Tool 15 · SAP Delivery Risk

Test Coverage
Intelligence

Upload your test register and requirements. AI maps coverage, detects gaps, flags duplicates, and generates missing test scenarios — before go-live risk becomes go-live failure.

Models: Semantic Similarity Cosine Distance XGBoost Risk LLM Suggestions
94%
Mapping Accuracy
2 min
Full Analysis
100+
Test Patterns
Coverage by Module
FI/CO
88%
SD
72%
MM/WM
61%
PP
44%
HCM
33%
Risk Summary
✓ 47 Covered ✗ 18 Gaps ⚠ 9 Duplicates ✦ 23 Suggested
WRICEF coverage: 61% · Critical: 3 untested
Tool Workspace
Coverage Analysis Engine
Upload your test case register and requirements list. Supports Excel (.xlsx), CSV, Jira export, or SAP Cloud ALM export. For a quick demo, use the "Load Sample Data" button.
Upload Files
Test Cases File
Drop test case file here
Excel · CSV · Jira export · Cloud ALM export
Requirements File (optional)
Drop requirements file here
Requirements register · WRICEF log · SoW scope
Analysis Configuration
Analysis Results
Coverage Report
Analysis complete. Review coverage scores, gaps, duplicates, and AI-generated test suggestions below.
Requirement → Test Case Matrix
Req ID Requirement Module Test Cases Coverage Criticality
Gap Detection0 gaps

No gaps detected yet

Duplicate Detection0 duplicates

No duplicates detected yet

WRICEF Object Coverage

WRICEF analysis will appear here

AI-Generated Test Suggestions0 suggestions
Missing test scenarios identified by AI analysis of your requirements, module patterns, and coverage gaps. Each suggestion includes a recommended test approach and priority level.

AI suggestions will appear after analysis

Coverage Dashboard
Visual Coverage Analysis
Interactive coverage breakdown by SAP module, process area, test type, and criticality.
Coverage % by SAP Module
Tests by Criticality
Test Distribution by Phase
WRICEF Object Coverage
Under the Hood
Algorithms & Intelligence
Test Coverage Intelligence combines semantic AI with SAP-domain rules to deliver coverage analysis that generic tools cannot replicate.
Semantic Requirement Mapping
Sentence-transformer embeddings map each test case to the closest requirements using cosine similarity. Unlike keyword matching, this catches semantic overlaps across differently-worded items — critical when requirements use business language but test cases use technical language.
Gap Detection Engine
Requirements with zero mapped test cases are flagged as hard gaps. Requirements with only one test case covering multiple conditions are flagged as soft gaps. A rule-based layer cross-checks SAP-specific patterns: payment runs, authorisation checks, period-end processes, and interface triggers must each have dedicated test cases.
Duplicate Detection
Pairwise cosine similarity across all test case descriptions detects functionally equivalent tests masquerading as separate entries. Threshold-based — configurable from 70% to 90% similarity. Duplicate pairs are ranked by similarity score and presented for SME review before deletion.
XGBoost Criticality Scoring
Each requirement is scored High / Medium / Low business risk using an XGBoost classifier trained on 340+ SAP project post-mortem outcomes. Features include: module type, process area, integration point count, custom object dependency, and ACTIVATE phase. SHAP attribution explains every score.
AI Test Suggestion Engine
For each detected gap, the engine generates missing test scenario suggestions using a library of 100+ SAP test patterns covering: happy path, negative/error path, boundary conditions, authorisation, interface trigger, period-end, and mass data scenarios. Suggestions are prioritised by criticality score.
WRICEF Object Coverage
Custom objects (RICEFW) are matched to test cases to determine whether each custom development has functional test coverage. The engine detects: Reports without output validation tests, Interfaces without trigger and error-handling tests, Conversions without data quality and volume tests, and Workflows without approval path tests.