Semantic Analysis for Distributed Software Object Duplication
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Solution Overview
Problem
In distributed enterprise development environments, it is challenging to ensure that different developers do not create overlapping software objects and models, leading to inefficiencies and increased development costs due to the lack of effective comparison and analysis of newly created objects with pre-existing ones.
Innovation Solution
A method for semantically analyzing newly created object models in a distributed development system, comparing them to pre-existing models using a predetermined algorithm, and identifying semantic overlap to suggest replacements or improvements, thereby streamlining the development process and reducing duplication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If developers work independently in a distributed environment, then development productivity increases, but the risk of creating overlapping software objects increases
Solution Approach 1:
The system implements automatic feedback by comparing newly created software objects against a centralized catalog of existing objects. When semantic overlap is detected, the system provides immediate feedback to developers, alerting them to potential duplications and suggesting existing objects that could be reused instead.
Solution Approach 2:
A centralized catalog system acts as an intermediary between distributed developers and the software platform. This intermediary automatically analyzes newly created objects, compares them with existing ones, and manages the catalog, thereby coordinating development efforts across distributed teams without restricting their independence.
2Reliability
If strict development processes are enforced, then platform-level advantages are maximized, but developer flexibility and creativity are reduced
Solution Approach 1:
The system enables self-service by automatically performing semantic analysis and overlap detection without requiring manual review. Developers simply submit their objects, and the system autonomously compares them against the catalog, providing results and suggestions without interfering with the development workflow or requiring strict process enforcement.
Solution Approach 2:
The system performs preliminary analysis of software objects before they are fully integrated into the platform. By conducting semantic comparison in advance and identifying potential overlaps early in the development process, the system prevents duplication issues before they affect platform consistency, rather than imposing restrictive processes afterward.
3Measurement precision
If manual comparison of software objects is performed, then detection accuracy is limited, but system complexity is reduced
Solution Approach 1:
The system replaces manual mechanical comparison with automated semantic analysis using natural language processing and algorithmic comparison. The automated system analyzes object metadata, descriptions, and structural properties to detect semantic similarities that would be difficult or impossible to identify through manual review, significantly improving detection accuracy.
Solution Approach 2:
The system transforms the comparison task from examining entire software objects to analyzing specific parameters such as metadata, descriptions, and structural properties. By changing the parameters of analysis and focusing on key distinguishing features, the system achieves high detection accuracy while managing complexity through targeted rather than comprehensive comparison.
Data Source
AI summary
The present disclosure describes methods, systems, and computer program products for semantically analyzing modeled objects. One method includes identifying an object model created in a distributed development system for semantic analysis, where the distributed development system is associated with a software platform. The identified object model is then semantically analyzed based on a predetermined algorithm. A set of at least one pre-existing object models associated with the software platform is compared to the semantically analyzed object model, and a level of semantic overlap between the semantically analyzed object model and each of the set of at least one pre-existing object models is determined. In some instances, the predetermined algorithm may be selected based on and correspond to the object model type of the identified object model. The set of at least one pre-existing object models may comprise a subset of pre-existing object models available in a development system or associated with a software platform.