1. CodeScene
Get Deep Insights into Your (Clojure) Code
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2. About (me)
• Java
• Clojure
• curiousprogrammer.net
• Empear - CodeScene
Brno, CZ
Malmo, SE
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3. Agenda
• Motivation
• What is CodeScene
• Demo
• “Under the hood”
• Why (not) Clojure
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4. Motivation
• Developers spend most of their time on doing
modifications to existing code
• Technical Debt is inevitable and must be
proactively eliminated.
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5. 5

6. Technical Debt
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7. Motivation (2)
• Clojure benefits - dynamic, quick experiments
=> rapid development
• Technical Debt can accumulate quickly
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8. Motivation (3)
• Not all technical debt is created equal - Return
On Investment
• Static analysis ignores history
• Relying solely on human’s expertise is ineffective
and expensive
• We need concrete data to be able to deal with
Technical debt effectively
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9. What is CodeScene?
• Web-based code analysis tool that lets you
prioritise technical debt, identify organizational
inefficiences, and detect code that’s expensive
to maintain.
• Language neutral
• On-prem & cloud version (codescene.io)
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10. Demo:
clojure.core
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11. Demo: Technical Debt
• Hotspots - commit frequency or code churn
• Refactoring Targets - prioritised hotspots
• X-Ray
• Programming languages
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12. Demo: Architecture
• Hotspots
• Conway’s Law
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13. Demo: Social Analyses
• Individuals
• Owners
• Knowledge loss (Rich Hickey)
• Coordination needs - gvec.clj
• Authors
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14. Demo: Project Management
• Branch statistics (re-frame)
• Delivery risk
• Lead Time To Merge
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15. Demo: Early Warnings
• metabase
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16. “Under the Hood”
• git log -> parse -> analyse -> store to disk -> …
present (UI)
• Pipes & Filters
• Core “analysis” module reused by cloud and on-
prem applications
• Performance
• Libraries
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17. Pipes & Filters
• Git -> git log -> parse -> analyze -> persist on
disk -> load from disk -> present (UI)
• Pipes & Filters
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18. Parsing
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19. Analyses
• Language neutral - based on universal LOC
metric
• X-Ray (ANTLR)
• Hotspots
• Temporal Coupling
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20. Analyses (2)
• Core analysis module is completely separated
and reused from both on-prem and cloud
applications
• Results are stored in plain CSV files - no DB!
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21. Performance
• Memory is the bottleneck => serialisation of
analyses
• Linux ~45 min on i7 machine
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22. Libraries
• ANTLR - microgrammars (X-Ray)
• Incanter - buggy
• ring & compojure
• selmer
• spec
• clojure.java.jdbc - H2
• core.async - simple scheduler
• 3rd party integrations - clj-http, proxy-vole, clj-ldap, clj-slack
• etaoin - UI tests
• cprops - configuration
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23. Why Clojure?
• It’s fun
• Productivity
• Quick feedback
• Fast innovations
• Data transformations
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24. “That’s it? Just these guys?!”
— Carl Gustaf
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25. Why Not Clojure(Script)?
• Server-side rendering with thin JS layer
• Jenkins plugin - Java
• Haskell - git cloning service
• Kotlin? (IDEA plugin)
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26. Conclusion
• Technical debt is a real problem regardless of
programming language
• There’s a huge amount of useful information
stored in your version control system
• Ultimately, you need to rely on human expertise
• Support your developer’s judgment and
experience with data to get the highest ROI
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27. Resources
• CodeScene Introduction (15 min) screencast
• CodeScene Product Sheet
• CodeScene.io Showcase - clojure, erlang, React, etc.
• Adam’s talks & books
• Talk A Crystal Ball to Prioritize Technical Debt
• EuroClojure 2015 talk Beyond Code: Repository Mining with Clojure
• book Software Design X-Rays: Fix Technical Debt with Behavioral Code Analysis
• book Your Code as a Crime Scene
• CodeScene enterprise documentation
• Empear’s blog - e.g. The Day I Parsed a Monster
• code-maat repository
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28. Go and Try!
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https://codescene.io/