Software Code Review In Due Diligence: Key Red Flags Investors Should Watch For

Software remains a critical area of M&A activity, but investors are becoming more selective about the technology assets they acquire. PwC’s 2026 M&A outlook notes that technology continues to attract some of the highest deal values, while AI is reshaping how investors assess software businesses, their scalability, and their long-term competitiveness. In 2025, technology led global megadeal activity with 26 announced transactions, more than any other sector.

At the same time, private capital is deploying capital more cautiously.

The firm also notes that sponsors are becoming more cautious around software targets as they evaluate AI disruption, revenue-model durability, and future technology investment requirements.

Against this backdrop, a software company can still present strong revenue growth, an attractive product roadmap, and a compelling management story while carrying significant risks inside its codebase.

During technology due diligence, a software code review gives investors a closer view of how the underlying product is actually built, maintained, secured, and scaled. The objective is not to determine whether every line of code is perfect. It is to identify issues that could materially affect the investment thesis, including hidden technical debt, security vulnerabilities, poor maintainability, weak testing practices, scalability constraints, and engineering dependencies that may require additional investment after close.

For private equity firms, strategic acquirers, and technology leaders, these findings can influence valuation assumptions, post-acquisition priorities, integration planning, and the level of engineering investment required to execute the growth plan.

This guide outlines 10 areas investors should examine during a software code review, the red flags to watch for, and what those findings may mean from an investment perspective.

What Is a Software Code Review in Due Diligence?

A software code review in tech due diligence is an independent assessment of a target company’s source code, engineering practices, and related development artifacts.

Unlike a routine peer review performed during software development, due diligence code review evaluates the codebase from an investment perspective. The goal is to determine whether the software can support the company’s current operations and future growth without introducing disproportionate technical, security, or execution risk.

Depending on access and scope, the review may examine source repositories, commit history, coding standards, test suites, dependencies, security controls, CI/CD practices, technical documentation, and evidence of technical debt.

A code review is only one part of a broader tech due diligence checklist, which also evaluates architecture, infrastructure, security, data, engineering organization, and operational maturity.

Why Software Code Review Matters to Investors

For investors who are evaluating a tech company, reviewing code quality (code scan) is an essential part of the due diligence process.

A strong code base reflects solid engineering practices, while weak or inconsistent code can reveal deeper structural issues that might rear their ugly heads later in the growth stage.

Sure, financials are important, but glowing profit margins are no excuse to skip code reviews. If the software doesn’t meet coding standards, the financials won’t be glowing for long. Poorly written code increases the risk of technical debt, performance bottlenecks, and security breaches — factors that can reduce a company’s valuation and derail an acquisition.

Ignoring these aspects can lead to acquisitions that are really more of a liability than an asset, so ignore them at your peril.

10-Step Code Review Checklist for Due Diligence

In any investment opportunity, time constraints, expenses, and resources available inevitably limit the amount of review possible. With that in mind, below are the 10 steps our experts in the technology due diligence services always follow when conducting a review and how they stack up against code review best practices.

Code Quality and Maintainability

The main priority in any code review is the quality of the code and the defect density that the reviewer encounters.

Code quality is not simply an engineering concern. It can directly influence how quickly a company can release products, integrate acquisitions, scale infrastructure, respond to security issues, and execute its post-investment roadmap.

Security Vulnerabilities

Security flaws can lead to data breaches, regulatory fines, and reputational damage. A proper security strategy is non-negotiable for investors and is a top priority in the code review.

• Does the code follow secure coding best practices?
• Does the system handle test cases for authentication and data validation?
• Are common vulnerabilities, such as SQL injection or cross-site scripting, mitigated? If so, how?
• Are authentication and authorization mechanisms correctly in place (and adhered to)?
• Are there hardcoded credentials in the repository?
• Is sensitive data encrypted and protected with appropriate testing measures?
• Is security testing a regular part of the code review process?

Test Coverage and Automated Testing

Testing is the backbone of software reliability. Without it, even minor changes can introduce bugs, security vulnerabilities, or performance issues that may go unnoticed until they cause real-world problems. Test coverage refers to the extent to which the software’s functionality is tested by automated or manual tests.

A high level of test coverage found in the code review process means that critical features, edge cases, and failure scenarios are accounted for before deployment. Automated testing tools allow teams to catch errors early in the development process, reducing time reviewing code and costs associated with fixing defects later.

• Are there automated tests for critical functionality?
• Does the test suite cover edge cases and failure scenarios?
• Is the defect rate low across different test scenarios?
• Are developers regularly running tests before pushing code?
• Do test cases follow best practices and provide meaningful validation?

Peer Code Review and Engineering Discipline

A strong code review process helps maintain high code quality after a code change, reducing defects and building collaboration between developers. Effective peer code reviews ensure that code is not only functional but also secure, maintainable, and aligned with coding standards.

For investors, a well-structured code review process signals good engineering discipline and long-term scalability. If developers skip code reviews due to time constraints, it often leads to higher defect density and higher maintenance costs.

• Does the team embrace peer review as a standard practice?
• Do senior engineers mentor junior developers during reviews?
• Does the team follow a structured code review checklist?
• Are code reviewers allocated in the team, or does everyone participate in this?
• Is constructive feedback provided in pull requests, or are reviews rushed?
• Do code owners take responsibility for fixing identified issues in their own code? If not, how are bugs fixed?

Coding Standards and Development Consistency

Adhering to coding standards and best practices is the most effective way of delivering quality code. Investors should check whether the development team follows industry best practices and enforces consistent coding guidelines across the whole team.

• Does the team follow a documented set of coding standards? If so, do developers regularly review and update these coding standards?
• Are recognized, industry-standard code review best practices followed?
• Does the company enforce consistent coding standards across teams?
• Are best practices integrated into the development process?
• Are developers adding comments and documentation where necessary?

Performance and Scalability

A platform does not need to support hypothetical unlimited scale. The more relevant question is whether its current design can support the growth assumptions behind the investment thesis.

Poorly optimized code can lead to slow load times, resource inefficiencies, and scaling issues as the software grows. A thorough code review should evaluate whether the system is designed to handle increased user demand without degrading performance.

A scalable architecture ensures long-term stability and prevents costly refactoring in the future. Investors should prioritize teams that emphasize performance in their development process.

• Does the code efficiently handle large datasets, requests, and concurrent users?
• Are there unnecessary loops, redundant computations, or excessive API calls?
• Are database queries optimized to avoid expensive operations like full table scans?
• Does the team run performance tests before pushing code to production?
• Is caching used effectively to minimize redundant processing?

Documentation and Knowledge Sharing

A well-documented codebase is an essential part of maintainability and long-term success. Without proper documentation, onboarding new developers, fixing bugs, and implementing new features becomes a slow and error-prone process.

Clear documentation ensures that code reviewers, developers, and other teams understand the reasoning behind key decisions.

• Are function, class, and module descriptions provided to explain code intent?
• Are comments used effectively to clarify complex or non-self-explanatory logic?
• Does the project contain up-to-date documentation for architecture, APIs, and dependencies?
• Are best practices followed for internal documentation, such as READMEs and inline comments?
• Is documentation reviewed alongside code to ensure consistency with the latest changes?

Defect Rate and Bug Resolution Process

The defect rate measures how often errors and bugs appear in the software. A high defect density suggests poor coding practices, inadequate testing, or rushed development cycles.

Investors should ensure that teams have an effective bug tracking and resolution process to keep defects under control.

• Is there a structured defect-tracking system in place?
• How quickly are bugs identified and fixed after being reported?
• Does the team run tests and peer code reviews before pushing changes to avoid regressions?
• Are defect trends analyzed to identify recurring issues in the code base?
• Is there an escalation process for critical defects affecting stability or security?

Use of Code Review Tools and Automation

Automated tools improve the efficiency of code reviews by catching common mistakes, enforcing coding standards, and reducing manual effort. Not to mention, automation can increase the inspection rate while removing the time constraints that often limit a code review.

Investors should check whether the team leverages automation in their enterprise development workflow and the processes around it.

• Are automated testing tools used for static analysis, security checks, and style enforcement?
• Does the team have a structured pipeline for continuous integration testing and deployment (for example, CI/CD)?
• Are test cases automatically executed before merging new code?
• Are code reviews integrated with pull requests, ensuring every change is reviewed?
• Do developers rely on code review checklists to maintain best practices?

Technical Debt and Refactoring Practices

Technical debt accumulates when teams cut corners or push unoptimized code to meet deadlines. While some debt is inevitable up to a point, a well-managed development process prioritizes refactoring and long-term maintainability (paying the debt).

Investors should ensure that teams proactively address technical debt rather than deferring it indefinitely.

• Does the team regularly review and refactor outdated or inefficient code?
• Are there structured plans to address existing technical debt?
• Does the company balance feature development with maintaining and improving the code base?
• Do developers follow best practices to avoid accumulating unnecessary debt?
• Is there a clear strategy for phasing out legacy systems or deprecated dependencies?

How to Prioritize Code Review Findings

Not every issue uncovered during a software code review should carry the same weight in an investment decision. Mature software platforms almost always contain technical debt, outdated components, inconsistent coding practices, or areas that could be improved.

The key question is not simply how many issues exist, but which findings are material to the transaction, the investment thesis, or the company’s ability to execute after close.

A useful prioritization framework should therefore consider both technical severity and business impact.

Critical Findings

Critical findings are issues that could materially affect the transaction, create immediate operational or security exposure, or undermine the core investment thesis.

Examples may include:

• severe security vulnerabilities in production systems
• unsupported or end-of-life technologies in critical platform components
• major intellectual property or licensing concerns
• architecture limitations that could prevent the platform from supporting expected growth
• critical functionality that depends heavily on one or two individuals
• high-risk technical dependencies with no viable replacement or mitigation plan.

These findings typically require immediate attention because they may influence deal terms, remediation requirements, post-close priorities, or whether additional technical investigation is needed before proceeding.

High-Priority Findings

High-priority findings may not threaten the transaction directly, but they could require substantial engineering effort or investment after close.

Examples include:

• significant technical debt across core modules
• weak automated testing around business-critical workflows
• tightly coupled architecture that slows product development
• inconsistent security controls
• major gaps in CI/CD automation
• scalability bottlenecks that are manageable today but may become problematic as the business grows.

For investors, these findings matter because they can affect the amount of engineering capacity and capital required to execute the post-investment roadmap.

Medium-Priority Findings

Medium-priority findings usually represent manageable engineering weaknesses that should be addressed over time but are unlikely to materially change the investment decision on their own.

Examples may include:

• inconsistent coding standards across teams
• incomplete documentation
• outdated but still supported libraries
• areas of unnecessary code duplication
• limited observability in non-critical systems
• manual processes that reduce development efficiency.

These issues are often best incorporated into the post-close technology roadmap rather than treated as immediate deal blockers.

Low-Priority Findings

Low-priority findings are typically normal software improvement opportunities with limited impact on the business or investment thesis.

Examples include:

• localized code cleanup
• minor naming inconsistencies
• non-critical refactoring opportunities
• low-risk technical improvements with limited operational impact.

These findings can still be valuable to engineering teams, but investors should avoid allowing minor code-quality observations to distract from more material technology risks.

Prioritize Findings by Investment Impact

A practical prioritization model might look like this:

Priority	What It Means	Example	Potential Investment Impact
Critical	Could materially affect the transaction or investment thesis	Severe security vulnerability, unsupported core platform	Deal risk, immediate remediation, potential impact on valuation
High	Requires significant post-close attention or investment	Major technical debt, scalability bottleneck	Increased engineering investment, slower value creation
Medium	Manageable issue that should enter the technology roadmap	Inconsistent testing or documentation	Operational inefficiency, incremental remediation
Low	Normal engineering improvement opportunity	Local code cleanup or minor refactoring	Limited impact on investment decision

The objective of due diligence is therefore not to produce the longest possible list of defects. A codebase with 200 minor findings may represent less investment risk than one with only a handful of issues affecting security, scalability, or the ability to execute the growth strategy.

The most useful software code review is one that distinguishes routine engineering improvement from material technology risk, helping investors understand what needs attention before close, what should become part of the first 100-day plan, and what can be addressed through normal product and engineering evolution.

What Investors Should Receive From a Code Review

A software code review should not end with a technical report filled with isolated defects, code smells, or engineering observations.

The final output should translate technical evidence into a decision-oriented view of the software asset.

Executive Assessment of Codebase Health

Investors should receive a concise summary of the overall condition of the codebase, including its maintainability, security posture, scalability, testing maturity, and development quality.

This assessment should answer questions such as:

• Is the software fundamentally sound?
• Can the current codebase support continued product development?
• Are there structural issues that could constrain growth?
• Does the platform require incremental improvement or significant remediation?

The goal is to provide a clear overall view without requiring investment teams to interpret low-level engineering details themselves.

Material Risks and Red Flags

The review should clearly separate routine engineering issues from findings that could materially affect the transaction.

Material risks may include:

• severe security vulnerabilities
• significant technical debt in core components
• unsupported technologies or critical dependencies
• weak automated testing around business-critical functionality
• scalability limitations
• poor maintainability
• key-person dependencies
• architectural patterns that make future integration or modernization difficult.

Each finding should explain not only what the issue is, but also why it matters to the investment.

For example, a tightly coupled codebase is not simply an architecture concern. It may indicate slower product development, more difficult post-acquisition integration, and a larger modernization requirement than management originally assumed.

Technical Debt Assessment

Investors should understand where technical debt exists, how concentrated it is, and whether it is actively managed.

A useful assessment should identify:

• areas where technical debt is most material
• whether debt affects core or peripheral functionality
• whether engineering leadership is aware of it
• whether remediation is already reflected in the product roadmap
• which issues may consume significant engineering capacity after close.

The objective is not to calculate every hour of future refactoring, but to determine whether technical debt could materially change assumptions about the company’s technology investment needs.

Scalability and Performance Findings

Where growth is an important part of the investment thesis, the code review should help validate whether the software is capable of supporting that growth.

Investors should receive visibility into:

• current performance bottlenecks
• components that may struggle as traffic or transaction volume increases
• inefficient database or API patterns
• areas where scaling may require architectural changes rather than additional infrastructure alone
• evidence that the platform has already been tested under realistic workloads.

These findings help distinguish between a platform that can scale incrementally and one that may require substantial reengineering before the business can reach its growth targets.

Security and Reliability Concerns

The review should identify software-level security issues that could create business, regulatory, or operational exposure.

This may include:

• insecure authentication or authorization logic
• poor secrets management
• vulnerable third-party dependencies
• weak input validation
• inadequate error handling
• insufficient security testing
• recurring production defects.

Investors should also understand whether these issues represent isolated defects or symptoms of broader weaknesses in engineering discipline.

Engineering Process Observations

Source code often reveals how the engineering organization operates.

The review may provide evidence around:

• peer-review discipline
• automated testing
• CI/CD quality gates
• dependency management
• coding standards
• documentation
• release practices
• how systematically teams address defects and technical debt.

These observations can help investors assess whether the organization has the engineering maturity required to maintain and evolve the platform after the transaction.

Prioritized Remediation Actions

A useful code review should conclude with a prioritized set of actions rather than a flat list of recommendations.

Those actions can be grouped into:

• Pre-close considerations — issues requiring clarification or mitigation before the transaction;
• Immediate post-close priorities — material risks that should be addressed early;
• First 100-day initiatives — improvements that support stabilization, scalability, or integration;
• Longer-term modernization opportunities — changes that improve the platform over the broader investment period.

This helps deal teams move directly from diligence into execution rather than restarting the technical assessment after close.

Areas Requiring Deeper Investigation

Code review findings may also reveal questions that cannot be fully resolved through source code alone.

For example:

• scalability issues may require architecture or infrastructure analysis
• security concerns may require deeper cybersecurity assessment
• integration complexity may require reviewing APIs and dependent systems
• technical debt may need to be evaluated against the product roadmap
• AI-related components may require additional assessment of data, governance, models, and infrastructure.

A strong review should explicitly identify these areas instead of overstating conclusions based on incomplete evidence.

Investment and Post-Deal Implications

Most importantly, the final readout should translate technical findings into implications for the investment.

Investors should be able to understand:

• whether identified risks could affect the investment thesis;
• which issues may require additional post-close capital or engineering capacity;
• whether technology limitations could slow revenue or product growth;
• what should be prioritized during integration or the first 100 days;
• where technology improvements could become opportunities for value creation.

The objective is to turn source-code evidence into investment clarity.

A software code review is most valuable when the final question is no longer simply:

“Is this good code?”

but rather:

“What does the condition of this codebase mean for the asset we are acquiring, the risks we are inheriting, and the technology investment required to execute the growth plan?”

The Last Word From Our Experts

It’s no understatement to say that a formal review of a company’s development process can make or break an investment decision.

A great code review is like peeking behind those flashy demos and sleek financial brochures into the nitty-gritty of a business. Savvy investors always assess how well the whole team adheres to code review best practices.

But doing it solo is risky. Even experienced investors can miss critical red flags buried in a software project’s structure. That’s why having technical experts review code quality, security, and maintainability is the most effective way to validate an investment’s potential.

Need expert support assessing a company’s codebase? KMS Technology specializes in technical due diligence, code audits, and software evaluations to help you make informed investment decisions. Get in touch today to safeguard your next tech investment.