CLAIMSET What MuseScore users ask for: unmet needs around arranging and parts
licence CC-BY-4.0; contributions C1, C2; highlights C1, C2
declarations funding: none | competing interests: Ivan Svetunkov is the founder of Syntonic Labs, which develops music-arranging software.
exploration {"lab_record": "A2", "questions": 2, "hypotheses": {"total": 2, "supported": 1, "not_supported": 1, "inconclusive": 0, "revised": 0, "abandoned": 0, "open": 0, "from_exploration": 2}, "tests": {"total": 2, "supported": 1, "not_supported": 1, "inconclusive": 0}, "runs": {"total": 7, "confirmatory": 2, "exploratory": 5, "failed": 1}}

DEFINITIONS
D1 [data] MuseScore feature requests: Issues in the public GitHub repository musescore/MuseScore labelled 'feature request', downloaded with the GitHub API; pull requests excluded.
D2 [data] exploration set: MuseScore feature requests with odd issue numbers; used to explore themes and form hypotheses.
D3 [data] held-out set: MuseScore feature requests with even issue numbers; not read during exploration; reserved for planned tests.
D4 [method] theme classifier: Fixed case-insensitive keyword rules (regular expressions in themes.py, artefact A6) applied to an issue's title and body; an issue may belong to several themes.
D5 [variable] arranging and instrumentation theme: Feature requests matched by the theme classifier's arranging_instrumentation rule (arranging, orchestration, reduction, implode/explode, instrument change, ensemble, instrumentation, playable range).
D6 [variable] notation and engraving theme: Feature requests matched by the theme classifier's notation_engraving rule (slurs, ties, accidentals, stems, beams, tuplets, clefs, signatures, lyrics, chord symbols, articulations, dynamics, engraving).
D7 [variable] share of issues in theme: Issues matched by a theme rule divided by all issues in the set.
D8 [variable] total reactions on issues in theme: Sum of GitHub reactions (all reaction types) on the issues matched by a theme rule, at download time.

CLAIMS
C1 [descriptive; principal; support: empirical_quant E1 (E1.R1); limitations L1, L2, L3; verifiability open; planning confirmatory; outcome supported]
  Requests in the [[D5:arranging and instrumentation theme]] make up less than 10% of [[D1:MuseScore feature requests]]: the [[D7:share of issues in theme]] was 0.0459 on the [[D3:held-out set]].
  scope: population: Issues labelled "feature request" in the GitHub repository musescore/MuseScore | period: Issues created up to the download on 2026-11-05 | data_type: GitHub issue titles and bodies (first 2,000 characters) | conditions: themes defined by fixed keyword rules; held-out set: even-numbered issues | excludes: requests made in forums, Reddit, app reviews or by e-mail; users who do not file GitHub issues
  extends B1: Li et al. studied how feature requests in 825 popular GitHub repositories are labelled, submitted and handled over a project's life; they did not measure which topics the requests of a music-notation project concern.
  test: deterministic; threshold 0.1; sample all 654 held-out issues; one run; no stopping rule; supported if s < threshold; not supported if s >= threshold; verdict computed; flags holdout_used_elsewhere
  plan: lab plan PL3; planned 2026-11-05T12:02:45Z; anchor git_remote
C2 [descriptive; principal; support: empirical_quant E2 (E2.T1.r1, E2.T1.r2, E2.T1.r3, E2.T1.r4, E2.T1.r5, E2.T1.r6, E2.T1.r7, E2.T1.r8, E2.T1.r9); limitations L1, L2, L3; verifiability open; planning confirmatory; outcome not_supported]
  Requests in the [[D6:notation and engraving theme]] did not receive more [[D8:total reactions on issues in theme]] than every other theme on the [[D3:held-out set]]: they received 215 reactions, against 250 for the input, workflow and interface theme.
  scope: population: Issues labelled "feature request" in the GitHub repository musescore/MuseScore | period: Issues created up to the download on 2026-11-05 | data_type: GitHub issue titles and bodies (first 2,000 characters) | conditions: themes defined by fixed keyword rules; held-out set: even-numbered issues | excludes: requests made in forums, Reddit, app reviews or by e-mail; users who do not file GitHub issues
  extends B1: Li et al. studied how feature requests in 825 popular GitHub repositories are labelled, submitted and handled over a project's life; they did not measure which topics the requests of a music-notation project concern.
  test: deterministic; sample all 654 held-out issues; one run; no stopping rule; ties a tie counts as not more; supported if n > a and n > p and n > t and n > g and n > pb and n > pl and n > ie and n > ui; not supported if n <= a or n <= p or n <= t or n <= g or n <= pb or n <= pl or n <= ie or n <= ui; verdict computed; flags holdout_used_elsewhere
  plan: lab plan PL2; planned 2026-11-05T12:02:38Z; anchor git_remote

EVIDENCE
E1 [quant; design observational; data_origin secondary; n 654] Count of MuseScore feature requests matched by the arranging and instrumentation keyword rule, on the 654 even-numbered issues labelled 'feature request' in musescore/MuseScore (held-out set), downloaded through the GitHub search API on 2026-11-05 (lab runs RN2, RN3 and RN6; plan PL3).
  setup: studied D5; cases D3, D1; procedure D4; lens D7
  E1.R1 D7 = 0.0459 {theme: arranging_instrumentation, set: held-out}
E2 [quant; design observational; data_origin secondary; n 654] Total GitHub reactions on MuseScore feature requests in each of nine keyword-defined themes, on the 654 even-numbered issues labelled 'feature request' in musescore/MuseScore (held-out set), downloaded through the GitHub search API on 2026-11-05 (lab runs RN2, RN3 and RN7; plan PL2). The computation repeats that of E1 under a second plan: the lab record version used allowed one decision rule per plan, and H1 and H2 needed different rules.
  setup: studied D6; cases D3; procedure D4; lens D8
  E2.T1 Total GitHub reactions on the 654 held-out MuseScore feature requests (even issue numbers), by keyword-defined theme; a request can belong to several themes {set: held-out}
  | row | theme | D8 |
  | r1 | arranging_instrumentation | 44 |
  | r2 | parts_and_linked_staves | 117 |
  | r3 | transposition | 13 |
  | r4 | generation_assistance | 12 |
  | r5 | notation_engraving | 215 |
  | r6 | playback_sound | 185 |
  | r7 | platform_install | 76 |
  | r8 | import_export | 154 |
  | r9 | input_workflow_ui | 250 |

LIMITATIONS
L1 [measurement; affects C1, C2; could_bias_magnitude; mitigation none] Themes are assigned by keyword rules on issue titles and bodies; some matches are incidental words, and issues about a theme that use other words are missed.
L2 [sampling; affects C1, C2; reduces_transferability; mitigation none] GitHub feature requests come from people who file issues on GitHub, mostly experienced users and contributors; they do not represent all MuseScore users. A study of Moodle found that developers write most issue-tracker feature requests while users write most forum requests (KC and Hosseini 2026, arXiv:2606.20876).
L3 [data_quality; affects C1, C2; reduces_precision; mitigation none] Reactions are sparse: the median exploration-set issue has none, so theme totals are driven by a few issues.

ARTEFACTS
A1 [data] Every result of the lab record (117 results of 6 runs) at full precision: the lab result's ID, its run, the quantity as the run's script named it, its conditions and its value (both as JSON). The evidence's tables give the values to four significant digits.
A2 [lab_record] Lab record of the study: questions, hypotheses, plans, runs, results and decisions, as an append-only, hash-chained event log (Claimset lab record specification v0.15, begun 2026-11-05; exported with claimset 0.41.2).
A3 [code] Python script fetch_issues.py: downloads the feature requests through the GitHub search API, one creation year per query (run RN2).
A4 [code] Python script split_parity.py: splits the downloaded feature requests by issue number, odd numbers for exploration and even numbers held out (run RN3).
A5 [code] Python script explore_top.py: lists the exploration set by reactions (run RN4).
A6 [code] Python script themes.py: theme classifier: fixed keyword rules and per-theme counts (runs RN5, RN6, RN7).
A7 [data] The 1,289 issues labelled "feature request" in the GitHub repository musescore/MuseScore, as downloaded through the GitHub search API on 2026-11-05 (run RN2): titles, the first 2,000 characters of bodies, creation dates, states, reactions, comments and labels.

REFERENCES
B1 Li, J., Yang, W., Pan, M. and Zhou, Y. (2025). Understanding Feature Request Practice on GitHub via a Large Scale Empirical Study. 40th IEEE/ACM International Conference on Automated Software Engineering (ASE 2025).
B2 musescore/MuseScore GitHub repository, issues labelled "feature request", https://github.com/musescore/MuseScore, retrieved 2026-11-05

SCORES
Scores are computed by rules from the claimset file (EntryLib rubric 0.2): they check the record, not the science, and may change as the rubric and reviews develop.
Reliability of the paper: 77 (medium), the score of its lowest principal claim, C1.
C1: reliability 77 (medium); novelty: new, by the authors · no close match on EntryLib
C2: reliability 77 (medium); novelty: new, by the authors · no close match on EntryLib
Open problems in the principal claims and what they rest on:
P1 [open; up to -12; C1, C2] Limitation L1 (could bias magnitude, not mitigated): Themes are assigned by keyword rules on issue titles and bodies; some matches are incidental words, and issues about a theme that use other words are missed. To remove it: Mitigate it with evidence, or narrow the claim's scope so that it no longer applies.
P2 [plan; up to -5; C1, C2] The lab record flags the test: holdout used elsewhere. To remove it: Rerun the test as planned, or explain the flag in a limitation.
P3 [plan; up to -3; C1, C2] The plan's time is anchored by a git push only. To remove it: Anchor plans with the platform, a timestamp authority (RFC 3161) or a registry.
P4 [open; up to -2; C1, C2] Limitation L3 (reduces precision, not mitigated): Reactions are sparse: the median exploration-set issue has none, so theme totals are driven by a few issues. To remove it: Mitigate it with evidence, or narrow the claim's scope so that it no longer applies.
P5 [open; up to -1; C1, C2] Limitation L2 (reduces transferability, not mitigated): GitHub feature requests come from people who file issues on GitHub, mostly experienced users and contributors; they do not represent all MuseScore users. A study of Moodle found that developers write most issue-tracker feature requests while users write most forum requests (KC and Hosseini 2026, arXiv:2606.20876). To remove it: Mitigate it with evidence, or narrow the claim's scope so that it no longer applies.

HOW TO CITE
This claimset: Svetunkov, I. (guarantor) (2026). What MuseScore users ask for: unmet needs around arranging and parts. EntryLib. entrylib:2026.000004@v1. https://entrylib.org/p/2026.000004@v1
One claim of it: by its identifier, as entrylib:2026.000004@v1#C1 for claim C1. Each principal claim has its own page, as https://entrylib.org/p/2026.000004/C1.