Writing Advice
This page is a practical guide for students writing empirical software engineering papers, theses, and dissertations. It is intentionally link-heavy: the goal is to help you find strong resources for each section of a paper and avoid preventable reviewer frustration.
I use this page as a compact writing companion. The advice below is not a universal formula, but it reflects the patterns I recommend most often in supervision and reviewing.
Table of Contents
Research & Discovery
My tip: If you discover papers only at the end, your writing will sound late and defensive.
Good writing starts before writing. Use discovery tools early to understand clusters, competing schools of thought, and which papers are central enough that reviewers will expect you to know them.
- Connected Papers for visualizing citation neighborhoods and research clusters.
- ResearchRabbit for AI-assisted discovery of related work and forward/backward citation exploration.
- Google Scholar for checking who cites a paper, how terminology varies, and whether your framing is still current.
Abstract
My tip: The abstract is a trailer, not a summary. Show why the study matters before you drown the reader in detail.
The abstract is the first quality filter for most readers and reviewers. In empirical software engineering, structured abstracts are often the safest option because they force clarity on motivation, method, results, and implications.
- Structured abstracts guide from EBSE Durham: https://ebse.webspace.durham.ac.uk/structured-abstracts/
- Instructions from Information and Software Technology: https://www.elsevier.com/journals/information-and-software-technology/0950-5849/guide-for-authors
- Psychology-oriented advice on abstracts: http://www.unice.fr/sg/authors/abstracts.htm
- Impact-focused advice from Enago: https://www.enago.com/academy/tips-writing-impactful-structured-abstract/
Broken-link audit note: the old Durham PDF now redirects to the EBSE site root, so I replaced it with the live Structured Abstracts page.
Back to TopIntroduction
My tip: A strong introduction narrows the reader's world step by step until your research question feels inevitable.
A good introduction helps the reader understand what is known, what is missing, and why your study is worth reading now. The CARS model is still one of the most useful scaffolds for this.
- USC Writing Guide on the CARS model: https://libguides.usc.edu/writingguide/CARS
- Updated Lund/AWELU introduction structure guide: https://www.awelu.lu.se/writing/writing-stage/structuring-the-text/structure-of-introductions/
- Swales-inspired reference PDF: https://researchwrit.files.wordpress.com/2015/01/article_swales_cars-model.pdf
Broken-link audit note: the old Aalto URL is no longer stable, so I replaced it with the current AWELU/Lund guide that covers the same introduction logic.
Back to TopResearch Design
My tip: Reviewers forgive limits more easily than vagueness. Be explicit about what you did, why you did it, and why the design fits the question.
The research design section explains how the study was structured and why the chosen method is appropriate. In software engineering, it helps enormously to align the study with method-specific guidance and community reporting expectations.
- Experimentation: Experimentation in Software Engineering
- Case studies: Case Study Research in Software Engineering
- Design science research: Design Science Research in Information Systems
- Action research: Action Research in Software Engineering
- ACM SIGSOFT Empirical Standards: https://www2.sigsoft.org/EmpiricalStandards
Threats to Validity
My tip: Threats to validity are not an apology section. They are where you show intellectual honesty and methodological maturity.
For empirical software engineering papers, this is a high-priority area. Good validity discussion explains which risks mattered, how they were handled, and what uncertainty remains.
- Feldt & Magazinius classification: Validity Threats in Empirical Software Engineering Research - An Initial Survey
- ACM SIGSOFT empirical standards validity guidance: Empirical Standards PDF
Results
My tip: The results section should answer the research questions, not merely replay the analysis pipeline.
The results section depends strongly on method, but in all cases it should stay disciplined: present findings clearly, separate interpretation from reporting when possible, and tie results back to your research questions.
- San Jose State writing guide: https://www.sjsu.edu/writingcenter/docs/Results%20Section%20for%20Research%20Papers.pdf
- Elsevier advice on results sections: https://scientific-publishing.webshop.elsevier.com/manuscript-preparation/how-to-write-the-results-section-of-a-research-paper/
Discussion
My tip: The discussion should explain why the results matter, not just say that they are interesting.
This is where you connect results to prior work, implications, and interpretation. Good discussion is analytical rather than repetitive.
- Sacred Heart discussion guide: https://library.sacredheart.edu/c.php?g=29803&p=185933
- USC discussion guide: https://libguides.usc.edu/writingguide/discussion
- Hands-on advice from Bioscience Writers: https://www.biosciencewriters.com/How-to-Write-a-Strong-Discussion-in-Scientific-Manuscripts.aspx
Conclusions
My tip: Conclusions should leave the reader with a clean answer to “So what?” and “What now?”
Conclusions are often too vague or too repetitive. A good conclusion should state what was learned, why it matters, what remains uncertain, and what should happen next.
- Practical step-by-step guide: https://www.wikihow.com/Write-a-Conclusion-for-a-Research-Paper
- USC conclusion guide: https://libguides.usc.edu/writingguide/conclusion
Examples
My tip: If your example needs a long apology before the reader understands it, it is not yet a good example.
Examples are important throughout scientific texts, but they are often neglected or overcomplicated. Small, precise examples usually teach better than ambitious ones.
- Minimal reproducible examples: https://stackoverflow.com/help/minimal-reproducible-example
- Short, self-contained example concept: http://www.sscce.org/
Templates & Tools
My tip: Good tooling does not write the paper for you, but it removes friction that otherwise steals time from thinking.
Use templates and reference tools early. They save formatting effort and reduce last-minute mistakes.
- Overleaf IEEE official templates: https://www.overleaf.com/gallery/tagged/ieee-official
- Overleaf ACM official templates: https://www.overleaf.com/gallery/tagged/acm
- Zotero getting started: https://www.zotero.org/support/getting_started
AI Ethics & Integrity
My tip: If you use an LLM, treat it like an unreliable assistant, not like an author and definitely not like a source.
Generative AI can help with brainstorming, outlining, and language cleanup, but it can also introduce fabricated claims, broken references, and policy violations. Students should always check venue and publisher policies before submission.
- ACM FAQ and policy guidance on generative AI: https://www.acm.org/publications/policies/frequently-asked-questions
My recommendation: disclose meaningful AI use when required, never invent citations, never let generated text bypass verification, and never assume that fluent text is accurate text.
Back to TopOther Resources
My tip: Keep a small personal toolkit of resources you actually return to. A useful shortlist beats a huge forgotten bookmark folder.
- Lund University resource on academic popular science writing: https://awelu.srv.lu.se/genres-and-text-types/writing-in-academic-genres/popular-science-writing/
- Checklist for academic texts: http://www2.elc.polyu.edu.hk/CILL/essay_checklist.htm
- How to rescue a problematic article or chapter: https://medium.com/advice-and-help-in-authoring-a-phd-or-non-fiction/seven-upgrade-strategies-for-a-problematic-article-or-chapter-3c6b81be9aa2
- Swedish-English dictionary for higher education terms: https://www.uhr.se/publikationer/svensk-engelsk-ordbok/
- BBC course on academic writing: https://www.bbc.co.uk/learningenglish/english/course/go-the-distance/unit-1/session-4
Books
My tip: Read writing books with a pen in hand. If you do not translate advice into your own sentences, it stays theoretical.
These are some of the books and resources that helped me get better at academic writing.
Stylish Academic Writing by Helen Sword
A comprehensive guide to improving academic writing style without losing rigor.
Don't Be Such a Scientist by Randy Olson
A practical guide to scientific storytelling and audience engagement.