Lighthouse perched on sea cliffs

Software is becoming increasingly central to business transactions in today’s complex world. Like any other transaction assets, buyers need to know precisely what they’re buying and for the sellers to highlight the value of the asset they are selling properly. Technical due diligence (TDD) is the process of better evaluating such software assets and identifying their strengths and weaknesses. TDD is a critical step in any software-centric transaction. Entrepreneurs need to have an in-depth view of their intellectual property before it’s evaluated by the investors/acquirers. More importantly, private equity (PE) firms trying to invest and large enterprises trying to acquire more minor start-ups need a clear and detailed understanding of the main asset in the transaction. TDD is perhaps the most critical step in helping reduce risk and prevent failure in acquiring troubled assets. It also allows sellers to highlight their strengths and buyers to justify their valuation. A key question always asked in these transactions is what is a good “technical due diligence checklist”. Entrepreneurs are interested in such lists to better prepare for the future. PE firms, acquirers, and investors are looking for (TDD) service providers with a comprehensive tech due diligence checklist to examine software artifacts and components in a transaction.

If you are reading this blog post, it means you are already aware of the importance of TDD. If you have not entirely bought the idea yet, or want to learn more about TDD in general, stop here and read about why good TDD is critical. Another misconception is that technical due diligence only applies to the buy-side (PE firms and large companies investing in or acquiring targets). There is, in fact, a compelling case for sell-side diligence. Regardless of which side of a transaction you’re on, you are probably reading this page in search of a “technical due diligence checklist”. While this article does provide a checklist you’re probably looking for; it aims to underscore the importance of targeted tech due diligence based on the critical questions being asked, key risks involved in the transaction, and relevant post-transaction considerations. The danger in using a generic technical due diligence checklist is that it just checks the box and gets archived once the transaction closes. It fails to identify critical issues that cause the vast majority of M&A transactions to fail. Instead, a customized, carefully targeted technical due diligence should generate a report that serves as a guideline post transaction (especially if a merger of two technology stacks is involved).

A decade of software analysis, consultation, and numerous due diligence projects helped us create “Lighthouse”. Lighthouse is a suite of products and services incorporating various software analysis tools to run against the target software. Lighthouse checks a given software against multiple standards and best practices. We use Lighthouse to generate reports on how well the software under investigation responds to Quandary Peak’s rigorous audits.


As promised, here’s Lighthouse’s comprehensive technical due diligence checklist we use to analyze the target’s people, products, and technology. Depending on the nature of our engagement (PE tech due diligence, M&A, self-audit, SPAC, IPO, VC investment, etc.), we configure Lighthouse to analyze a subset of the checklist below. The list is organized into 16 main buckets representing different prongs of Lighthouse’s analysis.

Our TDD Checklist Includes the Following

Software Development Lifecycle (SDLC)

  • SDLC Methodology Used

    Scrum, Kanban, Scrumban, SAFe, Agile, Lean, Agile/Lean

  • Methodology Use

    Two week sprints, SCRUM master role, daily standups, project managers, Product owners, sprint planning, backlog, retrospective.

  • Team Roles and Responsibilities

    Product Owner, Scrum Master, Project Manager, Tech Lead, Architect,
    Release Engineer, Senior Developer, Junior Developer, UI/UX Designer,
    Front-end Developer, DevOps Manual Tester, T1 Monitoring and Operation,
    Customer Care Manager.

  • Tools

    JIRA, Slack, ClickUp, Google Docs, spreadsheets, etc.

  • Issue Tracking

    Issue types: task, bug, a new feature, stats on issue types.

  • Sessions

    Regular sessions and their frequencies, standup meetings, planning, postmortem.

  • Processes

    Version release, average release cycle, bug fix.

  • Planning and Estimations

    User story definitions, backlog scrubbing, velocity tracking, definition of done, story point,
    Time estimate for tasks methodology (Pocker, T-Shirt Sizing), reports, burndown charts, etc.

  • Process Engineering

    Pair programming, code review, sanity check scripts.

  • Delivery

    Beta and final tests before each release.

  • Support

    Level 1 and 2 teams, Help Desk.

Customer Feedback & Customer Engagement

  • Process

    Involved team members and frequency of outreaches, Net Promoter Scores (NPS), surveys, A/B testing.

Documentation and Knowledge Management

  • Tools

    Confluence, Javadoc, Sharepoint.

  • Processes and Roles

    “When/How/What/” information by “Who”.

  • Document Types

    Architecture, Root Cause Analysis (RCA), Javadocs for code, onboarding, update frequency.

Code Repository

  • Inventory Analysis

    Collaborative IDE.
    Inclusion of configuration files and scripts on Git in addition to the actual code.
    Repository security levels, 2FA, encryption, etc.
    Push access level, merge request policies, general branching strategies, and policies.
    Conflict resolution policies.
    Number of versions under work.
    Target’s branching policy, feature branch, GitFlow or GitHub flow policy, hot-fix, cherry-pick, patch-version, branch naming policy, and release policies.

Build, Integration, Continuous Integration (CI)

  • Tools

    Dependencies: Maven, Gradle, NPM, etc.
    Build: Maven, Make, etc.
    JAR Repository: Nexus
    CI/CD pipeline: Gitlab CI, Jenkins, Bamboo, Circle CI, etc.

  • CI Pipeline Automation

    Average build time
    CI steps and policies (DOs and DONTs)
    CI triggers, and outputs
    CI environment
    Virtualization and containerization of CI (Docker, etc.)

Installation, Deployment, Continuous Delivery (CD), Software Update

  • CD Steps

    Installation is automation
    Version rollback automation

  • Metrics

    Downtime, restore time, MTTF, MTBF, MTTR, MTRS, MTBSI, MTTD, MTTI, MTTK, MDT, MTTA, MTTV

  • Data Governance

    Migration and data role back

  • Container

    Container repository and container orchestration: Docker, Kubernetes, Artifactory, HashiCorp.

Software Architecture & Framework & Scalability

  • Code Analysis, Code Review, Static Code Analysis
  • Tools

    Sonar, etc.

  • Processes

    CI/CD, paired code review, code review at merge request, code audit, [code] review for documentation

  • Issue Tracking

    Bugzilla and bug analysis (most frequent bugs)
    Metrics Blocker, Critical, Major, Minor (quality gates and rules)

Data Protection

  • Security, DevSecOps, Audit
  • Processes

    Backups, encryption, access levels, monitoring, change of default settings, security processes for remote staff.

Test, Test Automation, Coverage

  • Security Audit

    Log analysis, and manual checks, open redirection broken authentication, Direct Object Reference, OWASP Top 10, CWE
    Plan B

  • Pen Test

    SQL injection, command injection, XSS, CSRF, LFI, RFI

  • (non) Functional Tests

    Data migration test, smoke test, mutation test, stress test, load test, functional test, security test, pen-test, static, acceptance test, integration test, unit test.

Log, Fault Detection, Debug

  • Tools

    Logback for log registry and collection
    ELK for log aggregation
    Sentry for error tracking
    Zipkin for distributed log tracing

  • Techniques and Procedures

    Log analysis
    Stack Trace analysis
    Memory Dump analysis
    Thread Dump Analysis
    Code instrumentation
    Software probes

  • Processes

    Rules for log registry: DB errors classification, etc.
    Log circulation: data preservation and archiving policies
    Logs retrieval from log silos

  • Dashboards and Reports

    List of all dashboards and reports that use log analysis.
    Report preparation procedures.

  • Report Types

    Authentication and authorization reports
    Systems and Data Change Reports
    Network Activity Reports
    Resource Access Reports
    Malware Activity Reports
    Failure and Critical Error Reports

DevOps (Monitoring and Incident Management)

  • Tools

    Zabbix, SolarWinds

  • Techniques and Procedures

    RCA procedures + Roles and Responsibilities
    Incident Management procedures + Roles and Responsibilities
    Issue discovery automation, server down notification, etc.
    Announcement: procedures automation, for example, text, email, or call.
    Roles and Responsibilities

  • Resolution

    Procedure automation, for example, server reboot automation, fault prediction, etc.
    List of services under monitoring

  • SLA Management

    SLA breach detection and automation

  • Managed Services

    Server availability (system uptime) & load balancing.
    Service availability: out of service (OOS), total time OOS, in-calls, mean-time response to each API call.
    Call status: complete, fail, suspend, cancel, incomplete, time-out.
    Valid/invalid messages (visible to customers).
    API call success rate & API auto-throttling: over 5 seconds, technical failure, business failure.
    Resource usage: CPU/RAM/Disk.

Risk Management and Technical Debt

  • High Risks Factors

    Departing of SSA, development team
    Price change (business)
    Server protection

  • Risks from Different Stakeholders POV

    Business managers
    Scalability risk and limitations

Human Resources, Intellectual Capital

  • Technical Empowerment, Education, Training

    Team members academic and education background
    Team members related experiences
    New employee/developer onboarding
    Diversity of skill in the team
    Available training
    Mandatory training
    Employment requirements (remote working options)
    Interview processes
    Knowledge transfer in the team
    Periodic evaluation

  • Culture, Environment, Developer Experience

    Team values
    Norms (should and shouldn’t)
    Perks and benefits
    Working environment
    Team buildings
    Gender diversity
    Punctuality and discipline
    KPI, OKR

  • Feedback Loop

    Processes (update frequency), transparency