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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.

• GitLab Duo
  4.3

  6 Reviews

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.

• GitLab
  4.4

  185 Reviews

DevOps Platforms

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.

• GitLab
  4.5

  546 Reviews

Gartner defines enterprise agile planning (EAP) tools as products that enable organizations to scale their agile practices to support a holistic enterprise view. These tools act as a hub for defining, planning, managing and deploying work. They also serve as an information hub for the disparate islands of metrics from the full life cycle. Just as agile is an evolution of development methodologies, EAP tools are an evolution of project-/team-centric tools. They support a business-outcome-driven approach to managing the full life cycle of agile product delivery at scale. EAP tools in this market combine data from multiple sources to enable: - Monthly, weekly and even daily incremental value delivery based on business outcomes - Support for enterprise agile frameworks like Scaled Agile Framework (SAFe) - Product roadmapping - Management of strategy, investments and objectives - Increased visibility into the flow of work - Management of work backlogs - Collaboration capabilities for individuals and teams - Management of cross-team dependencies - Release planning and forecasting - Visibility into the financial aspects of the work being done

• GitLab
  4.4

  462 Reviews

Gartner defines Software Composition Analysis (SCA) as a technology that analyzes applications and related artifacts (containers, registries, etc.) to detect open-source and third-party software components known to have security and functional vulnerabilities, are out-of-date for security patches, or that pose licensing risks. SCA products and services help ensure the enterprise software supply chain includes only secure components and, therefore, supports secure application development and assembly

• GitLab
  4.0

  8 Reviews

Gartner defines software engineering intelligence (SEI) platforms as solutions that provide software engineering leaders data-driven visibility into the engineering team’s use of time and resources, operational effectiveness, and progress on deliverables. This data-driven visibility enables software engineering leaders and their teams to make smarter business decisions, which leads to the delivery of increased value to customers. SEI platforms must be able to ingest and analyze the signals created by common engineering tools and systems. They must provide rich, tailored, role-specific user experiences to enable leaders to more easily query data to identify important trends and gain contextual insights. Software engineering intelligence platforms are used by software engineering leaders and their teams to better understand how software solutions are being built and delivered. Teams can more easily see where they are spending time and how they are approaching code quality (e.g., code reviews), and better understand team flow through key metrics like deployment frequency and cycle time. These platforms serve as a single source of truth for engineering data, providing a unified, comprehensive and transparent view of the engineering processes. Key engineering metrics for delivering digital products include team productivity, business alignment, software quality and operations effectiveness. Organizations can use SEI platforms to better understand their software development life cycle and gain insights into how their teams build software. These organizations can use these insights to continually adjust, experiment with and improve their processes and practices, yielding improved business alignment, higher quality software and happier, more productive teams.

• GitLab
  4.4

  11 Reviews