Ontology-Based Software Modernization Assessment Engine
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Solution Overview
Problem
Existing software modernization processes are labor-intensive, time-consuming, and error-prone, often relying on personal experience and external factors, making it difficult to make objective and consistent modernization assessments and recommendations for legacy applications.
Innovation Solution
A cloud provider network's modernization assessment service maintains a knowledge base with modernization ontologies and data models to automate software modernization processes, providing objective and consistent recommendations based on tool capabilities, cost information, and best practices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual software modernization processes are used, then flexibility in handling complex legacy applications is maintained, but labor intensity and time consumption increase significantly
Solution Approach 1:
An automated assessment engine serves as an intermediary between legacy applications and modernization targets. The engine analyzes application code, dependencies, and architecture to generate modernization recommendations, bridging the gap between manual analysis and automated transformation while maintaining flexibility through configurable assessment criteria and multiple modernization strategy options.
2Measurement precision
If expert knowledge is used for modernization assessments, then accuracy of recommendations is improved, but consistency across different assessments deteriorates due to personal experience variations
Solution Approach 1:
The system transforms subjective expert knowledge into objective, measurable parameters. Assessment criteria are defined as configurable parameters with specific weights and thresholds, allowing the same assessment logic to be applied consistently across different applications while maintaining the depth and accuracy of expert evaluation through adjustable parameter settings.
3Reliability
If comprehensive application analysis is performed, then modernization recommendation quality is improved, but assessment time and computational resources increase
Solution Approach 1:
The assessment process is segmented into multiple independent analysis modules, each focusing on specific aspects such as code quality, dependency analysis, architecture evaluation, and security assessment. This allows comprehensive analysis to be performed in parallel, improving recommendation quality while reducing total assessment time through concurrent processing of different application dimensions.
Data Source
AI summary
Techniques are described for enabling a software modernization assessment service of a cloud provider network to maintain a modernization knowledge base and to use the knowledge base to generate modernization recommendations for users' software applications. A modernization knowledge base comprises one or more modernization ontologies, where a modernization ontology defines concepts and relationships used to describe modernization tool capabilities and limitations, modernization strategies, etc. The modernization assessment service uses the modernization knowledge base to automate various software modernization processes including, for example, providing modernization recommendations for software applications (e.g., applications identified by users as candidates for modernization) and generating modernization assessment reports. A modernization knowledge base, including an ontology understood by a modernization assessment engine, can be readily updated to account for new modernization strategy information, modernization tool information, and modernization process and tool constraints, without necessitating changes to static definitions of such information defined by a modernization assessment service.