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Evidence Types for ISO 26262 and ASPICE

Evidence CategoryExamplesStorage LocationAuditor Views It As
Work productsHARA report, SW architecture, FMEA, test spec, test reportDMS (Windchill, SharePoint, Polarion)Primary compliance claim evidence
Review recordsReview meeting minutes, participant list, issues raised, resolution datesDMS or JIRA review ticketsProof that independent review occurred
Tool qualification recordsVendor TQK, tool usage history, validation test resultsDMS + CM baselineProof that tool outputs can be trusted
Independence confirmationAssessor CV, independence declaration, company affiliationDMS + Safety Plan appendixProof that assessor meets independence level requirement
Baseline recordsGit commit hash, build timestamp, configuration manifestCM system (Git + Jenkins)Proof that delivered binary = reviewed + tested code

Evidence Retention Requirements

StandardMinimum Retention PeriodWhat Must Be Retained
ISO 26262 Part 2.6.4.10Vehicle service life + 10 years minimumAll safety-relevant work products and evidence records
ISO/SAE 21434 Clause 8.3Vehicle service lifeTARA, security requirements, incident records, CSMS documentation
IATF 16949 Section 7.5Customer-specified + minimum 15 years for safety partsQuality records, PPAP documents, control plans, FMEA
UNECE R155Life of CSMS certification + per authority requirementCSMS documentation, annual assessment reports, incident records

⚠️ Broken Evidence Links Are Audit Critical

During an FSA or ASPICE assessment, the compliance engineer presents the evidence via the compliance matrix. If the assessor clicks an evidence link and gets a 404 or 'Access Denied' error, they classify the associated requirement as having no evidence — equivalent to the work not being done. Run a full link-check of the entire compliance matrix at least four weeks before any assessment and immediately fix all broken links. This single action prevents more findings than any other pre-assessment activity.

Git + JIRA as Audit Trail

Pythonaudit_trail_check.py
#!/usr/bin/env python3
# Verify ASPICE SUP.10 audit trail: every code change has approved CR in JIRA

import subprocess, json, requests

JIRA_BASE = "https://jira.company.com/rest/api/2"
JIRA_AUTH = ("automation_user", "api_token_here")

def get_commits_since_baseline(repo_path, baseline_tag):
    result = subprocess.run(
        ["git", "log", f"{baseline_tag}..HEAD", "--pretty=%H|%s|%ae"],
        cwd=repo_path, capture_output=True, text=True
    )
    return [line.split("|") for line in result.stdout.strip().split("\n") if line]

def check_cr_exists(commit_message):
    # Expect commit message format: "CR-XXXX: description"
    if not commit_message.startswith("CR-"):
        return None, "No CR reference in commit message"
    cr_id = commit_message.split(":")[0]
    response = requests.get(f"{JIRA_BASE}/issue/{cr_id}", auth=JIRA_AUTH)
    if response.status_code == 200:
        issue = response.json()
        status = issue["fields"]["status"]["name"]
        approved = status in ["Approved", "Implemented", "Verified", "Closed"]
        return cr_id, "Approved" if approved else f"Not approved (status: {status})"
    return cr_id, f"CR not found in JIRA (HTTP {response.status_code})"

print("ASPICE SUP.10 Audit Trail Check:")
commits = get_commits_since_baseline("repos/app_sw", "Release_EPS_v3.1")
for commit_hash, message, author in commits:
    cr_id, status = check_cr_exists(message)
    icon = "OK" if status == "Approved" else "FAIL"
    print(f"  [{icon}] {commit_hash[:8]} | {message[:50]} | CR: {cr_id} | {status}")

Pre-Assessment Evidence Completeness Check

CheckTimingAction if Failed
All matrix rows have Evidence Ref populated4 weeks beforeAdd evidence link or escalate to work product owner
All evidence links return 200 (not 404)4 weeks beforeFix DMS path or upload missing document
No 'Unknown' status rows remain4 weeks beforeClassify as N/A with justification or complete the work
All review records include participant list4 weeks beforeRetrieve sign-in sheets; if missing, re-run the review
Tool qualification records cover actual version used4 weeks beforeIf version differs from qualified version, run supplementary qualification
Independence declarations signed by assessor1 week beforeObtain signed declaration; check assessor meets required I-level

Summary

Evidence management is a continuous activity, not a pre-audit scramble. The DMS stores work products with audit trails (who created, reviewed, approved, when); Git provides code change history with CR references; JIRA provides the CR approval audit trail. Combined, these three tools cover the majority of ASPICE SUP.8 and SUP.10 evidence requirements automatically — if the project has used them consistently throughout development. The pre-assessment check four weeks before assessment gives time to fix gaps before the assessor arrives.

🔬 Deep Dive — Core Concepts Expanded

This section builds on the foundational concepts covered above with additional technical depth, edge cases, and configuration nuances that separate competent engineers from experts. When working on production ECU projects, the details covered here are the ones most commonly responsible for integration delays and late-phase defects.

Key principles to reinforce:

  • Configuration over coding: In AUTOSAR and automotive middleware environments, correctness is largely determined by ARXML configuration, not application code. A correctly implemented algorithm can produce wrong results due to a single misconfigured parameter.
  • Traceability as a first-class concern: Every configuration decision should be traceable to a requirement, safety goal, or architecture decision. Undocumented configuration choices are a common source of regression defects when ECUs are updated.
  • Cross-module dependencies: In tightly integrated automotive software stacks, changing one module's configuration often requires corresponding updates in dependent modules. Always perform a dependency impact analysis before submitting configuration changes.

🏭 How This Topic Appears in Production Projects

  • Project integration phase: The concepts covered in this lesson are most commonly encountered during ECU integration testing — when multiple software components from different teams are combined for the first time. Issues that were invisible in unit tests frequently surface at this stage.
  • Supplier/OEM interface: This is a topic that frequently appears in technical discussions between Tier-1 ECU suppliers and OEM system integrators. Engineers who can speak fluently about these details earn credibility and are often brought into critical design review meetings.
  • Automotive tool ecosystem: Vector CANoe/CANalyzer, dSPACE tools, and ETAS INCA are the standard tools used to validate and measure the correct behaviour of the systems described in this lesson. Familiarity with these tools alongside the conceptual knowledge dramatically accelerates debugging in real projects.

⚠️ Common Mistakes and How to Avoid Them

  1. Assuming default configuration is correct: Automotive software tools ship with default configurations that are designed to compile and link, not to meet project-specific requirements. Every configuration parameter needs to be consciously set. 'It compiled' is not the same as 'it is correctly configured'.
  2. Skipping documentation of configuration rationale: In a 3-year ECU project with team turnover, undocumented configuration choices become tribal knowledge that disappears when engineers leave. Document why a parameter is set to a specific value, not just what it is set to.
  3. Testing only the happy path: Automotive ECUs must behave correctly under fault conditions, voltage variations, and communication errors. Always test the error handling paths as rigorously as the nominal operation. Many production escapes originate in untested error branches.
  4. Version mismatches between teams: In a multi-team project, the BSW team, SWC team, and system integration team may use different versions of the same ARXML file. Version management of all ARXML files in a shared repository is mandatory, not optional.

📊 Industry Note

Engineers who master both the theoretical concepts and the practical toolchain skills covered in this course are among the most sought-after professionals in the automotive software industry. The combination of AUTOSAR standards knowledge, safety engineering understanding, and hands-on configuration experience commands premium salaries at OEMs and Tier-1 suppliers globally.

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