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Gartner defines AI code assistants as tools that generate and analyze software code and configuration. They use foundation models like LLMs, program-understanding technology, or both. Developers engage with these assistants to generate, analyze, debug, test, fix, refactor code, search dependencies, update libraries, create documentation, understand code, upgrade versions, translate languages and review commits. They help developers learn and explore codebases and access related information, such as frameworks and tools. AI code assistants integrate with developer environments, code editors, command-line terminals, chat interfaces, project management tools, monitoring, logging and deployment tools. Some are customized to an organization’s specific codebase and documentation. AI code assistants enhance software developers’ experience by boosting their efficiency, accelerating application development, minimizing cognitive overload, amplifying their problem-solving skills, enabling faster learning, fostering creativity and maintaining their state of flow.

• GitHub Copilot
  4.4

  254 Reviews

Gartner defines the application security testing (AST) market as consisting of providers of products that enable organizations to assess applications for the presence and management of risk. These products identify risk by evaluating source code, performing runtime tests and inspecting supply chain components. AST products can be integrated throughout development workflows for continuous assessment or be used to perform ad hoc evaluations. They enable organizations to manage application risks by providing an integrated set of capabilities for risk identification, prioritization and triage, policy evaluation and enforcement, and remediation assistance. Market offerings are available in on-premises, SaaS and hybrid delivery models. Organizations leverage AST products to assess applications for the presence of security vulnerabilities and other risks (e.g., legal and operational) throughout their life cycle. These assessments are used to measure and manage the risks within individual applications, application components or groups of applications in the context of their business criticality and other key attributes (e.g., environment, sensitive data handling, etc.). AST products further enable organizations to evaluate software for compliance with internal policies as well as regulatory requirements established by governments or authoritative industry groups.

• GitHub
  4.5

  116 Reviews

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.

• GitHub Codespaces
  4.3

  19 Reviews

Code review tools are software applications that help developers review and improve code quality by examining code changes, identifying issues, and ensuring adherence to standards. These tools enhance collaboration and knowledge sharing among team members, making the codebase more maintainable and reliable. Key features include enhancing code quality by automatically checking for coding standards, bugs, and security vulnerabilities. These tools allow reviewers to provide clear, actionable feedback through inline comments and streamline the integration of code changes via pull requests or merge requests. Typical users include developers, team leads, and quality assurance engineers who collaborate to maintain high code quality and streamline the development process.

• GitHub
  4.6

  146 Reviews

DevOps Platforms (Transitioning to DevSecOps Platforms)

Gartner defines DevOps platforms as those that provide fully integrated and orchestrated 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, including planning, creation, artifact management, security, quality engineering, change management, compliance, environment management, deployment and monitoring. DevOps platforms support team collaboration, consistency, tool simplification and measurement of software delivery metrics. They are delivered primarily as cloud-hosted services with some options for on-premises deployment. DevOps platforms simplify the creation, maintenance and management of the components required for the delivery of various types of modern software. Platforms create common workflows and data models, simplify user access, provide production-like development and test environments, and provide a consistent user experience (UX) to reduce cognitive load. They lead to improved visibility, auditability and traceability for the software delivery value stream. This end-to-end view encourages a systems-thinking mindset and accelerates feedback loops. Organizations use DevOps platforms to minimize tool friction resulting from complex toolchains, manual handoffs and lack of consistent visibility throughout the software development life cycle (SDLC). This enables product teams to deliver faster customer value without compromising quality. The DevOps platforms market reflects the consolidation of technologies across development, security, infrastructure and operations to streamline software delivery.

• GitHub
  4.6

  494 Reviews

Gartner defines the generative AI (GenAI) knowledge management apps/general productivity submarket as technologies that enable companies to better retrieve and contextualize information and insight from their knowledge bases, including enterprise AI search, conversational AI platforms, and productivity tools for communications and content development.

• GitHub Copilot
  4.4

  172 Reviews

Gartner defines software supply chain security (SSCS) tools as those that enable the building of secure software by protecting against compromises during development and delivery. These protections extend to source code, developer identities, development tools, delivery pipelines, and postdeployment patches. SSCS tools reduce third-party risks through policy-based curation of dependencies, software composition analysis (SCA) and software bill of materials (SBOM) inspection. They ensure artifact provenance and traceability with signing and verification as they pass through development and delivery pipelines. SSCS tools support SaaS and hybrid deployment models, and complement DevOps platforms in improving the organization’s DevSecOps maturity.

• GitHub
  5.0

  1 Review