{"id":409,"date":"2026-10-14T04:21:00","date_gmt":"2026-10-14T04:21:00","guid":{"rendered":"http:\/\/www.scmgalaxy.com\/tutorials\/2015\/04\/07\/difference-between-dynamic-code-analysis-and-static-code-analysis\/"},"modified":"2026-10-14T04:21:00","modified_gmt":"2026-10-14T04:21:00","slug":"difference-between-dynamic-code-analysis-and-static-code-analysis","status":"publish","type":"post","link":"https:\/\/www.devopsschool.com\/blog\/difference-between-dynamic-code-analysis-and-static-code-analysis\/","title":{"rendered":"Static vs Dynamic Code Analysis: Key Differences and How to Use Both in DevSecOps"},"content":{"rendered":"\n

Originally published on April 7, 2015; fully revised and updated.<\/em><\/p>\n\n\n\n

Static and dynamic code analysis are two complementary ways to improve software quality and security. This guide is for developers, QA engineers, and DevOps teams who want to understand when to use each method, what each one catches best, and how to wire both into a CI\/CD pipeline.<\/p>\n\n\n\n

\"Static<\/p>\n\n\n\n

Static vs dynamic analysis at a glance<\/h2>\n\n\n\n

Static analysis<\/strong> inspects source code, bytecode, or configuration without executing the application<\/em>. Dynamic analysis<\/strong> evaluates application behavior while the software is running<\/em> (for example during tests or in a test environment).<\/p>\n\n\n\n

Aspect<\/th>Static analysis<\/th>Dynamic analysis<\/th><\/tr><\/thead>
When it runs<\/td>Before runtime<\/td>During runtime<\/td><\/tr>
Input<\/td>Code and project artifacts<\/td>Running process and live requests<\/td><\/tr>
Coverage style<\/td>Broad code inspection<\/td>Only executed paths and exercised behaviors<\/td><\/tr>
Finds well<\/td>Coding issues, insecure patterns, rule violations<\/td>Runtime defects, memory issues, environment-specific behavior<\/td><\/tr>
Feedback timing<\/td>Early in development<\/td>During test execution and runtime validation<\/td><\/tr>
Typical pipeline stage<\/td>Pre-commit, pull request, build<\/td>Integration test, staging, pre-release<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

What each method is best at<\/h2>\n\n\n\n

Where static analysis helps most<\/h3>\n\n\n\n
  • Catches issues early, often before code is merged.<\/li>
  • Scales well across large repositories and frequent commits.<\/li>
  • Enforces coding standards and secure coding rules consistently.<\/li>
  • Supports fast feedback loops in pull requests.<\/li><\/ul>\n\n\n\n

    Where dynamic analysis helps most<\/h3>\n\n\n\n
    • Finds defects that appear only when code executes.<\/li>
    • Validates behavior under realistic inputs and environments.<\/li>
    • Exposes issues tied to runtime state, concurrency, and integration boundaries.<\/li>
    • Helps verify whether fixes actually resolve observed runtime failures.<\/li><\/ul>\n\n\n\n

      In practice, high-performing teams use both approaches because each one covers blind spots the other cannot fully address.<\/p>\n\n\n\n

      Workflow: combining static and dynamic analysis in CI\/CD<\/h2>\n\n\n\n

      A common pattern is to run static checks first (fast fail), then run dynamic checks after build\/deploy to a test target.<\/p>\n\n\n\n

      \nflowchart TD\n    A[Developer commit] --> B[Static analysis job]\n    B --> C{Static issues}\n    C -- yes --> D[Fail pipeline and fix code]\n    C -- no --> E[Build and deploy to test]\n    E --> F[Runtime and security tests]\n    F --> G{Runtime issues}\n    G -- yes --> D\n    G -- no --> H[Release approval]\n<\/pre>\n\n\n\n
      Example commands for both approaches<\/h2>\n\n\n\n
      The commands below are representative examples. Adjust tools and flags for your language, framework, and build environment.<\/p>\n\n\n
      # Static analysis examples<\/span>\nsemgrep --config auto .\neslint src\/\n\n# Runtime or dynamic analysis examples<\/span>\ngo test .\/...\ngo test -race .\/...\nvalgrind --leak-check=full .\/bin\/myservice<\/code><\/span>Code language:<\/span> PHP<\/span> (<\/span>php<\/span>)<\/span><\/small><\/pre>\n\n
      name: quality-and<\/span>-runtime-checks\non:\n  pull_request:\n\njobs:\n  verify:\n    runs-on: ubuntu-latest\n    steps:\n      - uses: actions\/checkout@v4\n      - name: Static<\/span> analysis\n        run: semgrep --config auto .\n      - name: Unit tests\n        run: go test .\/...\n      - name: Race detection\n        run: go test -race .\/...<\/code><\/span>Code language:<\/span> PHP<\/span> (<\/span>php<\/span>)<\/span><\/small><\/pre>\n\n\n
      Tooling categories compared<\/h2>\n\n\n\n
      Category<\/th>Static analysis examples<\/th>Dynamic analysis examples<\/th><\/tr><\/thead>
      Code quality<\/td>Linters, rule-based scanners<\/td>Runtime test assertions, integration tests<\/td><\/tr>
      Security<\/td>Pattern and policy scanners<\/td>Runtime security testing against a running app<\/td><\/tr>
      Reliability<\/td>Control-flow and rule checks<\/td>Race detection, memory\/runtime instrumentation<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
      Best practices<\/h2>\n\n\n\n
      • Run static checks on every pull request to catch issues early.<\/li>
      • Run dynamic checks in repeatable test environments, not ad hoc.<\/li>
      • Treat findings as triageable data: prioritize by risk and exploitability.<\/li>
      • Fail builds on high-severity issues, but avoid noisy rules that teams ignore.<\/li>
      • Track trend metrics over time (new issues, fixed issues, recurring classes).<\/li>
      • Use both methods together for better coverage and fewer late surprises.<\/li><\/ul>\n","protected":false},"excerpt":{"rendered":"
        Static and dynamic code analysis solve different quality and security problems. This guide explains the differences, trade-offs, and how to combine both in a practical CI\/CD workflow.<\/p>\n","protected":false},"author":1,"featured_media":3500,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_joinchat":[],"footnotes":""},"categories":[62],"tags":[517,1720,1003,784,492,1743,1721,1722,545,1090,1723,1742],"class_list":["post-409","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-code-analysis","tag-analysis","tag-between","tag-code","tag-code-analysis","tag-difference","tag-difference-between-dynamic-code-analysis-and-static-code-analysis","tag-dynamic","tag-dynamic-code-analysis","tag-how","tag-static","tag-static-code-analysis","tag-static-code-analysis-vs-dynamic-code-analysis"],"_links":{"self":[{"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/posts\/409","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/comments?post=409"}],"version-history":[{"count":3,"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/posts\/409\/revisions"}],"predecessor-version":[{"id":79278,"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/posts\/409\/revisions\/79278"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/media\/3500"}],"wp:attachment":[{"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/media?parent=409"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/categories?post=409"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/tags?post=409"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}