🤖 AI Summary
This study investigates how developers practically combine programming languages to uncover the latent structure and technological composition of software ecosystems. Leveraging hundreds of thousands of posts from Stack Overflow involving 186 languages, the research uniquely integrates FP-Growth frequent itemset mining, LDA topic modeling, and Louvain community detection to consistently reconstruct the same macro-level ecosystem structure from behavioral data, thereby enabling cross-method validation. The analysis reveals strongly coupled language pairs such as Shell/Bash and Swift/Objective-C, delineates 25 distinct developer expertise profiles, and identifies three major communities—Web/enterprise, Apple ecosystem, and systems/scientific computing—with Java emerging as the central hub bridging all three.
📝 Abstract
Understanding how developers combine programming languages in practice reveals the hidden structure of the software ecosystem: which languages are used as complements, which define coherent technology stacks, and which bridge disparate communities. We present a three-phase empirical pipeline that mines Stack Overflow posts by hundreds of thousands of developers across 186 programming languages, applying FP-Growth frequent itemset mining, Latent Dirichlet Allocation topic modeling, and Louvain community detection on a weighted co-usage graph, with the goal of characterizing co-usage coupling, latent developer specializations, and macro-level ecosystem structure simultaneously from behavioral data. FP-Growth identifies tight coupling clusters such as shell/bash, Swift/Objective-C, and the C-family with lift values far exceeding what individual language popularity predicts. LDA produces 25 developer profiles including Apple-platform developers, scientific and hardware programmers, functional/academic programmers, and two distinct Unix scripting sub-profiles. Louvain partitions the language graph into three macro-communities: web/enterprise, Apple ecosystem, and systems/scientific, and identifies Java as the highest-degree hub connecting all three. All three methods independently converge on the same ecosystem structure, providing strong cross-method validation of the findings.