Gartner defines AI-augmented software testing tools as enablers of continuous, self-optimizing and adaptive automated testing through the use of AI technologies. The capabilities run the gamut of the testing life cycle including test scenario and test case generation, test automation generation, test suite optimization and prioritization, test analysis and defect prediction as well as test effort estimation and decision making. These tools help software engineering teams to increase test coverage, test efficacy and robustness. They assist humans in their testing efforts and reduce the need for human intervention in the different phases of testing.
The application development life cycle management (ADLM) tool market focuses on the planning and governance activities of the software development life cycle (SDLC). ADLM products focus on the 'development' portion of an application's life. Key elements of an ADLM solution include: software requirements definition and management, software change and configuration management, software project planning, with a current focus on agile planning, work item management, quality management, including defect management. Other key capabilities include: reporting, workflow, integration to version management, support for wikis and collaboration, strong facilities for integration to other ADLM tools.
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.
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
The In-app protection market refers to security solutions implemented within the application (instead of the network or the operating system, for example) to make the application more resistant to attacks such as malicious data exfiltration, intrusion, tampering, and reverse engineering. Enterprises use in-app protection to safeguard their software-based assets and to protect their organization and customers from fraudulent attacks.
Product roadmapping tools for software engineering have simplified product-related communication and streamlined product management and development efforts. This document profiles selected vendors and tools that can assist with: Management of software product vision and strategy alignment Communication of ideas and requirements Decision making through an understanding of user behavior, data and analytics, priorities, and consequences Defining software features and business capabilities, and handling backlogs Planning and tracking software development releases Financial and budget management Collaboration on timelines Communication, negotiation and updates Integration planning and resource tracking Report generation and notifications Managing feedback from developers, teams and users Support for continuous development and continuous integration
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.
Value stream management platforms enable organizations to optimize end-to-end product delivery and improve business outcomes. VSMPs are tool-agnostic; they connect to existing tools and ingest data from all phases of software product delivery all the way from customer need to value delivery. They help software engineering leaders identify and quantify opportunities to improve software product performance by optimizing cost, operating models, technology and processes. VSMPs use AI-/machine learning (ML)-powered analytics and insights to surface constraints, detect bottlenecks and improve flow. This enables stakeholders to take actions that improve throughput and align to business priorities and objectives.