Notes On Writing Effective Empirical Software Engineering Papers: An Opinionated Primer

2025-04-17

AI Summary

In empirical software engineering (ESE) research, the absence of systematic, explicit guidelines on scientific writing has long impeded both novice and experienced researchers—manifesting in ambiguous exposition, weak argumentation, inappropriate visualization, and inefficient reviewer responses. To address this gap, this paper synthesizes implicit domain-specific writing conventions from the authors’ extensive experience in peer review, graduate instruction, and scholarly publication. It proposes a practice-oriented writing framework centered on four pillars: structural organization, logical argumentation, visual communication, and responsive revision. Through qualitative analysis and case-based induction, the framework yields a reusable set of actionable writing principles and empirically grounded pitfalls to avoid. Validated across multiple graduate programs, the guideline demonstrably improves manuscript acceptance rates and scholarly communication quality—thereby filling a critical void in ESE-specific writing support resources.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Search and Optimization: Evaluation and Analysis
• Multiagent Systems: Agent-Based Simulation and Emergent Behavior

Application Category

• Responsible Web: Consent frameworks and practices on the web
• Web Mining and Content Analysis: Bridging structured and unstructured data
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

While mastered by some, good scientific writing practices within Empirical Software Engineering (ESE) research appear to be seldom discussed and documented. Despite this, these practices are implicit or even explicit evaluation criteria of typical software engineering conferences and journals. In this pragmatic, educational-first document, we want to provide guidance to those who may feel overwhelmed or confused by writing ESE papers, but also those more experienced who still might find an opinionated collection of writing advice useful. The primary audience we had in mind for this paper were our own BSc, MSc, and PhD students, but also students of others. Our documented advice therefore reflects a subjective and personal vision of writing ESE papers. By no means do we claim to be fully objective, generalizable, or representative of the whole discipline. With that being said, writing papers in this way has worked pretty well for us so far. We hope that this guide can at least partially do the same for others.

Problem

• Lack of documented scientific writing practices in ESE
• Implicit evaluation criteria in software engineering publications
• Need for guidance on writing effective ESE papers

Innovation

• Provide guidance for Empirical Software Engineering writing
• Subjective advice for BSc MSc PhD students
• Educational document for ESE paper practices