Can AI Autogenerate and Run Automated Tests?

Generative AI made history last week. Launched with much fanfare were the likes of Google Bard, Adobe Firefly, Bing Image Gen, ChatGPT plugins, Roblox Generative, Nvidia DGX Power, Runway Text-to-Video Microsoft’s Notion killer and Github Copilot X.

DevOps. Agile. The Cloud. These are the adjectives increasingly associated with modern government innovation and success. But these aren’t limited to Digital Services teams or Innovation Labs. In this session, you’ll hear about how GitHub is bringing these modern successes to Federal agencies, all while improving security, meeting federal source code policy compliance, and helping to deliver mission more effectively. GitHub is the home of modern software development, and with recent additions including native vulnerability detection, improved developer collaboration and an enhanced ecosystem that supports tightly integrated best-of-breed tools, it's the perfect time for agencies to learn more about what GitHub can do for you. Whether you are migrating to the cloud, transforming your existing development process, or looking for innovative and modern ways to supercharge your agency.

AI-augmented tools like GitHub Copilot, AWS CodeWhisperer, and Diffblue Cover use machine learning to help developers with repetitive coding tasks like completing boilerplate code, calling APIs, and writing tests. These tools generate code fragments or entire functions to reduce errors and speed up development. While they are helpful for mundane tasks, fully autonomous coding remains a challenge, as writing high-quality tests requires understanding complex code dependencies and business requirements. Diffblue's reinforcement learning approach aims to autonomously write tests that satisfy developer needs and increase code coverage. These AI-assisted development tools are available today and can help eliminate tedious coding work.

Security issues, dependency vulnerabilities, misconfigurations... All of those can make or break your Open Source projects. Also, you want to make sure you adhere to the best practices, especially when you use more complex tools like Kubernetes. Let's see how we can use the tools that GitHub and Datree provide (most are Open Source too!) to secure your project and make sure that no misconfiguration ever reaches the deployment targets!

Have you been in the situation where you need to remember what is this code written by you some time ago about? Not even saying about you trying to understand someone else's code? GitHub Copilot Chat is a new way to code, where you can write code, fix bugs, write tests, and explain code to yourself and others in a chat window in a sidebar or inline. In this session, I'll demonstrate how GitHub Copilot Chat takes developer experience to the next level and how it can help you be more productive in your day-to-day work.

The document discusses GitHub Copilot, an AI programming assistant. It notes that Copilot can help reduce the pain of writing tests by providing predictive text and increasing a developer's velocity. Several use cases for Copilot are provided, including writing better comments, pair programming, writing tests, and live coding. Copilot Labs is also discussed as helping developers become comfortable in new codebases, understand StackOverflow solutions, and gain additional context on data structures. The document concludes with examples of using Copilot and a reminder that it is still in beta.

Our industry has a problem: We are not lacking software methodologies, programming languages, tools or frameworks but we need great software engineers. Great software engineer teams build quality-in and deliver great software on a regular basis. The technical excellence of those engineers will help you escape the "Waterfall sandwich" and make your organization a little more agile, from the inception of an idea till they go live. I will talk about my experiences from the last 15 years, including small software delivery teams until big financial institutions. Why would a company like to be "agile"? How can a company achieve that? How can you achieve Technical Excellence in your software teams? What developer skills are more important than languages, methods or frameworks? This will be an interactive session with a Q&A at the end.

Dive into the future of software development with Generative AI! From automating requirements to AI-powered code suggestions, discover how this revolutionary tech is reshaping the coding landscape. Stay ahead, and embrace innovation!

What is "Agile"? Why would someone like to be agile? What are the 3 pillars for agile software development? How can you achieve technical excellence in your software teams? Are developer skills more important than languages, methods or frameworks?

How do we document code? A good solution is to create self-explanatory code; this somewhat eliminates the need to document the code. We still need some very basic documentation. Code comments are one form of documentation, that is often misused. This talk is about self-explanatory code, the documentation we need and code comment patterns and anti-patterns.

How do we document code? A good solution is to create self-explanatory code; this somewhat eliminates the need to document the code. We still need some very basic documentation. Code comments are one form of documentation, that is often misused. This talk is about self-explanatory code, the documentation we need and code comment patterns and anti-patterns.

Session video: https://bit.ly/4boc1HS # # # # # Session Description: In this enlightening session, we will embark on a journey into the future of code review, where the integration of ChatGPT and GitLab CI revolutionizes the software development process. Discover how the fusion of automation, seamless integration, and cutting-edge innovation is reshaping the way we ensure code quality. Key Highlights: 1. Automation Redefined: Explore how AI-driven code review automates routine tasks, from identifying potential bugs to enforcing coding standards, freeing up valuable developer time. 2. Integration Mastery: Witness the seamless integration of ChatGPT within GitLab CI pipelines, allowing for real-time AI-powered code analysis and feedback. 3. Innovation Unleashed: Dive into the innovative solutions that emerge when human intelligence collaborates with AI, including enhanced code readability and faster development cycles. What to Expect: - Live demonstrations showcasing the ChatGPT-GitLab CI integration in action. - Insights into the benefits and challenges of incorporating AI into your development workflow. - Real-world success stories of teams already leveraging this AI-powered approach. - Practical tips for implementing AI-powered code reviews in your own projects. Join us for an engaging session that explores the possibilities and advantages of AI-powered GitLab CI, and learn how you can automate, integrate, and innovate your way to superior code quality and development efficiency. Don't miss the opportunity to shape the future of your software development process!

The document discusses code review tools and processes. It describes formal in-person code review meetings, challenges with scheduling and concentrating, and more efficient alternatives like email and web-based code review tools. It also covers motivations for code review like finding defects early and improving coding standards, and tips for effective code reviews like preparing, focusing on understanding rather than criticism, and keeping reviews short.

Talk given at ISC2 Secure SDLC event in Austin, TX The release velocity for our applications is increasing, often leaving security testing behind. In some cases, the security team ends up being the bottleneck. That's bad. In an idyllic world, security testing would happen earlier in the development lifecycle, but lets do one better. Lets do security testing on every code change. Using automation tooling and DevOps practices, this talk will help you tune security testing to your release cadence and more importantly help you deliver more rugged software.

This document is a presentation on Git and GitHub given by Olmo Maldonado. It introduces version control and why it is useful, especially for collaboration. It describes what Git and GitHub are and how they work together. The presentation walks through finding and following projects and users on GitHub. It also covers basic Git commands like cloning a repository, making changes, adding/committing, pushing changes to a remote repository, and creating/merging branches. It emphasizes using GitHub and pull requests for collaboration on projects.

In this session, we'll explore different scenarios where the features of Generative AI can provide added value to an IT solution. We'll also learn how to begin developing your own application powered by AI. Using Azure OpenAI service as an illustration, we'll examine the various APIs it offers, review the best practices of Prompt Engineering, explore different ways to incorporate your own data into the process, and take a glance at several tools and resources that make the developer experience more seamless.

Bad comments are such a big problem, that most discussion on the subject never gets past how not to write bad comments. No wonder so many programmers admit defeat and adopt a policy of writing no comments at all. This talk goes beyond bad comments to discover different kinds of good comments that are worth having, no matter how beautiful and perfect the code is.

Explore the advantages of integrating AI-powered testing into the CI/CD pipeline in this session from Applitools engineer Brandon Murray. More information and session materials at applitools.com Discover how shift-left strategies and advanced testing in CI/CD pipelines can enhance customer satisfaction and streamline development processes, including: • Significantly reduced time and effort needed for test creation and maintenance compared to traditional testing methods. • Enhanced UI coverage that eliminates the necessity for manual testing, leading to quicker and more effective testing processes. • Effortless integration with the development workflow, offering instant feedback on pull requests and facilitating swifter product releases.

Explore how to use the cutting-edge integration of Visual AI from Applitools with Kobiton's real mobile device cloud to create a comprehensive solution for continuous UI testing. See more information and find the on-demand recording at applitools.com.

See how rethinking your test automation tech stack can reduce costs, enhance agility, and expand coverage—while keeping a competitive edge.

Discover practical, AI-driven solutions to streamline test process, maintain high-quality user experiences, and accelerate eCommerce growth. Session recording and more info at applitools.com

Looking for cutting-edge AI-based test automation tools to level up your SDLC today? In this webinar, we will hit reset on the industry expectations around what your tooling needs to look and act like—and give you a preview of the new product we’ve been pouring ourselves into. You will see why now is the time to shake things up and push beyond what you thought possible in your test automation practice.

Explore how can AI drive value throughout software design, development, and testing. Session recording and more info at https://applitools.info/d0u

Explore the capabilities of AI in software test automation and see a demonstration of how AI can be used today to significantly expand end-to-end test coverage in this session with Applitools CTO Adam Carmi. Plus, see a special sneak peek of the next great wave in test automation—autonomous testing. More info and session materials at http://applitools.info/xe6

Leaders from top-performing teams share successful techniques and strategies for the implementation and execution of test automation at scale. See the session recording and more details at http://applitools.info/k6tj

Explore the efficiencies of test automation using the GienTech automation framework enhanced by the AI-powered Applitools platform. Details and session recording with demonstration at https://applitools.info/j90

Focusing on three key areas—Test Cases, Test Data, and Test Execution—these leaders shared their experience with the tools and techniques that have proven successful in their organizations. Along the way, they discussed their journey to testing at scale and which technologies and strategies have helped them reach their goals. Plus, they talked about the new innovations their top-performing teams are pursuing. More info and session materials at applitools.com