Expression Evaluation Infrastructure for Dynamic Context Adaptation
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Solution Overview
Problem
Software applications often require frequent recoding to adapt to changing requirements and regional variations, leading to inefficiencies in development and customization.
Innovation Solution
A method and system that utilize a contextual mapping data structure to adapt initial expressions to user contexts, generating contextualized expressions without re-coding, and apply validation rules to ensure compliance, triggering alerts for violations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If software applications are hardcoded to comply with specific requirements, then implementation is straightforward initially, but re-coding is inevitable as requirements change and customization arises
Solution Approach 1:
The system transforms static hardcoded requirements into dynamic expressions that can be automatically adapted to different contexts and requirements. The expression evaluator dynamically generates contextualized expressions based on user inputs and contexts, allowing the software to adapt to changing requirements without re-coding.
Solution Approach 2:
The system changes parameters by allowing users to input different expressions and contexts rather than modifying the core software code. The contextual mapping data structure maps initial expressions to contextualized expressions based on user contexts, enabling parameter changes through configuration rather than re-coding.
2Adaptability or versatility
If re-coding is performed to adapt to changing requirements, then compliance with new requirements is achieved, but time and resources are wasted
Solution Approach 1:
The system creates copies of expressions rather than modifying the original software code. The expression evaluator generates contextualized expressions as copies adapted to specific user contexts, allowing rapid adaptation to new requirements without time-consuming re-coding of the core application.
Solution Approach 2:
The system performs preliminary action by pre-defining the expression evaluation infrastructure and contextual mapping data structure. This preliminary setup enables rapid adaptation to changing requirements through automated expression generation rather than requiring time-consuming re-coding operations.
3Adaptability or versatility
If customization is performed for different users and regions, then user-specific requirements are met, but existing code cannot be reused
Solution Approach 1:
The system segments the customization process into separate components: the core expression evaluation infrastructure remains reusable, while contextualized expressions are generated as separate, user-specific segments. The contextual mapping data structure stores these segmented contextualized expressions, allowing existing code to be reused while meeting user-specific requirements.
Solution Approach 2:
The expression evaluation infrastructure provides universality by handling multiple user contexts and requirements through a single reusable system. The same core infrastructure can serve different users and regions by generating appropriate contextualized expressions, eliminating the need to discard existing code for each customization.
4Reliability
If validation rules are applied to ensure compliance, then accuracy and reliability are improved, but system complexity increases
Solution Approach 1:
The system introduces an intermediary layer in the form of validation rules that mediate between the expression evaluation and compliance requirements. These validation rules act as a simple intermediary mechanism that ensures compliance without adding significant complexity to the overall system, as they operate independently of the core expression evaluation infrastructure.
Data Source
AI summary
A method may include obtaining, from a user, an initial expression including an operator and an input extracted from a data source. The operator may be applied to the input. The method may further include obtaining, using a contextual mapping data structure, a contextualized expression including the input and the data source. The contextual mapping data structure may include a context corresponding to the user. The method may further include generating a result by evaluating the contextualized expression, obtaining, using a rule table, a validation rule corresponding to the contextualized expression, and triggering an alert in response to applying the validation rule to the result.