Extracting Rationale for Open Source Software Development Decisions -- A Study of Python Email Archives

TL;DR

This paper presents a large-scale study of Python email archives to extract decision rationales in open source development, introducing a heuristics-based system called Rationale Miner to improve transparency and accountability.

Contribution

It uncovers decision rationales from extensive email data and introduces a novel heuristics-driven system for rationale extraction applicable to similar communities.

Findings

Successfully extracted decision rationales from 1.5 million emails.

Demonstrated the effectiveness of heuristics-based rationale extraction.

Facilitated transparency and accountability in open source governance.

Abstract

A sound Decision-Making (DM) process is key to the successful governance of software projects. In many Open Source Software Development (OSSD) communities, DM processes lie buried amongst vast amounts of publicly available data. Hidden within this data lie the rationale for decisions that led to the evolution and maintenance of software products. While there have been some efforts to extract DM processes from publicly available data, the rationale behind how the decisions are made have seldom been explored. Extracting the rationale for these decisions can facilitate transparency (by making them known), and also promote accountability on the part of decision-makers. This work bridges this gap by means of a large-scale study that unearths the rationale behind decisions from Python development email archives comprising about 1.5 million emails. This paper makes two main contributions. First, it makes a knowledge contribution by unearthing and presenting the rationale behind decisions made. Second, it makes a methodological contribution by presenting a heuristics-based rationale extraction system called Rationale Miner that employs multiple heuristics, and follows a data-driven, bottom-up approach to infer the rationale behind specific decisions (e.g., whether a new module is implemented based on core developer consensus or benevolent dictator's pronouncement). Our approach can be applied to extract rationale in other OSSD communities that have similar governance structures.