Gartner defines AI code assistants as tools that assist in generating and analyzing software code and configuration. The assistants use foundation models such as large language models (LLMs) that have been optionally fine-tuned for code, or program-understanding technologies, or a combination of both. Software developers prompt the code assistants to generate, analyze, debug, fix, and refactor code, to create documentation, and to translate code between languages. Code assistants integrate into developer tools like code editors, command-line terminals and chat interfaces. Some can be customized to an organization’s specific codebase and documentation. AI code assistants can enhance a software developer’s experience by boosting efficiency, accelerating application development, minimizing cognitive overload, amplifying problem-solving skills, accelerating learning pace, fostering creativity and maintaining state of flow.
Gartner defines the application security testing (AST) market as the buyers and sellers of products and services designed to analyze and test applications for security vulnerabilities. This market is highly dynamic and continues to experience rapid evolution in response to changing application architectures and enabling technologies. AST tools are offered either as software-as-a-service (SaaS)-based subscription offerings, or less often, as on-premises software. Many vendors offer both options.
Cloud development environments (CDEs) provide remote, ready-to-use access to a cloud-hosted development environment with minimal effort for setup and configuration. This decoupling of the development workspace from the physical workstation enables a low-friction, consistent developer experience. CDEs offer built-in integrated development environment (IDE) capabilities such as code editing, debugging, code review and code collaboration, but also integrate with artificial intelligence (AI) code assistants and DevOps tools such as source code and artifact repositories. CDE users include but are not limited to software engineers, data scientists and AI engineers. CDEs provide consistent, secure developer access to preconfigured remote development workspaces. This frees developers from setting up their own local environments, eliminating the need to install and maintain dependencies, software development kits, security patches and plug-ins, which increasingly include AI code assistants. CDEs are prepackaged with tools to support multiple programming languages and frameworks enabling teams to write code across multiple technology stacks with standardized and templatized workflows. Developers can either access a remotely hosted IDE using a browser-based interface or use their locally installed IDE to connect to the CDE.
Gartner defines DevOps platforms as those that provide fully integrated capabilities to enable continuous delivery of software using Agile and DevOps practices. The capabilities span the development and delivery life cycle built around the continuous integration/continuous delivery (CI/CD) pipeline and include aspects such as versioning, testing, security, documentation and compliance. DevOps platforms support team collaboration, consistency, tool simplification and measurement of software delivery metrics. DevOps platforms simplify the creation, maintenance and management of the components required for the delivery of modern software applications. Platforms create common workflows and data models, simplify user access, and provide a consistent user experience (UX) to reduce cognitive load. They lead to improved visibility, auditability and traceability into the software development value stream. This end-to-end view encourages a systems-thinking mindset and accelerates feedback loops.
Generative AI (GenAI) apps use generative AI capabilities for user experience and task augmentation to accelerate and assist the completion of a user’s desired outcomes. Generative AI refers to technologies that can generate new derived versions of content, strategies, designs and methods by learning from large repositories of original source content. When embedded in the experience, generative AI offers richer contextualization for singular tasks such as generating and editing text, code, images and other multimodal output. As an emerging capability, process-aware generative AI agents can be prompted by users to accelerate workflows that tie multiple tasks together. Apart from helping save time and money, generative AI apps help improve branding of businesses by creating more engaging and effective content while also creating more engaging and immersive experiences for customers. Please note that this market is based on Beta research and is continuously evolving. We will be making changes as and when there are new updates.