I've noticed people on various web forums asking when they'll see Ooloi render notation. Fair question.

Not yet. Foundation work comes first: the stuff that makes it possible to draw music efficiently. When the rendering implementation begins, the blog will shift from infrastructure to musical decisions: how things sit, straddle, and hang.

Why this approach? This is open-source software built for decades of durability. It's not a commercial product racing as fast as possible to market. No competitors to 'eliminate', no users to 'capture'. Just correct foundations before visible output. Come back in a year or so: the conversation will be about music by then.

What 'correct' means: Nested tuplets to arbitrary depth with exact arithmetic, for instance. No ticks, no fudging, no approximations. The kind of precision that takes time to build right. And tuplets are just one small example.

Single-user first. Ooloi is designed for one person working on one score. Collaboration features are a byproduct of the architecture, not the main focus. The distributed design is about clean separation of concerns and deployment flexibility: collaboration just happens to work because the architecture supports it.

Do I care if people understandably say 'I'll believe it when I see it'? No. 

The work continues.

Research for Ooloi’s input system turned up something I hadn’t expected. Igor Engraver’s Flow Mode – the modal, stateful keyboard entry that defined its way of working – has never been recreated. Not by Dorico, not by Sibelius, not by Finale, nor by any of the open-source projects. Twenty-three years on, the idea has simply vanished.

Flow Mode was straightforward. You pressed “.” once and staccato stayed active; crescendos extended naturally as you continued writing. The commands mapped directly to the symbols – intuitive, fast, and oddly satisfying. When Igor died of business failure in 2001, the method died with it. There is no academic record, no terminology, no sign that anyone even remembered it existed. I had fully expected other programs to have copied this feature; it gives a five- to ten-fold increase in music-entry speed.

Web forums on notation are full of people asking for faster, more fluent keyboard entry, yet without the vocabulary to describe what they want. They are looking for something they have never seen.

So this part of Ooloi isn’t innovation; it’s recovery. The system worked. It was lost for reasons that had nothing to do with design. The decision to re-implement it, and the details, are now recorded in ADR-0032: Ooloi Flow Mode.
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What remains is to implement it – and to find Magnus Johansson, who just might still have the user manual.

Every notation program eventually reaches the same constraint: the interface and the layout engine compete for control of time. When they do, the system freezes.

ADR-0031 defines how Ooloi avoids that conflict. Local actions such as editing, scrolling, and selection remain inside the JavaFX event system, which responds instantly. Network events, like collaborative edits or layout changes, are handled separately, through a dedicated Event Router that never blocks the interface.

For engravers, this means something simple but long overdue: editing and scrolling stay smooth, no matter how large or complex the score, and no matter who else is working on it.

The document doesn’t describe a finished feature; it describes the foundation that makes such responsiveness possible. From this point on, Ooloi’s design rests on a single rule: the interface must never wait for the network, and the network must never interrupt the interface.

Full text → ADR-0031: Frontend Event-Driven Architecture

Finishing the statistics infrastructure naturally led to thinking about the next architectural milestone: the rendering pipeline. This is the mechanism that determines what happens when someone clicks into a score to add a note, and how that change propagates through the system.

The design is complete. That in itself is an important milestone, as this is the very foundation on which Ooloi's performance ultimately depends. Everything hinges upon it.

Traditional notation software recalculates entire scores when a single element changes. Dense passages in works like Strauss's Elektra bring systems to a halt because every operation is sequential and single-threaded. The reason for this is that parallelism is very difficult to do with mutable state, which is the traditional approach. Scalability often becomes an issue, with diminishing returns as a result.

Ooloi takes the opposite approach and chooses the Clojure way instead, with immutable state. With this, it is comparatively easy to distribute formatting work across all available CPU cores and use them fully and linearly.

Every user action – whether adding a single note or adjusting spacing – thus becomes part of a coordinated cascade where each stage can run in true parallel across all available cores.
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The goal is straightforward: responsive editing even in the heaviest repertoire.

ADR-0028 specifies the pipeline in five stages, separating connecting from non-connecting elements and applying a clear fan-out/fan-in pattern.

1. Minimum Widths (Fan-out): Each measure independently calculates spatial requirements – collision boundaries only. Results are immutable and persist until the content changes.
2. Vertical Raster (Fan-in): The MeasureStackFormatter collects widths, generates result rasters, and records both minimum and ideal widths. This prepares the ground for spacing optimisation.
3. Non-Connecting Elements (Fan-out): Independent symbols – noteheads, accidentals, articulations, dynamics – are prepared in parallel. They don't need finalised atom positions.
4. Discomfort Minimisation: Iterative optimisation adjusts widths and system breaks to reduce proportional distortion. No layout changes occur after this stage. From here on, positions are fixed.
5. Connecting Elements​: Slurs, ties, beams, hairpins, and glissandi are drawn only once final positions are known. Sequential coordination ensures continuity across measures and systems.

This separation allows Ooloi to exploit parallelism where possible and enforce order where necessary.

Formatting in Ooloi is plugin-driven. Core elements such as notes and beams are implemented through the same interfaces available to extensions.
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Plugins can participate in different stages depending on their needs:

• Spacing hook (Stage 1) for collision boundaries
• Paint hook (Stage 3) for independent elements
• Connect hook (Stage 5) for elements spanning multiple atoms

Simple articulations may use only the first two; beams may require all three. This uniform model ensures extensibility without compromising performance.

The optimisation engine measures deviation from ideal proportions across measures, systems, and pages. Improvements multiply: small gains in multiple places compound into significant overall reductions. Hard constraints such as manual breaks provide natural stopping points.
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This replaces arbitrary iteration limits with a principled measure of quality.

Claypoole provides efficient thread-pool execution, delivering significant speed-ups over built-in Clojure parallelism. STM transactions keep operations atomic while allowing concurrency inside each stage. Cooperative cancellation ensures that rapid user input remains responsive.
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The system treats a single user as a 'collaboration network of one'. The same infrastructure that supports multi-user editing ensures smooth interaction for individuals.

This pipeline is the structural core that should make scrolling through Elektra or Ligeti's Requiem as fluid as editing a Gnossienne by Satie.
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The specification is complete. Implementation begins as soon as the current phase closes. Ooloi's promise of responsive, professional-scale notation depends on it.

​Scary stuff.

​Full specification: ADR-0028: Hierarchical Rendering Pipeline with Plugin-Based Formatters

After a year of working only on foundations – work that must succeed by disappearing – we are finally ready to turn to visible things. Music, for instance.

This Grafana dashboard shows eighteen minutes of a distributed system handling real client connections. The server sits at a 44 MB baseline and stays there: no memory growth, no thread churn, zero old-generation garbage collections. The jump to 83 MB comes not from client load, but from Grafana itself polling for statistics.

Those numbers matter because they validate architectural decisions made months ago. Functional programming principles, STM coordination, gRPC infrastructure: all the invisible work that had to be right before building anything a user might see.

Stable thread pools. Clean memory management. Efficient client handling. Nothing dramatic – just solid enough to carry what comes next.

The system no longer needs proving. Now it needs notes.

Right. Quick update from the development trenches.

When I completed Ooloi's backend engine in July, starting work on the frontend interface revealed the anticipated cascade of architectural requirements that needed systematic resolution first.

Here's what emerged, in order:

1. Collaborative Undo/Redo Architecture (ADR-0015)
Thinking about frontend-backend relationships immediately raised the question: how does undo/redo work in a multi-client, distributed collaborative setup? The answer required a three-tier architecture separating backend piece changes (coordinated via STM) from frontend UI changes (local to each client).

2. Universal Settings Architecture (ADR-0016)
The insight that there should be no global application settings, only per-piece settings living inside each piece, led naturally to implementing settings not just on the piece level, but across all levels of the hierarchy. Any entity – piece, musician, staff, pitch – can now have configuration attributes via a unified defsetting macro with lazy storage and automatic VPD support.

3. Component Lifecycle Management (ADR-0017)
Multi-scenario deployment demanded rock-solid system architecture using Integrant. This needed to be in a stable architectural form – wiring, lifecycle boundaries, failure modes – before setting up the actual components with proper dependency injection, partial failure handling, structured error codes, the full production suite.

4. Automated gRPC Generation (ADR-0018)
With component architecture sorted, I could tackle the actual gRPC implementation: automating API endpoint generation for native Java interop across hundreds of methods, plus bidirectional communication for real-time collaboration. Manual implementation at this scale would be architecturally impossible.

5. In-Process Transport Optimisation (ADR-0019)
Combined deployments (frontend and backend in same process) were using unnecessary network transport. Implementing automatic in-process gRPC transport delivers 98.7–99.3% latency reduction whilst preserving external monitoring capabilities.

6. TLS Infrastructure (ADR-0020)
Secure connections are essential for distributed deployments – conservatory intranets, corporate environments, cloud SaaS situations. Auto-generating certificates with full enterprise capabilities makes this transparent whilst supporting everything from development to production.

7. Authentication Architecture (ADR-0021)
Finally, distributed deployments require comprehensive authentication and authorisation. Pluggable JWT-based providers scale from anonymous sessions to enterprise LDAP integration. This is fully designed and will be implemented as deployment scenarios require.

Current Status: About 95% of the above is implemented, tested, and production-ready.

Next Steps: Finish the auto-generated gRPC Java interop interface, then create an actual frontend client of the 'Hello World' variety and ensure it runs and communicates across all deployment scenarios.

The rather encouraging discovery throughout this process was how readily the existing functional architecture accommodated these enterprise concerns. Vector Path Descriptors naturally supported universal settings. STM transactions elegantly handled collaborative undo operations. The component system absorbed authentication providers without strain. When features like collaboration or security slide cleanly into place, it's not luck – it means the architecture wanted them there. That's what sound foundations do.

Worth noting: collaboration isn't something tacked on later. It's integral to the architecture from the ground up.
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Right. Back to the gRPC generator.

It's been five months since my last update on Ooloi – or FrankenScore, as it's still known in its pre-release incarnation. This silence wasn't planned; rather, it happened because life got in the way. A demanding day job, a significant career change – we had to liquidate Delegat AB and I had to find a new job as a principal-level AWS Cloud Architect – and other responsibilities all conspired to slow Ooloi's momentum.

​I won't bore you with excuses – sometimes one simply must pause to change course, and I really needed to devote all time and mind space to finding what I hope is my final employment. Now that I've secured a great position with HiQ in Stockholm, I can return to Ooloi with full force.

Five months of relative silence offers time to think. Perhaps there's value in stepping back from the constant pressure to show visible output. In such moments, the architecture is refined not through frantic coding but through careful consideration.
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The journey from Igor Engraver to Ooloi spans decades, and a few months of slower progress hardly register on such a timescale. What matters is that the vision remains clear and the foundation solid.

After all, the whole purpose of the Ooloi project is not to "disrupt the market". Like Octavia Butler's ooloi aliens, we're neither aggressive nor competitive. What is important, however, is doing this right using modern tools. The idea is to create an architecture and a platform that'll last and that musicians and publishers will want to use.

It's also to provide a powerful environment that can be easily extended through any JVM language. Ooloi has a tight, lean and efficient core, organically and seamlessly  augmented by a flora of plugins for any vertical. This would include jazz, early music, tablature, etc - but also commercial plugins to support things like virtual instruments, extremely intelligent playback, or perhaps GenAI used for musical purposes. The idea is to shift the initiative to the users, not to a central committee trying to anticipate user needs.

Ooloi is designed for flexibility and efficiency. Uniting these two aspects sucessfully requires careful architectural design. (And a language like Clojure for the core and the JVM for the plugins.)

With the core architecture stabilising, I'm thinking more about community. Ooloi is intended as an open-source project, a collaborative effort that will benefit from diverse perspectives and expertise.

The extensive documentation work completed earlier – including the architecture decision records, READMEs, and technical specifications – was not merely for my benefit. It prepares the ground for future collaborators, creating a clear map of the territory for those who will join us.
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The website, this blog, and the growing collection of documentation all serve as beacons for those who might be interested in contributing. They signal our commitment to transparency and proper communication – essential ingredients for any successful open-source project.

Five months of comparative quiet doesn't mean I've abandoned ship; it simply reflects the natural ebb and flow of a project undertaken alongside life's other commitments. Ooloi continues to grow, perhaps not as swiftly as in those heady initial weeks, but with steady purpose nonetheless.

I'm reminded of how musical compositions themselves develop – sometimes in great creative bursts, other times through careful refinement of existing material. Both approaches have their place.

To those following Ooloi's progress, thank you for your patience. The work continues, and updates will come more regularly as we approach the milestone of public release. The vision of a modern, efficient, and elegant music notation system – one built on sound architectural principles and open to community collaboration – remains as compelling as ever.
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Until next time (which will be considerably less than five months hence),
/ Peter

In the past weeks, I've been focused on FrankenScore's core architecture. I'm not rushing to open-source this; instead, I'm taking my time to craft a solid platform that will do the heavy lifting for future users and collaborators. All the complexities involving data representation and manipulation in a multi-threaded environment must be solved so collaborators can concentrate on the essentials. Clojure is ideal here, just as Common Lisp was the clear choice for Igor Engraver back in 1996.

Key developments:

1. The API is now fully polymorphic and can be used in the same way internally in the backend as in the frontend. There is a system of pointerless vector path descriptors (VPDs) implemented for this purpose that all API operations can accept as part of their polymorphic setup. I wouldn't be surprised if core collaborators will use the API for internal purposes as well, as it is highly efficient and exposes the underlying functionality in an abstract, domain-specific way. There should be little need to go directly to the underlying data structures, at least not for speed - and certainly not for expressivity. This also bodes well for plugin development in other languages than Clojure, which is an important feature.

2. This beast is fast. Clojure's STM facilities ensure high-speed ACID-compliant transactions with automatic retries. They are also composable. This means that plugins can bombard the backend with hundreds of thousands of mutation requests, for instance to implement MusicXML, with the same efficiency as the pure Clojure backend.

3. Piece Manager Implementation: There's now a Piece Manager, providing functions for storing, retrieving, and resolving pieces from IDs. This allows for multiple clients to work simultaneously on the same piece in a distributed arrangement. The FrankenScore backend can run in the cloud with multiple people collaborating on the same piece. Multiple pieces can be open simultaneously to allow copy-and-paste operations between them.

My next steps involve implementing file persistence (saving and opening music files), as well as tackling printing. These are foundational features, not mere add-ons. Persistence forces a clear definition of the data model and enables easier testing. Printing isn't just about output; it's about representation and serves as a sanity check on the entire system design. Both will likely inform further refinements of the core architecture, potentially revealing oversights or opportunities for optimisation.

Additionally, sequencing is a crucial part of the core platform. And by sequencing I mean support for converting musical representations to timed sound events - though not necessarily via MIDI; a software synth may use direct means of control, for instance. The core sequencer can be used by plugins to generate MIDI, or to input MIDI, but the actual MIDI implementation will be done in the plugin layer. But that's a whole blog post of its own.

The past four weeks have been a whirlwind of productivity. Enjoying a deep creative flow, I've really been wind-surfing through parentheses as I've been working almost around the clock on FrankenScore. The results have been surprising:

• Core Platform: The massively concurrent core engine will be complete in a matter of days, providing a robust, high-performance platform for ACID-compliant transactions.
• API: The polymorphic API is almost finished as well, allowing clients to easily manipulate musical structures in a powerful and intuitive way.
• Documentation and Website: A comprehensive wiki and a live website are now available, serving as central resources for the project.

This initial rush has successfully got FrankenScore off the ground, building a strong foundation in record time. However, as my holiday draws to its close and my day job with Delegat AB resumes, the pace will inevitably slow down a little.

The timeline for releasing FrankenScore as open source depends on several factors, including the presence of internal collaborators before the public release. While the foundational work is largely complete, the project will continue to evolve at a steadier pace.

If I'm left entirely to my own devices without any pre-release assistance, I should say the public open source release of Ooloi 0.x will happen in about a year's time. With collaborators, in about six months or so. But this is difficult to gauge with any exactness, as there are so many variables involved.

Also, after going public, remember Ooloi won't be finished by any means. That's when the journey begins in earnest, travelling the distance from Ooloi 0.x to 1.0. But then we'll be travelling as a group.

Anyway, there'll be regular status and road map updates on this blog. I'll keep you posted.

FrankenScore is still private. There is a number of things that need to be in place before the project can go public and I can start inviting collaborators, so let's touch a little on names, releases and versions.

At this stage I'm finalising the robust, high-performance platform for ACID-compliant transactions which forms the basis of everything in FrankenScore and is manifested through the backend API.

FrankenScore becomes Ooloi when released as open source. But the first release doesn't need to be Ooloi 1.0, which by definition would be feature-complete. In fact, it should be Ooloi 0.n with an n as low as possible, meaning it's best to go public as early as possible, yet feature-complete enough so Ooloi's promise is immediately apparent.

Here's a very rough project plan:

1. Finalise the API (nearly done)
2. Implement File Persistence using Fressian (saving and loading pieces)
3. Implement gRPC Layer and Event Handling (for communication between the backend and the frontend)
4. Create Initial Frontend with Hello World Window (proof of concept)
5. Implement printing in the frontend client (of the Hello World Window)
6. Implement enough of the frontend/backend interaction so that a score can be set up and simple elements can be entered and manipulated. This is an complex. multi-step process that also involves setting up event handling in the frontend. It's the basis for everything that is to come and must be rock solid.
7. Implement measure reformatting locally for measures according to a simple linear method that will be upgraded later
8. Implement backend reformatting and reflow of measures over systems and pages
9. Iteratively add more notational elements and features until Ooloi 0.n can be released, meaning that the project is released as open source.
10. After the release, adding more notational elements continues in parallel with the remaining points:
11. Implementation of a more advanced measure formatting algorithm
12. Implementation of the plugin system.
13. Implementation of an open source plugin for simple MIDI in- and output.
14. Implementation of an open source plugin for reading and writing MusicXML files.
15. When all notational elements are supported, Ooloi 1.0 can be released.

​So, point 9 represents the point where the project goes public and Ooloi 0.n appears. It remains to be seen how feature-complete the notation must be to confidently take that step.

However. There might of course be room for collaborators in the project before the public release as open source, as there are points in the above list that cover isolated features that could be delegated to an experienced Clojure programmer. Hmm. Let's think about that.