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Re-Reading Read

2/12/2025

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​I'm re-reading Gardner Read's Music Notation from 1974. I bought my copy in 1977, which makes me 16 at the time – old enough to take it seriously, young enough to believe comprehensive understanding was achievable through diligent study. Later, this book would influence Igor Engraver's formatting decisions, though not always in ways I'd care to defend today.

What strikes me now is what Read doesn't cover. There's nothing about ledger line thicknesses, actual distances in spaces between noteheads and accidentals, sit-straddle-hang rules, slur curvatures, or tie formatting. None of the engraver-level detail that Elaine Gould's Behind Bars (2011) and Ted Ross's The Art of Music Engraving & Processing (1970, but I didn't discover it until much later) document so comprehensively. Read gives you musical orthography – what symbols mean and when to use them – but not typographical execution.

What Igor Got Away With

​When Magnus Johansson published examples of Igor's output on NOTATIO recently, I experienced that particular species of discomfort that comes from seeing your 25-year-old work through 2025 eyes. The ledger line thicknesses were wrong. The beam slants were inconsistent. We clearly knew nothing about sit-straddle-hang.

So what made Igor well-received? Not typographical perfection, that's certain.

First, integrated parts. Only Composer's Mosaic had them at the time, and Igor had them long before Finale or Sibelius. This alone solved a workflow problem that cost professional copyists days of manual labour.

Second, the user experience didn't fight the music. After spending years with Finale on The Maids – full score, parts, piano reduction – I ended up hating Finale. I've called it 'as user-friendly as a cactus' more than once. Creating something that didn't actively work against the creative process was evidently a sufficient innovation.

Third, note entry was fast and powerful. The modal Flow Mode interface that would later vanish completely from notation software for 23 years gave professional users substantial note entry and editing speed improvements. When you're saving many hours per score, you'll forgive a few ledger lines being slightly too thin – and there was a setting for that anyway.

Fourth, we had stellar MIDI playback and a semantic model that made things consistent rather than a collection of rules-of-thumb. That alone provided predictability. And everything could be adjusted – the absence of automatic sit-straddle-hang rules just meant more manual interventions.

The landscape in 1996 made these trade-offs reasonable. The streamlined experience outweighed what we today immediately see was missing.

The Bar Has Been Raised

​2025 is not 1996.

The leading programs have improved considerably since 1996. They're genuinely competent at beam placement and formatting – not flawless, but competent enough that egregious errors are rare.

A new program entering this landscape must get the foundations correct from day one. Beam placement, slurs, ties, accidental positioning – these must be flawless, not 'good enough to ship'. The field has progressed, and users' baseline expectations have risen accordingly.

This is as it should be. But there's something deeper that hasn't been solved.

The Semantic Deficit

Here's what I've stated repeatedly: Ooloi is not about 'disruption' or market share. The entire motivation is to escape what commercialism leads to and create something modern, scalable, and architecturally correct from the ground up. Why? Because music notation is an extremely messy and difficult field of computation, and it requires correctness to address its long-standing problems of scalability and accuracy.

This starts with internal representation.

The old programs – and many modern ones still in broad use – were all based on a paradigm inherited from MIDI. MIDI was the standard for pitch representation at the time, and all notation software needed MIDI output for playback anyway. This meant pitches were MIDI numbers (0-127) with attachments indicating whether they were sharp or flat. Figuring out musical context – for instance, to determine what accidentals to draw – had to be derived from something with no connection to musical structure whatsoever. It had to be inferred from context each time.
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That's at the root of the problems programs still have with accidentals. The internal representation is designed around the presentation – the visual aspect – not around the meaning, the semantics, of the music.

And of course, MIDI has no concept of microtonality, which is why notation programs struggle with microtonal entry, presentation, and playback.

Furthermore, for duration, these early programs based their rhythmic representation on a raster of 480 subdivisions – ticks – of a quarter note (TPQN: Ticks Per Quarter Note). A quarter note is 480 ticks long in some arbitrary tempo, an eighth is 240, and so forth. This is the equivalent of pixels in a JPEG, which means there's a limit to what the raster can represent.

The number 480 isn't evenly divisible by very many factors. This leads to all the problems we're still seeing in music notation programs. Various kinds of duct tape – rules of thumb, arbitrary rounding, tolerance spans – have to be used. When tuplets are nested, the approximation errors compound. We're still seeing the effects of this unfortunate MIDI heritage in 2025.

A MIDI-derived representation centred on presentation – the visual aspect – will always have difficulty interpreting what the music means. That interpretive layer is essential for presenting it correctly and consistently.

For that, you need a semantic model, which turns this on its head. The representation is 'musically correct' and detached from its presentation. Once this is in place, you can make informed decisions instead of relying on rounding and rules-of-thumb. It also makes things like playback trivial, which in MIDI-based systems is paradoxically complex.
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Igor's Semantic Foundation

​Igor Engraver was, I believe, one of the first programs – possibly the very first – to use a fully semantic internal model. It was also the first to model the real world by using Musicians playing Instruments, which allowed new and powerful abstractions.

It's interesting that Dorico also has this arrangement, though they call their Musicians 'Players' – but it's the same thing. I have no idea whether Daniel Spreadbury was inspired by Igor here, but it's not unlikely. On the other hand, introducing Musicians/Players into the representational hierarchy is a logical choice once you commit to semantic modelling.

I'm not certain Dorico has a fully semantic model, though it's closer than any other program I know of. LilyPond doesn't, despite its sophisticated batch nature. One telling diagnostic: look at how they handle remembered accidentals for grace notes, and how they treat them rhythmically. Another: how durations are represented. If they're floating-point numbers, they're approximations. For true accuracy in all situations, you need rational numbers – infinite precision, always correct. Anything else eventually leads to problems.

If a program has problems with edge cases or behaves inconsistently when dragging things cross-staff, check how it represents pitch and duration. If floating-point is involved, or rasters of ticks (480 or otherwise), the representation isn't semantic. The program might still handle 95% of hairy accidental placements competently. But when it starts having problems with tied notes across key changes or grace notes at measure starts, you know rules-of-thumb are involved – which means results can never be fully deterministic.

Ooloi is fully semantic with the explicit intention of making results fully deterministic.

This might not matter if you're satisfied with what capable commercial programs achieve today. That's legitimate – they handle about 95% of cases well. But if you depend on the remaining 5%, or if you spend your days as an engraver adjusting those 5% repeatedly, then you understand what I mean by deterministic results saving considerable time.

This Time: No Compromises

Now, on to Gould and Ross – books that weren't available when Igor was created. We'd inevitably have implemented their specifications had we had time. But as you know, I was ousted from my own company by venture capital pop zombies before we could. They thought guitar tablature was more important than correct engraver-level beaming.

This time, there will be no guitar tablature at the expense of correct beaming and orthography. All things in their proper order. Lead sheets are kid's stuff, comparatively speaking, and will be added later as plugins.
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When Four Systems Align

20/11/2025

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I've just completed ADR-0035 on remembered alterations: the system determining when accidentals print in music notation. The client's first window won't open for yet a few weeks, so there's no technical pressure for this work. But conceptually, it felt necessary. Pitch representation, time signatures, key signatures: all complete. Before proceeding to visualization, I needed to see these systems work together. I needed conceptual closure.

The result surprised me. Not because it works (of course it works), but because of how naturally the pieces fit.

The Actual Problem

Accidental rendering isn't 'print a sharp when the note differs from the key signature'. Accidentals have memory. Once F♯ appears in a measure, subsequent F notes remember that sharp until the barline. This memory flows left-to-right through musical time, independent of visual layout.

The complexity emerges in multi-staff instruments. Piano, harp, organ, even choirs: all staves share accidental memory. A sharp in the treble affects naturals in the bass. Multiple voices complicate further; temporal sequence follows rhythmic position, not staff order or voice structure. You need a model where musical time is explicit and independent of how things appear on the page.

This is precisely the problem that four separate architectural decisions, made for entirely different reasons, were built to solve.

What Was Already There

Pitch representation (ADR-0026): Letter names, octaves, accidental keywords. Built for memory efficiency and canonical identity. No thought given to accidental rendering at the time.

Time signatures (ADR-0033): Metric positions as rationals (1/4, 3/8, 5/16) providing exact temporal coordinates for every event. Built to handle irrational and additive meters correctly. Again, no consideration of accidental logic.

Key signatures (ADR-0034): Define which accidentals are 'normal' for a given context. Standard keys, keyless modes for keyless music, per-octave microtonal signatures for contemporary notation. Built as baseline, not as accidental memory.

Timewalk (ADR-0014): Traverses music in strict temporal order. Built for efficient general-purpose traversal. The musical timeline made explicit as implementation detail.

Four systems, four separate problems, no coordination between them.

The Single Comparison Rule

With those foundations in place, remembered alterations became straightforward. The algorithm is a wave pattern flowing left to right:
  1. Start of measure: Initialize to key signature baseline
  2. Process each note: Compare against current remembered state
  3. Update after each note: This accidental becomes new remembered state  
  4. Measure boundary: Reset to baseline

Decision rule: A note requires a printed accidental when its accidental differs from the current remembered state for that letter and octave.

That's it. This single rule handles both required accidentals (contradicting key signature) and courtesy accidentals (restating after alteration). No special cases. No heuristics. The data structure stores only deviations from baseline; eight entries typical versus seventy for full representation.

Grace notes participate fully in the memory system. Tied notes bypass conditionally with position-based French tie distinction. Simultaneities detect conflicts where the same letter has different accidentals at the same moment. Cross-octave courtesy accidentals work through letter-first grouping that makes the lookup O(m) where m equals octaves for that letter, not O(k) for all octaves globally.

All of this through the same mechanism. The complexity isn't in the algorithm; it's in having the right foundations.
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The Mental Shift

Timewalk changed how I think about notation problems. Instead of 'iterate over notes and check context', the remembered alterations pipeline is stream transformation:
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​Each stage is pure transformation. Grace notes are repositioned to exact temporal locations based on tempo-dependent duration (85ms default, compressed on collision). Simultaneities group by rhythmic position. Conflicts detect same-letter different-accidentals at the same moment. The reducer threads remembered state through the stream, accumulating decisions.

This pattern will handle dynamics, articulations, phrase marks: any notation requiring temporal context. The abstraction scales because the foundations were right to begin with.

What This Actually Reveals

​The algorithm produces semantic decisions about accidental requirements, independent of layout. These decisions are deterministic: same music, same decisions, always. They're layout-independent: work identically across all visual representations. They're configurable: house style settings modify behaviour without code changes. They're correct: edge cases handled through the same mechanism as common cases.

But here's what matters: I didn't design these four systems to work together. I designed each to solve its own problem correctly. The alignment emerged because correct solutions in related domains tend to compose naturally.

This is evidence. Either the domain model reflects musical reality accurately, or I've successfully imposed coherent structure on chaos. Those are different conclusions with different implications, but both suggest the foundations can carry what comes next.

The Timing Question

​Why now? Why remembered alterations before any visualisation exists?

Because I needed to know whether the foundations were actually complete. Pitch, rhythm, key signatures, temporal traversal: individually validated, but never tested as a system. Remembered alterations forced that test. If they didn't align naturally, I'd have learned something important about what was missing.

They aligned. Beautifully. With no compromises in existing architecture, no special cases, no friction. Four systems built independently composed into a solution more elegant than any I'd planned.

That's conceptual closure. That's knowing the foundations are right before proceeding to build on them. That's why this work happened now, before technical necessity demanded it.

The next phases (windowing, rendering, note entry) will build on these same primitives. But now I know they're sound. Not because I believe they should be, but because I've seen them work together when they had no reason to unless the underlying model was correct.

The window opens soon. But first, this needed to be right. Now I know that when notes appear on screen, there will be no special cases left to fix, no rules-of-thumb to implement. Accidentals are now correct regardless of staff, voice, cross-staff, or cross-measure situation or house rule preferences.

​Es ist alles eins, as Marie sings in Wozzeck. But in a good way.
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5 Comments

The Lineage: When Ledger Lines Shorten

27/10/2025

2 Comments

 
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Today, preparing the drawing system, I returned to LilyPond’s essay on engraving. Within a few paragraphs I realised: we come from exactly the same place.

The moment my spine tingled was when they described the shortened ledger line beside an accidental – that precise, almost invisible kindness that makes a score feel right before you know why. The line yields a little, the principle remains. That gesture is the mark of true engraving.

Martin Spreadbury studied LilyPond when he built Dorico. I’m convinced Martin Keary did too, though we didn't talk about it when I had him on the line some time ago. LilyPond is the gold standard – the Holy Grail of digital engraving with a soul.

The Masters We Serve

​Bärenreiter, Durand, Peters, Schott, Universal Edition. Publishers whose engravers spent ten years learning how to disappear behind their craft.

The copper-plate aesthetic: bold, confident, generous. Staff lines weighty enough to guide the eye, noteheads round enough to feel sung, stems drawn with conviction.

Modern digital engraving forgot this. It grew thin, bloodless — optimised for screens instead of for musicians.

The Musician’s Eye

As a performer, I react to good engraving before I’ve even played a note. My hands and eyes recognise the rhythm of care – the breathing room between notes, the balance of white space, the subtle confidence of proportion.

A well-engraved page feels alive: it draws the body toward the instrument. The pulse is visible before sound begins. That is what the old masters knew, and what the best modern systems are all trying to recapture in their own ways.

Good engraving isn’t decoration. Not by any means. It’s the first phrase of the music itself.

The Recognition

The lineage is clear, and the standard unchanging: those 1920s scores, those shortened ledger lines, that unspoken discipline that still knows how to sing.

We all worship at that shrine.
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    Author

    Peter Bengtson –
    Cloud architect, Clojure advocate, concert organist, opera composer. Craft over commodity. Still windsurfing through parentheses.

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Ooloi is a modern, open-source desktop music notation software designed to produce professional-quality engraved scores, with responsive performance even for the largest, most complex scores. The core functionality includes inputting music notation, formatting scores and their parts, and printing them. Additional features can be added as plugins, allowing for a modular and customizable user experience.

​Ooloi is currently under development. No release date has been announced.​


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