Cross-Metric Impact

Fixing circular dependencies doesn’t only improve the SCC metrics — it improves other metrics that depend on the dependency graph. Arxo uses the result of cycle detection (the “condensed” graph where each cycle is a single node) inside several other analyses. So reducing cycles often improves Layer Structure, Change Impact, Code Health, and Insights in one go.

For an overview of circular dependencies, see Circular Dependencies.

How Other Metrics Use Cycle Data

After finding cycles, Arxo builds a condensed graph: each strongly connected component (cycle or single module) becomes one node, and edges between components are preserved. That graph is a directed acyclic graph (DAG). Several metrics run on this DAG or use it to reason about your codebase.

Metric	How it uses cycle/SCC data	Effect of fixing cycles
Layer Structure	Computes “agony” and hierarchy levels on the condensed DAG. Cycles are collapsed into one node, so the DAG can have a clear direction.	Fewer/smaller cycles ⇒ cleaner levels, lower agony, better hierarchy score.
Change Impact	Measures how much of the graph is reachable from each node. Cycles create large strongly connected blobs, so from any node in a cycle you can reach the whole cycle.	Breaking cycles shrinks reachable sets and usually lowers propagation cost.
Critical Modules	Betweenness and other centrality measures count paths through nodes. Cycles create many paths through the same set of nodes.	Breaking cycles can reduce centrality of former cycle members and spread load.
Module Boundaries	Community detection and modularity work better on graphs with clear boundaries. Cycles blur boundaries.	Fewer cycles ⇒ clearer modules and better modularity scores.
Code Smells	Cyclic package/module dependencies are detected as a smell.	Fixing those cycles removes the corresponding smell.
Refactoring Recommendations	Uses SCC and cycle details to suggest concrete cycle-breaking refactors.	Fewer cycles ⇒ fewer cycle-related recommendations.
Cross-Metric Insights	Combines multiple metrics; cycle-related issues are part of the overall risk picture.	Less cycle debt ⇒ better overall insights and risk scores.

So when you break cycles, you’re not only making scc.max_cycle_size and scc.total_nodes_in_cycles look better — you’re giving the rest of the pipeline a cleaner graph to work with.

Practical Takeaway

Prioritize cycles when you want to improve structure and several metrics at once.
Re-run analysis after refactors: you should see SCC improve and often Layer Structure, Change Impact, Modularity, and Insights improve as well.
Use Cycle Microscope and Git History to decide which files in a cycle to fix first for maximum impact.

Next Steps

Circular Dependencies — Overview
Cycle Microscope — Per-cycle details
Fixing Cycles — Step-by-step process
Cross-Metric Insights — How metrics are combined