πŸ“– Keshav Three-Pass Reading Log

Keshav’s Three-Pass Method (S. Keshav, University of Waterloo, 2007):

  • Pass 1 (5–10 min): bird’s-eye view using title, abstract, intro, headings, conclusions
  • Pass 2 (≀1h): grasp content, note figures, mark unread references
  • Pass 3 (4–5h): re-implement / virtually reconstruct the paper

[!info] Overview

Used in MIT AI Lab Working Paper 316 (β€œHow to Do Research”) as reading guidance for graduate students. Integrated here as the PUMA paper-reading framework.


Reading Queue (Pass 1 pending)

TABLE title AS "Title", first-author AS "Author", year AS "Year", relevance AS "⭐"
FROM #literature
WHERE status = "to-read"
SORT relevance DESC

In Progress (Pass 2)

TABLE title AS "Title", first-author AS "Author", year AS "Year"
FROM #literature
WHERE status = "reading"

Completed β€” Ready for Permanent Notes (Pass 3 done)

TABLE title AS "Title", first-author AS "Author", year AS "Year", topic AS "Topic"
FROM #literature
WHERE status = "reviewed"
SORT year DESC

All Literature

TABLE title AS "Title", first-author AS "Author", year AS "Year", status AS "Status", relevance AS "⭐", topic AS "Topic"
FROM #literature
SORT relevance DESC, year DESC

Manual Log (for papers not yet in Dataview)

PaperAuthorYearPass 1Pass 2Pass 3Permanent Note
Reproducibility of LLM Studies in SEAngermeir2025βœ…βœ…βœ…PN-KeyConcepts-Agents-Reproducibility-RedTeam
CoGEE: Story Point EstimationTawosi2024βœ…βœ…πŸ”„PN-IssueTriage-StoryPoints
How Big Things Get DoneFlyvbjerg2023βœ…βœ…βœ…PN-IssueTriage-StoryPoints
Chain-of-Thought PromptingWei2022βœ…βœ…βœ…PN-CoT-FewShot-Prompting
TAWOS DatasetTawosi2022βœ…βœ…βœ…LN-Datasets-JiraSR-TAWOS
Design Science in IS ResearchHevner2004βœ…βœ…βœ…PN-DSR-SLR-Methods
Cognitive Agents for Agile PMSpichkova2025βœ…πŸ”„β¬œβ€”
Jira SR DatasetOrtu2015βœ…βœ…βœ…LN-Datasets-JiraSR-TAWOS
PM-LLM-BenchmarkBerti2024βœ…πŸ”„β¬œβ€”
AI in Project Management 2019–2024Manzoor2025βœ…βœ…πŸ”„β€”
Request Formats and Effort EstimationCalikli2025βœ…βœ…βœ…PN-CoT-FewShot-Prompting
Energy and Policy for Deep LearningStrubell2019βœ…βœ…βœ…Carbon-Tracking-Log
Experimentation in SEWohlin2012βœ…βœ…βœ…PN-Wilcoxon-FINER-Cornell-PRISMA
Local LLMs for Sprint EstimationYonathan2025βœ…πŸ”„β¬œβ€”
Language Models are Few-Shot LearnersBrown2020βœ…βœ…βœ…PN-CoT-FewShot-Prompting

Legend: βœ… Done Β· πŸ”„ In Progress Β· ⬜ Not started


Keshav Pass-1 Quick Template

For fast capture during Pass 1, use:

**Paper**: [Title]
**Author**: [Last name, Year]
**Category**: measurement | analysis | description | proposal
**Context**: Related to [papers/theories]
**Correctness**: Assumptions [seem valid | questionable because...]
**Contributions**: 1) ... 2) ... 3) ...
**Clarity**: [clear | confusing | jargon-heavy]
**Decision**: Read Pass 2? [YES / NO β€” reason]

Permanent Notes Generated from Reading

LIST
FROM "30 - Permanent"
WHERE type = "permanent"
SORT file.ctime DESC
LIMIT 20