SAP Code Analysis

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.

Yes, comprehensive SAP custom code analysis can accurately identify unused, obsolete, and duplicate code within your system.

Using smartShift's Code Analysis solution, the process integrates a technical evaluation of your ABAP repository with SAP statistical usage data (such as ST03/ST03N, UPL, SUSG, or SCMON) to determine exactly which custom objects are still actively utilized. This Usage Analysis categorizes used versus unused objects and performs deep dependency analysis to understand if related underlying objects, such as Function Groups or Includes, must be retained.

To ensure the most reliable conclusions, the analysis typically requires a sufficient history of usage data—ideally up to 13 months—so that it successfully captures all critical business cycles and year-end processing events.

Why identifying obsolete code matters:

In many legacy SAP environments, it is common to find that 40% to 60% of the custom code objects are no longer used. Pinpointing this obsolete code allows organizations to:

• Reduce Technical Debt: It provides a data-driven foundation to build a safe decommissioning action plan, allowing you to cleanly retire unneeded objects.
• Lower Transformation Costs: Removing redundant or inactive code shrinks the footprint of your SAP landscape, which directly reduces the scope, testing effort, and overall cost of a future S/4HANA upgrade or Clean Core initiative.
• Improve Security: Unused code is often not maintained to the same degree as active code, meaning it can harbor hidden vulnerabilities. Decommissioning this obsolete code safely removes these risks from the system.

Yes, comprehensive SAP custom code analysis is an absolutely essential first step for any ECC to S/4HANA migration.

Because SAP S/4HANA is a complete rewrite of ECC designed specifically for the HANA in-memory database, the custom ABAP code that organizations have built over decades will require extensive changes to continue operating in the new environment. Attempting to migrate without total visibility forces organizations to make transformation decisions based on assumptions, which inevitably drives up costs, creates blind spots, and introduces massive project risk.

Conducting a thorough custom code analysis prior to migration is necessary to achieve the following:

• Accurate Sizing and Fact-Based Planning: An analysis provides a complete inventory of all custom objects and dependencies across your landscape. This replaces manual guesswork with a reliable, data-driven project plan, allowing you to accurately estimate the budget, timeline, and effort required for the S/4HANA conversion.

• Targeting Mandatory Compatibility Fixes: The analysis combines proprietary evaluation engines with SAP ABAP Test Cockpit (ATC) S/4HANA Readiness checks. This pinpoints exactly what legacy code must be remediated to align with S/4HANA's new data models, field lengths, and architecture.

• Reducing the Upgrade Scope: ASUG research indicates that having "too many customizations" in legacy instances is the top challenge organizations face during S/4HANA migrations. Analysis resolves this by identifying unused, obsolete, and duplicate code. Safely decommissioning this inactive code shrinks the physical footprint of the upgrade, which directly reduces testing efforts, lowers costs, and accelerates go-live timelines.

• Mitigating Hidden Risks: Legacy SAP systems are often filled with undocumented technical debt. A deep analysis scans for HANA-specific performance bottlenecks, obsolete constructs, and security vulnerabilities. Identifying these issues early prevents them from surfacing as costly surprises or system crashes during testing phases or post-go-live operations.

smartShift's analysis goes significantly beyond the capabilities of standard SAP tools like the ABAP Test Cockpit (ATC) or Static Code Inspector (SCI) by moving from basic pattern matching to comprehensive, algorithm-based AI.

Here is how smartShift’s approach fundamentally differs from standard code scans:

• Proprietary Meta-Model vs. Simple Pattern Matching: Standard SAP tools rely on pattern-based analysis, which often generates a massive volume of "false positives" because the tools lack deep context. For example, SAP ATC might flag every instance of a SELECT * statement as an issue, even when changing it isn't appropriate and could cause errant system behavior. Instead of simple search-and-find methods, smartShift extracts the code and translates it into a proprietary "meta-model". This creates a machine representation of the code's logical constructs, data flow, and deep inter-object dependencies, allowing the AI to understand exactly what needs to be fixed and what should be safely left alone.

• A "Transformation Parse" vs. Static Reporting: Standard analyzers simply output a list of issues or limited "Quick Fix" suggestions that human developers must then manually evaluate, prioritize, and rewrite. When smartShift performs a "Code Analysis," it is actually running the code through its Application Transformation Engine and reviewing the audit reports of a complete transformation parse. Because smartShift's engine evaluates the code against over 240 intelligent rules to see exactly how it will be transformed, it provides exact, data-driven planning rather than estimates. This is why smartShift can guarantee 100% compatibility with fixed costs and timelines.

• Multidimensional Scope: While standard tools typically focus only on mandatory S/4HANA or HANA database compatibility, smartShift’s analysis is holistic. It layers in multiple dimensions of insight that standard scans miss, including:

  • Usage and Decommissioning: It integrates SAP statistical usage data (like UPL, SCMON, or ST03N) to provide a reliable picture of code utilization, identifying exactly which unused or obsolete objects can be safely decommissioned without breaking dependent active code.

  • Landscape Comparison: It compares custom code repositories across different system tiers (such as Development and Production) to identify version discrepancies and ensure the correct code is transformed.

  • Comprehensive Optimization: Beyond basic compatibility, the analysis identifies opportunities to improve general performance, remediate security vulnerabilities, fix stability risks, and align legacy syntax with modern ABAP Cloud standards.