Repository mining study, 41,000 pull requests, 14 repositories

Software engineering research poster example

A software engineering research poster has to make a mined dataset readable from two metres away. This A0 landscape board does it for code review: 41,000 pull requests in 14 open source repositories, with the median wait for a first review falling from 31 hours to 22 over three years, shown as a four point timeline across the top.

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The whole board

The poster at full size, exactly as it prints. Every number, citation and caption on it was written for this example, so the layout is being judged on real content.

CIT
How long does a pull request wait for a first review? 41,000 pull requests in 14 open source repositories over three years
L. Okafor ¹, M. Brandt ¹
1 School of Computing, Corrowind Institute of Technology
31 h
Year 1, 2023
Median first review, 12,400 pull requests
27 h
Year 2, 2024
Median first review, 13,700 pull requests
22 h
Year 3, 2025
Median wait, 14,900 pull requests
29%
Three year fall
Nine hours off the median, 31 to 22
Abstract
We timed the wait from opening a pull request to its first human review across 41,000 pull requests in 14 repositories, 2023 to 2025. The yearly median fell from 31 to 27 to 22 hours, but large projects still wait longest.
METHODS
Repositories. 14 open source repositories from a public package index, each with at least 50 merged pull requests in every quarter of 2023 to 2025.
Pull requests. 41,000 opened in the window: 12,400 in 2023, 13,700 in 2024 and 14,900 in 2025. Drafts count from when they were marked ready.
Measure. Hours from opening to the first approval, change request or inline comment by a person other than the author. Bots do not count.
Exclusions. Bot pull requests and those closed by their author inside one hour were removed before the 41,000 were counted.
Analysis. Medians by quarter, by year and by size band on contributor count. Medians, because a few pull requests wait for months.
REFERENCES
1.Ilunga, P. and Sorensen, K. (2024) First response time as a health signal for open source projects. Journal of Software Practice, 31(2), 118 to 140.
2.Moreau, D. (2025) Review queues and owners files in large repositories. Empirical Software Studies, 12(1), 55 to 79.
3.Okafor, L. (2025) Measuring review latency without counting bots. Corrowind Computing Report 4, 2025.
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Figure 1. Median hours to first review by quarter, quarters 1 to 12 running January 2023 to December 2025, all 14 repositories pooled.
Source: public repository event logs, 41,000 pull requests.
Results
The pooled median wait for a first review was 31 hours in 2023, 27 hours in 2024 and 22 hours in 2025. The quarterly medians fall in ten of eleven steps and never rise, from 33 hours in the first quarter to 20 in the last. By repository size the picture splits. Six small repositories with under 50 contributors carried 7,800 pull requests and reached a median of 14 hours in 2025. Five medium repositories with 50 to 200 contributors carried 14,600 and reached 20 hours. Three large repositories with over 200 contributors carried 18,600 pull requests, close to half the total, and still waited 27 hours. Every band got faster over the three years, so the pooled fall is not a shift in which repositories were busy. Weekend pull requests waited about 9 hours longer than weekday ones in every year.
22 hours
median first review in year 3
Down from 31 hours in 2023 and 27 hours in 2024, 14,900 pull requests in 2025
Key finding
Reviews got faster every year, but large repositories still wait almost twice as long as small ones.
Discussion
The fall is steady rather than sudden, which points away from one tool or one policy change and towards habits spreading slowly. Small repositories are fastest because one or two maintainers see every pull request. Large repositories route work through owners files and review queues, and the 27 hour median says the queue is still the constraint. Two limits matter. A first review is not a merge, so a fast first comment can hide a slow decision. And 14 repositories that stayed active for three years are not a random sample of open source.
Median first review fell from 31 to 22 hours over three years
Small repositories 14 hours, large ones 27 hours in 2025
Every size band got faster, not just the busy ones
Weekend pull requests waited about 9 hours longer

Block by block

What each block on the board is for, in the order a reader walks it.

Title band and two authors
The title asks the question as a reader would, how long a pull request waits for a first review, and names 41,000 pull requests and 14 repositories so the scale is set at once.
Findings timeline
Four points: 31 hours in 2023 on 12,400 pull requests, 27 hours in 2024 on 13,700, 22 hours in 2025 on 14,900, and the 29% fall from first year to last.
Abstract and methods
A short abstract, then five labelled entries: how the 14 repositories were chosen, the yearly pull request counts, what counts as a first review, what was excluded and why medians were used.
Figure 1, median hours by quarter
Twelve bars, one per quarter from January 2023 to December 2025, falling from 33 hours to 20. The design draws this figure as bars, so quarters are numbered 1 to 12 and the caption gives the dates.
Results, with the size table in prose
This design has no table block, so the three size bands go into the results text: small repositories 14 hours, medium 20 and large 27 in 2025, with their pull request counts.
Key number and key finding
The stat block holds 22 hours, the 2025 median. The callout says reviews got faster every year but large repositories still wait almost twice as long as small ones.
Discussion, key points and references
Why the fall is gradual, why large repositories lag, and two limits: a first review is not a merge, and survivors are not a random sample. Four checked points and three references close the board.

What makes this board work

The timeline carries the headline

Four large numbers across the top, 31 h, 27 h, 22 h and a 29% fall, give the whole result before a reader reaches a paragraph. Each carries its year and pull request count underneath, so the denominator travels with the number.

Medians, and the reason for them

Review waits have a long tail: a few pull requests sit for months. The methods block says why medians were used, which answers the first question a software audience asks about this kind of data.

The pooled trend is checked against size

A falling pooled median could just mean busy repositories got quieter. The results split 41,000 pull requests into small, medium and large repositories, 7,800, 14,600 and 18,600, and show every band got faster.

Questions people ask

What should a software engineering research poster show first?

The one number your study changes and its denominator. Here that is the median first review time by year, 31, 27 and 22 hours, each with its pull request count. Mining studies often lead with the pipeline, but a reader at a poster session decides in seconds whether to stop, and a pipeline diagram rarely makes them.

How do I describe a mined dataset on a poster?

Give the selection rule, the window, the count and the exclusions in one block. This board says the 14 repositories each merged at least 50 pull requests in every quarter, the window is 2023 to 2025, the total is 41,000, and bot pull requests and quick self closes were removed before counting.

Should I report means or medians for review times?

Medians, and say why on the board. Review times are skewed: most pull requests get a response within a day or two, and a handful wait for months, which drags a mean far above what a typical contributor experiences. This board states the reason in its analysis entry so nobody has to ask.

Can this layout hold a table of repositories?

Not as a table. Only three of the forty poster designs carry a table block, and this timeline layout is not one of them, so the three size bands are written into the results section. If your repositories need a full table, pick one of the table led designs instead and keep the timeline numbers in the abstract.

Why is the quarterly figure drawn as bars?

Each figure block has its chart kind set by the design, and this one is a vertical bar chart. Twelve bars still read as a trend when they fall steadily, as these do from 33 to 20 hours. Short tick labels, 1 to 12, keep the axis clear of the legend, and the caption carries the dates.

How big does a landscape A0 board export?

The working canvas is 2,340 by 1,656 pixels and image export captures it at twice that, so about 4,680 by 3,312 pixels, close to 100 dots per inch at full A0 width. Text stays sharp at reading distance. There is no bleed, crop mark or CMYK option, so a print shop that needs them will add them.

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