Automated Source Code Review for Data Store Access
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Solution Overview
Problem
Large-scale data stores face inefficiencies due to the difficulty in reviewing and ensuring proper performance of data store access source code, particularly with multiple types of source code being written by different groups, leading to inconsistencies and delays in deployment.
Innovation Solution
A computer-implemented automated review method that checks data store access source code for compliance with guidelines across various levels, including SQL, DAO, and configuration files, halting deployment if issues are found to ensure proper operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual source code review is performed by data store managers and IT personnel, then code quality and performance can be ensured, but deployment time increases and productivity decreases
Solution Approach 1:
The system enables self-service automated code review where the review process is performed automatically without requiring manual intervention from data store managers or IT personnel. The automated reviewer executes pre-defined review criteria against the source code, eliminating the need for human reviewers while maintaining code quality standards.
Solution Approach 2:
The patent replaces the mechanical manual review process with an automated computer-based review system. The automated reviewer uses algorithms and pre-defined criteria to evaluate source code, substituting human manual inspection with automated computational analysis, thereby eliminating delays while ensuring consistent code quality.
2Ease of manufacture
If multiple groups write different types of source code files, then specialized expertise is utilized, but inconsistencies and errors increase
Solution Approach 1:
The automated reviewer performs multiple review functions across different source code file types (SQL, DAO, configuration files) using a single unified system. It applies appropriate review criteria based on the file type, enabling consistent quality control across diverse codebases written by different specialized groups without requiring separate review processes for each type.
Solution Approach 2:
The system applies different review criteria and standards tailored to each source code file type (SQL files, DAO files, configuration files). Each file type receives customized review rules appropriate to its specific requirements, ensuring that specialized code written by different groups meets the appropriate quality standards for its category while maintaining overall system consistency.
3Reliability
If thorough source code review is conducted to ensure proper performance, then operational reliability improves, but deployment delays increase
Solution Approach 1:
The system performs code review actions in advance before deployment is attempted. By executing the automated review process as part of the build or pre-deployment workflow, potential issues are identified and can be addressed before they cause operational problems, eliminating the need for post-deployment fixes and reducing overall deployment time.
Solution Approach 2:
The automated review process quickly evaluates code against pre-defined criteria without the time-consuming nature of manual review. The system rapidly analyzes source code files, identifies issues, and provides feedback in a streamlined manner that maintains thoroughness while significantly reducing the time required compared to manual inspection processes.
Data Source
AI summary
A computer-implemented automated review method for source code files seeking to access a data store comprises the steps of receiving a request to review data store access source code; determining computer files which include the data access source code; examining structured query language (SQL) source code files and determining compliance with non-syntax-related guidelines; examining data access object (DAO) source code files and determining compliance with guidelines for invoking SQL components within Java source code; examining configuration source code files and determining compliance with data store connection and object definition guidelines; examining configuration source code files and determining compliance with transaction-related guidelines; examining configuration source code files and determining compliance with datasource configuration guidelines; and issuing a halt signal if any of the guidelines are not followed.


