AI-Powered Code Review for ERP Customizations
ERP customizations are the primary source of upgrade failures, security vulnerabilities, and maintenance burden in enterprise systems. The average mid-market ERP has 50-200 custom objects including forms, reports, scripts, and integrations. AI code review agents analyze these customizations against ERP SDK standards, identify upgrade-breaking patterns, detect security vulnerabilities, and assess technical debt. Organizations deploying AI code review report 65% reduction in post-upgrade defects and 40% faster customization assessment during upgrade planning.
Customization Quality and Standards Compliance
AI code review agents analyze custom ERP code against vendor SDK standards, naming conventions, and architectural patterns. For SyteLine, the agent reviews IDO extensions, form scripts, and event handlers against Infor's Mongoose framework standards. For LN, it checks 4GL customizations and UI personalizations. The agent identifies anti-patterns like direct SQL manipulation bypassing the ORM layer, hardcoded values that should reference configuration, and missing error handling in transaction-critical code.
- Analyze custom code against ERP vendor SDK standards checking API usage patterns, naming conventions, and framework compliance
- Detect anti-patterns: direct SQL bypassing ORM layers, hardcoded connection strings, missing transaction rollback handling, and tight coupling
- Identify code duplication across customizations where shared libraries or framework extensions would reduce maintenance burden
- Assess code documentation completeness including inline comments, change logs, and functional specification references
- Generate technical debt scores per customization combining complexity metrics, standard violations, and maintenance risk indicators
Upgrade Impact and Compatibility Analysis
Every ERP upgrade risks breaking customizations that depend on internal APIs, database schema, or UI framework versions. AI agents perform static analysis on custom code to identify dependencies on deprecated APIs, internal methods not part of the public SDK, and database objects that may change in target versions. The agent cross-references customization dependencies against release notes and breaking change documentation to produce upgrade risk assessments with specific remediation guidance.
- Map customization dependencies on ERP internal APIs, database views, and UI framework components to identify upgrade-fragile code
- Cross-reference dependencies against target version release notes and breaking change documentation for proactive risk identification
- Generate upgrade impact scores per customization: low (no changes needed), medium (minor adjustments), high (significant rework required)
- Produce migration path recommendations for high-risk customizations including alternative implementation approaches using supported APIs
Security Vulnerability Detection in Custom Code
Custom ERP code frequently contains security vulnerabilities because ERP developers often lack security training and ERP SDKs do not enforce secure coding patterns. AI security review agents scan for SQL injection (especially in custom report queries), cross-site scripting in web customizations, hardcoded credentials, insufficient input validation, and insecure data handling. SAST (Static Application Security Testing) models trained on ERP-specific vulnerability patterns detect issues that generic security scanners miss.
- Scan for SQL injection vulnerabilities in custom queries, reports, and data access layers, especially concatenated SQL string patterns
- Detect hardcoded credentials, API keys, and connection strings in custom code that should use encrypted configuration stores
- Identify insufficient input validation on user-facing customizations where unvalidated input could cause data corruption or injection
- Review custom authentication and authorization code for bypass vulnerabilities and missing access control checks
Secure and future-proof your ERP customizations with AI code review. Contact Netray today.
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