Continuous Integration and Software Quality: A Causal Explanatory Study

TL;DR

This study investigates the causal impact of Continuous Integration on software quality using a combination of literature review, mining software repositories, and causal DAG analysis, revealing both direct and indirect effects.

Contribution

It introduces a novel causal analysis approach combining literature, empirical data, and DAGs to understand CI's influence on software quality, including indirect effects.

Findings

CI has a direct positive effect on software quality

CI indirectly improves quality through enhanced team communication

Project age confounds the relationship between CI and SQ

Abstract

Continuous Integration (CI) is a software engineering practice that aims to reduce the cost and risk of code integration among teams. Recent empirical studies have confirmed associations between CI and the software quality (SQ). However, no existing study investigates causal relationships between CI and SQ. This paper investigates it by applying the causal Direct Acyclic Graphs (DAGs) technique. We combine two other strategies to support this technique: a literature review and a Mining Software Repository (MSR) study. In the first stage, we review the literature to discover existing associations between CI and SQ, which help us create a "literature-based causal DAG" in the second stage. This DAG encapsulates the literature assumptions regarding CI and its influence on SQ. In the third stage, we analyze 12 activity months for 70 opensource projects by mining software repositories -- 35 CI and 35 no-CI projects. This MSR study is not a typical "correlation is not causation" study because it is used to verify the relationships uncovered in the causal DAG produced in the first stages. The fourth stage consists of testing the statistical implications from the "literature-based causal DAG" on our dataset. Finally, in the fifth stage, we build a DAG with observations from the literature and the dataset, the "literature-data DAG". In addition to the direct causal effect of CI on SQ, we find evidence of indirect effects of CI. For example, CI affects teams' communication, which positively impacts SQ. We also highlight the confounding effect of project age.