recent IEEE study
CAST Imaging reverse engineers and automatically ‘understands’ software systems built with any mix of 3GL, 4GL, Mobile, Web, Middleware, Framework, Database, Mainframe technologies.
It creates accurate, zoomable architecture blueprints of all database structures, code components, and their interdependencies. Down to the slightest details. You can see the transaction flows and tag the components using functional knowledge from the application users.
Refactoring millions of lines of code during cloud migrations requires a deep understanding of software architecture and its interdependencies.
Lack of documentation and legacy knowledge slows down architects and developers. This often leads to trial-and-error approaches, increasing the risk of production defects that impact the business.
CAST Imaging in action for refactoring and modernizing an application for the cloud.
Starting with the initial discovery of the AS-IS state of the application, from the different layers and technologies used, down to the tiniest details of components and their dependencies.
Continuing with the automatic discovery of transactions for faster isolation of impacted components, enabling precise cost estimation of changes, defining test cases, and reducing side effects.
Automatically understand the technology stack, as well as all interdependencies between code components, application layers, frameworks, technologies, databases. Identify obsolete technologies and frameworks that are good candidates for decommissioning and see inside the software system with MRI-like precision.
Automatically identify all components involved in the display and/or the processing of the data stored into data repositories, such as tables and flat files, avoiding wrong turns in de-coupling and refactoring.
Automatically identify API routes with tight dependencies between them (hard to separate) and flows with low dependencies (to be considered for separation), a necessary consideration for ensuring scalability and deployment flexibility of the modernized application.
Quickly identify the artefacts (horizontal layer) contributing to functional communities. Automatically identify communities tightly coupled and with low modularity (hard to separate) and communities with low coupling that could be isolated with minimal effort.
Find the most practical (low effort) Microservices candidates. Identify core components (vertical layer) supporting several functions, a good starting point for microservices.
Understand and visualize in real time the impact of newly developed or changed code to the fundamental architecture, its adherence with the intended TO-BE design, and its effects on the structural quality of the entire software system.
You can tag modules discovered by CAST Imaging according to their functional and/or technical relevance. For example, you can tag all modules that comprise a transaction and all modules slated for de-coupling and immediately see the intersection.
Minimize business interruptions by migrating a cluster of applications together, based on the dependencies between them. When required, investigate the impact of breaking off the application from its cluster.
Ramesh Chandrasekaran
COO, LTI Nordics
David Ruggiero
Modernization & Cloud Advisory Leader
Kyndryl
Mario Contreras
Senior Architect
Microsoft
Doug Criddle
Sr. Director of Engineering
PMMC