Automated SAP Custom Code Analysis & Remediation

SAP Custom Code Analysis is the process of gaining complete visibility into your custom ABAP codebase before transformation. smartShift Code Analysis scans 100% of custom code to uncover what exists, identify risks, and assess readiness for S/4HANA modernization.

Unlike surface-level scans, smartShift delivers full-spectrum insight into custom code volume, compatibility issues, performance and stability risks, security concerns, and remediation scope. This clarity enables organizations to plan transformation accurately, reduce risk, and modernize with confidence.

The cost of SAP custom code analysis depends on the size and complexity of your custom codebase, including the number of objects and overall lines of code. Traditional, manual assessments are often expensive due to the time and effort required.
Automated analysis significantly reduces cost and effort by scanning large codebases quickly and consistently. Automated analysis delivers clear visibility and accurate remediation insight, enabling organizations to plan transformation more confidently and reduce uncertainty.

With automation, SAP custom code analysis can be completed far faster than manual approaches. Even for large enterprise environments with millions of lines of custom code, smartShift Code Analysis typically delivers results in days rather than months.

Completing analysis early gives teams immediate visibility, reduces transformation risk, and enables more accurate planning for S/4HANA upgrades or optimization initiatives.

SAP provides standard tools such as ABAP Test Cockpit (ATC), SPAU, and SPDD to help identify and review custom-developed objects. These tools offer useful technical checks but typically provide only partial visibility and fragmented insight.

smartShift Code Analysis goes further by scanning the entire custom codebase at scale. Using patented automation and 250+ expert rules, it delivers a comprehensive view of custom code volume, risk areas, remediation requirements, and decommissioning potential—enabling data-driven decisions about what to fix, modernize, or retire before transformation.