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.
Gartner defines the application programming interface (API) management market as the market for software to manage, govern and secure APIs. Organizations use APIs to modernize their architectures; APIs provide access to systems, services, partners and data services. API management software enables organizations to plan, deploy, secure, operate, version control and retire APIs, regardless of their size, region or industry.
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.
Reviews for 'Application Development, Integration and Management - Others'
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.
Continuous configuration automation (CCA) tools enable the description of configuration states, customization of settings, software binaries deployment, and configuration state reporting. These tools are a programmable framework on which configuration and provisioning tasks can be codified, versioned and managed like any other piece of application code — frequently known as 'infrastructure as code.' Many of the tools in the market provide a repository to store and manage configuration content but can be integrated with or use (code) revision control systems in use by application development teams. System administrators and application developers use CCA tools to programmatically manage the configurations of applications, servers, middleware, databases and other IT infrastructure for both on-premises and cloud data centre environments. Most CCA tools have both an open-source and commercial offering.
Data masking is based on the premise that sensitive data can be transformed into less sensitive but still useful data. This is necessary to satisfy application testing use cases that require representative and coherent data, as well as analytics that involve the use of aggregate data for scoring, model building and statistical reporting. The market for data protection, DM included, continues to evolve with technologies designed to redact, anonymize, pseudonymize, or in some way deidentify data in order to protect it against confidentiality or privacy risk.
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.
Elevating Test Data Management for DevOps is the process of providing DevOps teams with test data to evaluate the performance, and functionality of applications. This process typically includes copying production data, anonymization or masking, and, sometimes, virtualization. In some cases, specialized techniques, such as synthetic data generation, are appropriate. With that, it applies data masking techniques to protect sensitive data, including PII, PHI, PCI, and other corporate confidential information, from fraud and unauthorized access while preserving contextual meaning.
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
Load Testing Tools determine the performance of a system, software product, or software application under real-life based load conditions and resource utilization levels. The goal of load testing is to improve performance bottlenecks and to ensure stability and smooth functioning of software application before deployment. Through specialized testing software,various scenarios are simulated to test the system’s behavior under different load conditions. The software places a simulated “load” or demand from multiple sources on applications to ensure it remains stable during operation and peak load. It enables test analysts to evaluate application performance and maximize the operating capacity of the application.
Mobile testing services are different from traditional application testing with additional complexity, such as the testing of multiplatform, networks, multiple operating systems (OSs) as well as different devices. These services are needed to test the function, performance, compatibility and other details of a mobile application, using both manual and automated tests. While the testing this market refers to is that of applications residing on mobile handheld devices, the testing must also take into account the data being gathered or supplied to embedded devices and sensors with the Internet of Things (IoT) becoming more prominent. User experience is key in mobility by creating unique requirements for the testing process. With digital business and customer experience, applications and data are increasingly available and visible to external constituents — especially customers. Thus, quality, reliability, security, and adaptability needed for external use of systems are far beyond internal usage.
The structured data archiving and application retirement market is identified by an array of technology solutions that manage the life cycle of application-generated data and accommodate corporate and regulatory compliance requirements. Application-generated data is inclusive of databases and related unstructured data. SDA solutions focus on improving the storage efficiency of data generated by on-premises and cloud-based applications and orchestrating the retirement of legacy application data and their infrastructure. The SDA market includes solutions that can be deployed on-premises, and on private and public infrastructure, and includes managed services offerings such as SaaS or PaaS.