Technical Due Diligence Checklist for Software Projects

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Technical due diligence separates opinion from evidence. Whether you are acquiring a company, investing in a startup, evaluating a vendor, or auditing an internal project, this checklist provides a systematic framework for assessing the technical foundation. Each section includes specific items to evaluate and scoring guidance to quantify risk.

Area 1: Code Quality

Code quality is the most direct indicator of engineering discipline. Clean, well-structured code is easier to maintain, extend, and debug. Poor code quality signals accumulated shortcuts that will compound over time.

Automated analysis

• Run static analysis tools (SonarQube, ESLint, Pylint) — what is the overall quality score?
• Measure code coverage — what percentage of code is covered by automated tests? (Benchmark: 60-80% is good, below 40% is a red flag)
• Check cyclomatic complexity — high complexity indicates code that is difficult to understand and test
• Scan for code duplication — above 10% duplication suggests copy-paste development patterns
• Run dependency vulnerability scan — how many known CVEs exist in the dependency tree?

Manual code review

• Review naming conventions — are variables, functions, and classes named clearly and consistently?
• Assess separation of concerns — is business logic separated from infrastructure, presentation, and data access?
• Check error handling — are errors caught, logged, and handled gracefully, or do they propagate silently?
• Evaluate coding standards — is there a consistent style, or does each file look like it was written by a different person?
• Review recent commits — are commit messages meaningful? Do pull requests have reviews? Is the git history clean or chaotic?

Technical debt assessment

• Identify TODO/FIXME/HACK comments — count and categorize them
• Assess technological debt backlog — is there a documented list of known issues? Is it growing or shrinking?
• Evaluate code age distribution — what percentage of code has not been modified in 2+ years?
• Check for dead code — unused functions, unreachable branches, commented-out blocks

Scoring guide:

• Green (low risk): Coverage > 70%, no critical vulnerabilities, consistent style, manageable tech debt
• Yellow (moderate risk): Coverage 40-70%, some vulnerabilities, inconsistent style, growing tech debt
• Red (high risk): Coverage < 40%, critical vulnerabilities, no standards, overwhelming tech debt

Area 2: Architecture

Architecture determines how well the system can evolve, scale, and integrate. A sound architecture makes changes cheap. A poor architecture makes every change expensive and risky.

System design

• Document the high-level architecture — can the team explain it clearly? Does a diagram exist?
• Identify architectural pattern — monolith, microservices, modular monolith, event-driven? Is the choice appropriate for the system’s complexity?
• Assess coupling — how tightly are components connected? Can one component be changed without affecting others?
• Evaluate cohesion — does each component have a single, clear responsibility?
• Check for architectural drift — does the actual code match the documented architecture?

Data architecture

• Document the data model — is it normalized, documented, and consistent?
• Assess database choice — is the database appropriate for the data patterns (relational vs NoSQL vs time-series)?
• Check data migration strategy — is there a schema migration process? Are migrations version-controlled?
• Evaluate data integrity — are referential constraints enforced? Is there data validation at the application level?
• Assess backup and recovery — are backups automated, tested, and recoverable within defined RTO?

Integration architecture

• Map external integrations — APIs, third-party services, message queues, file transfers
• Assess integration resilience — what happens when an external service is slow or unavailable? (Circuit breakers, retries, fallbacks)
• Check API versioning — how are breaking changes managed for consumers?
• Evaluate message handling — are messages processed exactly-once or at-least-once? Is idempotency implemented?

Scoring guide:

• Green: Clear architecture, appropriate patterns, low coupling, documented data model
• Yellow: Partial documentation, some tight coupling, data model inconsistencies
• Red: No architecture documentation, monolith with tight coupling, undocumented data model

Area 3: Security

Security assessment identifies vulnerabilities that could lead to data breaches, compliance violations, or operational disruption.

Application security

• Run SAST scan — how many critical and high vulnerabilities exist?
• Run DAST scan — are there exploitable vulnerabilities in the running application?
• Check OWASP Top 10 coverage — injection, broken authentication, sensitive data exposure, XXE, broken access control
• Assess authentication implementation — password hashing algorithm, session management, MFA support
• Review authorization model — is access control role-based, attribute-based? Are permissions enforced consistently?

Infrastructure security

• Review network architecture — are production systems in private subnets? Is ingress/egress controlled?
• Check data encryption — encryption at rest and in transit? What algorithms and key management?
• Assess secrets management — are credentials stored in code, environment variables, or a secrets manager?
• Review access controls — who has production access? Is access logged? Is MFA enforced?
• Check for security monitoring — intrusion detection, log analysis, alerting on suspicious activity

Compliance

• Identify applicable regulations (GDPR, SOC 2, HIPAA, PCI-DSS)
• Assess data privacy practices — PII handling, consent management, data retention policies
• Check audit trail — are critical actions logged with user identity, timestamp, and action detail?
• Review incident response plan — does it exist? Has it been tested?

Scoring guide:

• Green: No critical vulnerabilities, strong authentication, encryption everywhere, compliance-ready
• Yellow: Some vulnerabilities (no critical), partial encryption, compliance gaps
• Red: Critical vulnerabilities, weak authentication, plaintext secrets, no compliance framework

Area 4: Scalability and Performance

Scalability determines whether the system can handle growth without proportional cost increases or architectural rewrites.

Current performance

• Review performance metrics — response times (p50, p95, p99), throughput, error rates
• Check resource utilization — CPU, memory, disk, network at current load
• Identify bottlenecks — database queries, external API calls, compute-intensive operations
• Assess caching strategy — what is cached, where, and how is cache invalidation handled?

Scalability architecture

• Assess horizontal scalability — can the application scale by adding instances, or does it require vertical scaling?
• Check database scalability — read replicas, connection pooling, query optimization, sharding readiness
• Evaluate statelessness — can any instance handle any request, or is there session affinity?
• Review auto-scaling configuration — does the system scale automatically based on load?

Load and stress testing

• Has load testing been performed? What were the results?
• What is the maximum tested throughput? How does it compare to projected peak load?
• How does the system degrade under overload — graceful degradation or cascading failure?
• What is the recovery time after an overload event?

Scoring guide:

• Green: Horizontally scalable, load-tested, auto-scaling configured, 3x headroom above current peak
• Yellow: Vertically scalable only, limited load testing, manual scaling, 1.5x headroom
• Red: Cannot scale without rearchitecting, no load testing, at capacity

Area 5: Team and Process

Technology is only as good as the team building and maintaining it. Team assessment reveals whether the organization can sustain and evolve the system.

Team composition

• Map the team — roles, experience levels, tenure, areas of responsibility
• Identify key person dependencies — is critical knowledge concentrated in one or two people?
• Assess team stability — turnover rate over the past 12 months
• Evaluate hiring pipeline — how long does it take to fill open positions?

Development process

• Assess CI/CD maturity — automated build, test, and deployment pipeline
• Review branching strategy — is there a consistent workflow (GitFlow, trunk-based)?
• Check code review practices — are all changes reviewed before merge? What is the review quality?
• Evaluate release process — how often are releases deployed? What is the lead time from commit to production?

Knowledge management

• Assess project documentation — architecture docs, API docs, onboarding guide, runbooks
• Check code documentation — are complex functions documented? Is there an API reference?
• Evaluate onboarding process — how long does it take a new developer to make their first meaningful contribution?
• Review knowledge sharing practices — tech talks, documentation culture, pair programming

Scoring guide:

• Green: Full team, no single points of failure, mature CI/CD, comprehensive documentation
• Yellow: Some key person risk, basic CI/CD, partial documentation
• Red: High key person risk, manual processes, minimal documentation

Scoring Summary Template

Area	Weight	Score (1-5)	Weighted score	Key findings
Code quality	20%	_	_
Architecture	25%	_	_
Security	20%	_	_
Scalability	15%	_	_
Team & process	20%	_	_
Total	100%		_ / 5.0

Interpretation:

• 4.0-5.0: Low risk — system is well-built and maintainable
• 3.0-3.9: Moderate risk — specific areas need investment but no blockers
• 2.0-2.9: High risk — significant technical debt that will require substantial budget to address
• Below 2.0: Critical risk — fundamental issues that may require rearchitecting or rebuilding

How ARDURA Consulting Supports Technical Due Diligence

Technical due diligence requires experienced engineers who can assess code, architecture, and team practices quickly and objectively — skills that are difficult to find for short-term engagements.

• 500+ senior specialists across software architecture, security engineering, DevOps, and quality assurance — available within 2 weeks
• 40% cost savings compared to traditional hiring, with engagement flexibility from 2-week assessments to ongoing technical advisory
• 99% client retention — engineers who provide honest, actionable assessments rather than generic findings
• 211+ completed projects — assessors who have seen what good and bad look like across dozens of technology stacks and industries

Whether you need a 2-week rapid assessment for an M&A timeline or an ongoing technical advisory for portfolio companies, ARDURA Consulting provides the engineering depth that turns due diligence findings into informed decisions.