Automated Source Code Scanning for Missing Object Attributes
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Solution Overview
Problem
Current software development processes lack automated means for identifying and generating alerts for missing object attributes during code development, leading to manual, labor-intensive, and time-consuming processes that delay test automation and extend test cycles.
Innovation Solution
A system and method that scans source code to identify missing hardware and software parameters, converts them into configurable digital bins, determines an automation parameter, generates corrective actions, and automatically generates software by executing these actions to enhance the automation quotient (AQ) of user interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual processes are used to identify missing object attributes during code development, then developers can detect and address issues, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The system enables self-service by automatically scanning source code to identify missing object attributes without requiring manual developer intervention. The automated scanning mechanism detects missing attributes, generates alerts, and suggests corrective actions, allowing the development system to serve itself rather than relying on human developers to manually identify and fix these issues during the development process.
Solution Approach 2:
The system performs preliminary action by conducting automated scans during the code development phase itself, before the testing phase begins. By identifying and alerting developers to missing object attributes early in the development process, the system prevents these issues from carrying into later testing stages, thereby reducing overall test cycle duration while maintaining detection accuracy.
2Productivity
If automated scanning is implemented to identify missing parameters, then detection efficiency improves, but system complexity increases
Solution Approach 1:
The system achieves universality by creating a multi-functional automated scanning platform that can detect multiple types of issues (missing object attributes, hardware parameters, software parameters) across different codebases. This single unified system performs what would otherwise require multiple separate tools and manual processes, improving detection efficiency while managing system complexity through consolidation rather than proliferation of separate systems.
Solution Approach 2:
The system introduces an intermediary automated scanning layer between the source code and the developers. This intermediary automatically analyzes code, identifies missing parameters, and communicates findings to developers through alerts and suggestions. By placing this intelligent intermediary in the workflow, the system handles the complexity of automated analysis while developers receive simplified, actionable information, thus improving productivity without proportionally increasing the complexity developers must manage.
3Ease of operation
If manual identification of missing attributes is performed, then developers have control over the process, but automation quotient remains low
Solution Approach 1:
The system implements feedback by automatically scanning code, identifying missing object attributes, and providing structured alerts with suggested corrective actions to developers. This feedback loop maintains developer control as they review and act on the suggestions, while simultaneously increasing automation quotient through the automated detection and recommendation processes. The feedback mechanism bridges manual control with automated efficiency by presenting processed information for developer decision-making.
Solution Approach 2:
The system enables self-service through automated scanning and alert generation, reducing the manual effort developers must invest in identifying missing attributes. While developers retain control over the final decisions and corrective actions, the automated system handles the labor-intensive detection and analysis work, thereby increasing the automation quotient without completely removing developer involvement or control from the process.
Data Source
AI summary
A method, system, and computer program product for implementing automated software application generation is provided. The method includes scanning source code for identifying missing elements of hardware and software parameters associated with functional operation of software for development. The hardware and software parameters are analyzed and converted into configurable digital bins. An automation parameter is generated. The automation parameter is associated with portions of the software configured for automatic development and generation. Corrective actions associated with automating development of the software are generated based on the automation parameter and it is determined that the automation parameter is within a specified range of the portions. The corrective actions are executed with respect to development of the software and the software is generated.