant on the AI helper and forgo continuing their education through professional books, seminars, courses, and research papers.

Conclusion

As more and more engineers claim increased productivity and quicker acquisition of new languages, libraries, and frameworks, the introduction of huge language models and AI coding assistants is changing the patterns of software development.

However, some computer professionals are concerned that advanced AI tools would eventually reveal and monetize the exclusive IP, without the developers even being aware of it, amid growing concerns about big tech corporations selling private information and increasingly frequent data breaches. Software developers advocate migrating to privately hosted repositories in this situation to secure the most valuable code assets.

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