SE Journals in 2036: Looking Back at the Future We Need to Have
Written from a 2036 perspective, this paper reflects on how the Software Engineering journal community overcame its 2025 scalability crisis by forming a unified alliance, reforming broken peer-review mechanisms, and shifting cultural paradigms to ensure a sustainable future for research publication.
Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
The Story: How Software Science Stopped Drowning in Paperwork
Imagine the world of software research in 2025 as a giant, chaotic airport.
Thousands of researchers (the passengers) are trying to board a plane (get published). But there are only a few hundred gate agents (reviewers). The agents are exhausted, the lines are miles long, and the system is broken. Because there are so many people and so few agents, getting on the plane feels less like a fair test of your ticket and more like a lottery. If you get lucky, you fly. If you don't, you wait forever, even if your idea is brilliant.
The authors of this paper (a group of top journal editors) are writing from the year 2036. They are looking back at that chaotic airport and explaining how they completely redesigned the entire transportation system to save the industry.
Here is how they fixed it, using six simple steps:
1. The "Alliance": Stop Fighting, Start Sharing
The Problem: Before 2026, every journal was like a rival airline. If a paper was rejected by one, the author would just run to the next airline, hoping for a different result. This wasted everyone's time. The reviewers were stuck in silos, and no one knew who had already reviewed what.
The Fix: The top journals formed a United Alliance. Imagine all the airlines merging into one giant network.
- Portable Reviews: If a paper was rejected by one journal, the reviews traveled with it. The next journal could see the history immediately. No more "resetting" the clock.
- Shared Credit: Reviewing a paper used to be a thankless volunteer job. Now, it's like earning frequent flyer miles that count toward your career. If you review papers, it actually helps you get hired or promoted.
2. The "Lottery": Stop Trying to Judge Everything
The Problem: With millions of papers, trying to give every single one a full, deep human review is mathematically impossible. It's like trying to read every single book ever written to find the best one.
The Fix: They introduced a Lottery System.
- First, a fast, automated check (or a quick human glance) filters out the obvious junk.
- The "good" papers get a guaranteed deep review.
- The "okay" papers enter a lottery. If you win the lottery, you get a full review. If you don't, you don't.
- Why this works: It stops the stress of trying to rank every single paper perfectly. It accepts that some good work will be missed, but it ensures the system doesn't collapse under the weight of trying to judge everything.
3. The "Traffic Cop": Robots Do the Boring Stuff
The Problem: Human reviewers were wasting hours checking if a paper had a table of contents, if the code was broken, or if the math was formatted correctly.
The Fix: They hired AI Traffic Cops.
- Before a human ever sees a paper, a robot checks the basics: "Is the code runnable? Is the data there? Does it have a conclusion?"
- If the paper fails these checks, it's sent back immediately.
- If it passes, the human reviewers only have to do the hard part: judging the ideas and the logic. This frees up the experts to think deeply instead of fixing typos.
4. Two Speeds: The "Cathedral" and the "Bazaar"
The Problem: The old system tried to force every type of research into the same slow, heavy box. Deep, life-changing scientific discoveries were stuck waiting for years, while quick, useful tools were ignored because they weren't "deep" enough.
The Fix: They built two different lanes:
- The Cathedral (Deep Science): For massive, groundbreaking discoveries. These are slow, rigorous, and require extreme depth. Think of building a massive cathedral; it takes years, but it lasts forever.
- The Bazaar (Agile Science): For quick, useful tools and fast experiments. These are published quickly, like a busy market stall. You don't need a 50-page thesis to sell a new tool; you just need to show it works.
- The Result: Deep scientists can focus on quality without rushing, and fast innovators can share their work immediately without waiting for a slow committee.
5. Unbundling: Breaking the "Monolith"
The Problem: In the old days, a research paper was a "monolith"—a giant, heavy package containing the idea, the method, the results, and the conclusion all stuck together. If one part was weak, the whole thing was rejected.
The Fix: They unbundled the package.
- You can now publish just the Idea (a Vision Statement).
- You can publish just the Method (how you did it).
- You can publish just the Results (what happened).
- Why this helps: It's like buying ingredients separately instead of a pre-made meal. A statistician can review just the math without reading the whole story. A tool developer can share just the code. It makes the process faster and more flexible.
6. Escaping the "Benchmark Graveyard"
The Problem: Researchers were obsessed with "leaderboards." They would take the same old test data (the benchmark) and try to squeeze out 1% more accuracy. It was like running on a treadmill that never moves. They were winning games, but not solving real problems.
The Fix: They stopped rewarding small improvements on old tests.
- Now, to get published, you have to break the cage. You must use messy, real-world data, or prove that the old tests were wrong.
- Instead of trying to climb a ladder that goes nowhere, researchers are now encouraged to build a new ladder entirely.
The Big Picture
By 2036, the editors look back and say: "We stopped guarding the gate and started building a conversation."
In the past, the system was about Quality Control by Guarding (keeping bad stuff out, which took 90% of the energy).
Now, the system is about Quality Control by Dialog (improving the good stuff, which takes 90% of the energy).
They realized that science isn't about perfect paperwork; it's about sharing ideas, fixing tools, and solving real problems. They stopped treating researchers like applicants in a bureaucracy and started treating them like a community of explorers.
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