Class: RubyMaat::Analysis::Communication

Inherits:
BaseAnalysis show all
Defined in:
lib/ruby_maat/analysis/communication.rb

Overview

Communication analysis - identifies developer collaboration patterns Based on Conway’s Law: organizations design systems that mirror their communication structure

Instance Method Summary collapse

Instance Method Details

#analyze(dataset, options = {}) ⇒ Object 



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# File 'lib/ruby_maat/analysis/communication.rb', line 8

def analyze(dataset, options = {})
  min_revs = options[:min_revs] || 5
  min_shared_revs = options[:min_shared_revs] || 5

  # Group entities by author to find their work domains
  author_entities = {}

  dataset.to_df.each_row do |row|
    author = row[:author]
    entity = row[:entity]

    author_entities[author] ||= Set.new
    author_entities[author] << entity
  end

  # Find pairs of authors who work on shared entities
  results = []
  author_pairs = author_entities.keys.combination(2)

  author_pairs.each do |author1, author2|
    shared_entities = author_entities[author1] & author_entities[author2]
    next if shared_entities.size < min_shared_revs

    author1_entities = author_entities[author1].size
    author2_entities = author_entities[author2].size

    # Communication strength based on shared work
    avg_entities = average(author1_entities, author2_entities)
    next if avg_entities < min_revs

    communication_strength = percentage(shared_entities.size, avg_entities)

    results << {
      author: author1,
      peer: author2,
      shared: shared_entities.size,
      average: avg_entities.ceil,
      strength: communication_strength
    }
  end

  # Sort by communication strength descending
  results.sort_by! { |r| -r[:strength] }

  to_csv_data(results, i[author peer shared average strength])
end