Autocompletion Framework for ALM Entity Graph Traversal
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Solution Overview
Problem
The increasing complexity of enterprise applications in application lifecycle management (ALM) makes it time-consuming and error-prone for users to manually identify the optimal set of entities and relations needed to complete actions, often including unnecessary or missing components.
Innovation Solution
A generic, extensible, and configurable framework for ALM graph traversal that automatically identifies and ascertains the necessary set of entities and relations required to complete actions, using a processor-based autocompletion method that traverses ALM models and graphs, applying user-configurable rules to ensure completeness and coherence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users manually identify entities and relations needed to complete actions in ALM, then they can ensure completeness and accuracy, but the process becomes time-consuming and error-prone
Solution Approach 1:
The system performs autocompletion of ALM entities automatically without requiring manual user intervention. The framework traverses the ALM graph and self-determines the necessary entities and relations based on configured rules, eliminating the time-consuming manual identification process while maintaining accuracy through systematic rule-based analysis.
Solution Approach 2:
The patent replaces the manual mechanical process of identifying ALM entities with an automated computational system. The framework uses processor-based autocompletion methods that traverse the ALM graph and apply rules automatically, substituting human manual effort with machine-based systematic analysis that is both faster and more reliable.
2Reliability
If users manually identify all entities and relations for actions, then completeness can be achieved, but unnecessary or missing components are often included
Solution Approach 1:
The framework employs feedback mechanisms where the autocompletion process continuously evaluates the ALM graph traversal results against configured rules. The system adjusts and refines the identified entity set based on rule-based validation, ensuring that only necessary entities and relations are included while excluding unnecessary components through iterative rule application and verification.
Solution Approach 2:
The patent utilizes configurable parameters and rules that can be adjusted to control the autocompletion behavior. By changing parameters such as rule configurations and traversal criteria, the system can optimize the entity set identification to achieve the right balance between completeness and necessity, adapting to different ALM action requirements without manual intervention.
3Adaptability or versatility
If a generic and extensible framework is used for ALM graph traversal, then adaptability to different actions is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal autocompletion framework that can handle multiple different ALM actions through a single systematic approach. The framework uses configurable rules and graph traversal mechanisms that can be adapted to various actions (such as baseline capture, project copying, filtered set creation) without requiring separate manual processes for each action, achieving multi-functionality through rule-based flexibility.
Data Source
AI summary
Example methods, apparatus and articles of manufacture to autocomplete application lifecycle management (ALM) entities are disclosed. A disclosed example method includes obtaining an action associated with an ALM entity, and tracing an ALM repository starting with the ALM entity to automatically identify a connected set of entities and relationships that complete the action.