IE437

Verification record — IE437 worked examples

Version 1.8 · Existing annual catalog restored · Synthetic classroom fixtures

There are two demo sites. Case A now provides the operator flow Import planning data → Objective & constraints → Run optimization → Review results, with the dark sidebar, light workspace and fixed action bar used by Case B. The old film exchange is a collapsed Results experiment. Case A retains its published operator app. Case B retains the existing Movie First M0 calculation engine and restores the annual simulator's 24-film sample through its original importer. The proposal files retain release 1.7's presentation flow and shared comparison page; each main/compatibility pair remains byte-identical. These examples execute different fictional evaluators, not measured business effects.

Case A — executed operator-flow checks

The supplied planning package is the run's baseline. Its films, capacities, site/time factors, constraints and timetable are actually parsed and used. Configuration changes opening/closing, cleaning, coverage, per-site caps, reference response scale, iteration budget and seed; confirmation must still admit the uploaded timetable. No optimization occurs before confirmation, and no hidden uniform-response presolve replaces that uploaded reference. The engine API is inspectDataset / loadDataset(package, {iterations, seed}).

The public samples are CinemaPlanning.json and Screenings.csv. JSON contains the complete planning package. CSV requires exactly showing_id,site_id,screen_id,film_id,start_time and uses the active package, or the explicit classroom definitions. It replaces the complete timetable, not a subset of rows. Maximum input size is 2 MiB; supported shape is six films A–F, six sites A–F, three screens/site and 18–600 screening rows, subject to operating, room-fit, cleaning, coverage and supply constraints, with all 18 screens used. Rich response inputs are declared assumptions, not fitted from uploaded purchase records.

The independent pure-parser test run passed 25 checks. The separate final embedded-app Node verifier passed 39/39 on the exact 650,464-byte app (SHA-256 77067435a531c809bc1e89f8a9b0bbf3b48dba09d5a7e2a6144fc283b1474d17). Parser evidence covers JSON/CSV validation/canonicalization; the exact app suite covers the current numerical/engine behavior. Neither establishes a course-build pass or unexecuted browser checks.

The recorded HTTP sample run and final Node checks used default rules, 2,600 iterations, seed 20260829, and the loaded feasible sample. Its observed outputs were:

Operator-flow measure Recorded result
Uploaded reference score 4,969
Retained best score 5,247
Gain from uploaded reference +278
Search iterations 2,600
Local response evaluations 1,742
Reference / best screenings 90 / 89
Best-plan feasibility PASS

The search can add/remove screenings within hard constraints; 90 → 89 is a genuine searched supply change. The default numerical results are confirmed by the exact final-build Node suite. The earlier configuration and invalid-file observations below preceded a final custom-ID metadata-only fix; the final Node suite confirms those contracts, and default recovery was replayed on the exact final app. Final exact-app pipeline, responsiveness, actual downloads and CSV reimport passed separately. Do not reuse 1.4's 5,302 / 1,711 results: reconstructing gaps from canonical uploaded start times changes the internal starting plan and random-search trajectory even though its reference score is 4,969. The reference is now the uploaded package, not the earlier presolved reference-plus-manual-edit entry path.

Actual browser downloads produced a five-column CSV with 89 retained screening rows and full results JSON with 90 input/reference rows, 89 best rows, confirmed settings and per-show factors. The audited best prediction sum was reported as 5,246.789, rounding to the displayed 5,247. The downloaded CSV parsed successfully through the actual Node importer and was then reimported through the final browser app: 89 reference rows and baseline score 5,247, with validation passed. Save planning inputs creates a reusable input JSON; a results JSON is an audit record, not automatically a valid input package. Fresh downloads were then obtained from the exact final app. The full results JSON audit passed (SHA-256 248759acff3a39dc05e90f0b42c1ab4de4f8a61b9668804f7daa2fa2f7ad3179), retaining 90 input rows, 89 best rows, settings and factors. The final CSV had the same five-column, 89-row content, and actual exact-final-browser reimport returned 5,247 / PASS. Earlier configuration/error observations retain their stated metadata-only boundary; export verification no longer relies on that earlier candidate.

Additional real-control observations:

Actual UI action Observed result / scope
JSON file upload 90 reference rows; default score 4,969
Search budget 100, seed 7, scale 130 Best 5,126, 63 response evaluations
CSV upload with active reference scale 104 Reference 3,975; the CSV intentionally inherited the current package's scale
Scale 104 with budget 100 and seed 7 Best 4,101
Closing changed to 23:00 Existing rows rejected under the tighter window; previous-results navigation invalidated
CSV row 2 with unknown film X Import rejected, Next disabled, previous valid dataset retained
Recovery by Load classroom sample and default confirm/run Reference 4,969 → best 5,247, 1,742 evaluations, 2,600 iterations, 89 best rows

CSV does not reset response assumptions: 3,975 at scale 104 is not a parsing error or the scale-130 baseline. Changing data/rules requires renewed confirmation, rather than reusing an earlier score. No invalid import or setting produced a new valid result.

Required new-flow check Completed evidence Remaining scope
JSON/CSV validation and upload Independent parser 25 passed; real files uploaded and used; final-browser 89-row optimized CSV reimport scored 5,247 Broader custom-ID browser upload/download cases are not claimed
Review/configure/confirm Real scale/seed/budget changes altered results; closing-time rejection invalidated old-results navigation Broader untested setting combinations are not claimed
Default optimize/repeat Final exact app Node 39/39; exact browser reload → default Run/Pause at iteration 1,605 → Finish: 5,247 / 1,742 evaluations / 2,600 iterations / 89 rows / PASS Same fixed input/settings/seed scope
Failure/recovery Unknown film X row 2 rejected with Next disabled/data retained; closing-time rejection; sample recovery observed Remaining boundary combinations are not exhaustively tested
Export/reimport Fresh exact-final JSON audit: 90 inputs/89 best/factors/settings; five-column 89-row CSV downloaded and actual final-browser reimport scored 5,247/PASS Current sample and declared planning context
Responsive/course integration Final app at 390 pixels: Import/Results body 390, method dialog 356; desktop restored. 29-file assembly/staging/build/tests and course navigation passed Offline direct-file opening is not verified

See the Case A guide and per-case verification for the authoritative final API/results when recorded. The response formula is explicitly assumed and the search is ILS; neither a learned model nor BO nor global optimality is established. No individual consumers are created.

Case B — current annual-sample checks, release 1.8

The current public Movies.csv restores the existing annual simulator's sample workbook: 24 distinct fictional movie IDs, two new releases per month, paired science-fiction/drama preference features and overlapping monthly windows. Each of the 365 service days has two active films. End dates are exclusive; December ends on January 1, 2028. Metadata are declared known at 2027-01-01T00:00+09:00, the annual cutoff. The controlled sample uses 110-minute runtimes, all-age ratings and standard format.

The fresh annual-sample baseline completed over local HTTP through CUA in the actual English app. Its HTML SHA-256 is d43c00a19489882c6e3ba082c8f6debd79c0ffcddc48c160be35e13b656997ea. The subsequent sample-download link patch preserves this run's Worker and catalog byte-for-byte. Settings were 2,000 profiles, estimated annual frequency, Admissions, one initial path and default operating rules. The displayed mean frequency was 10.84 viewings/year and the local person pool was 10,000. Earlier two-film numbers below are not a substitute for this run.

Current annual-sample check Status
Existing sample / English CSV 24 IDs and 12 monthly pairs specified; exact source-preservation audit recorded separately
Actual import and movie count Existing importer loaded the annual sample; 24 movies registered
Reference calibration / potential demand / baseline evaluation Completed: 130.6-second calibration; 9,576 potential viewings; 5,536 realized viewings; 7,467 showings; one path
Monthly timeline and film/date/person details 24 film rows / 12 months. Baseline December · Our Day: 234 visits; December 2: 27 people, 23 showings. P00094 / U00018: 25 completed input watches and zero earlier path visits. All English
Annual schedule improvement / February 15 OWN-02-A shock Not run; these are separate 20-path comparisons
Public site and package Release 1.8 live check follows publication; deterministic public-package checks protect the fixture

Progress showed the forecast complete for all 365 service days, allocation complete and choice evaluation through December 27 before baseline completion. The observed complete run took approximately 419 seconds in this environment; this is not a formal runtime benchmark. The complete baseline verifies the annual workload, while the optional 20-path improvement/replanning experiments remain unexecuted for this catalog.

Case B — historical release 1.7 two-film M0 checks

These checks belong to the former two-film CSV, active January 1–4. They demonstrate that fixture's workflow; they are not annual-catalog outputs or a current performance benchmark.

The historical Case B HTML was byte-identical to the checked English movie-first build (SHA-256 8a2823a577059361d284542c42aafbd12b2a22022517f8dd335a5909dfabb08f). That app and its embedded Worker completed the full population → movie registration → objective → baseline → improvement → response-change workflow over local HTTP.

Inputs were 2,000 computational profiles, estimated frequency with declaration unchecked, Admissions, one initial forecast path, default operating constraints and Movies.csv containing Stellar Voyage and Quiet Afternoon. The inline Load classroom sample action uses the original file importer. Both films have release windows January 1–5, 2027, with the end date excluded; the configured horizon remains the full year. The app displayed mean frequency 10.84 visits/year and calibration time 23.4 seconds in this run. Timing is an observation on this environment, not a performance benchmark.

Baseline measure Observed result
Schedule-independent potential viewings 757
Potential: Stellar Voyage / Quiet Afternoon 348 / 409
Realized baseline viewings 726
Realized: Stellar Voyage / Quiet Afternoon 332 / 394
Baseline showings 241

The results selector switched from potential to realized baseline. Selecting Stellar Voyage and January 3 displayed 107 people on path 0. Opening P00205 from the potential Quiet Afternoon list displayed 10 completed synthetic historical watches and zero earlier visits in that simulation path. All labels and explanatory text in these views were English.

Schedule improvement searched paths 100–103 and compared the schedules on the separate common validation paths 200–219. It completed one round with 24 candidate evaluations. The validation panel gave 767.30 admissions for both schedules, paired gain 0.00 and a 95% Monte Carlo interval [0.00, 0.00], with Uncertain gain · Baseline schedule retained. This comparison is separate from the initial path-0 baseline of 726; their headline values must not be subtracted to claim improvement.

A shock on January 3, 2027, affecting Stellar Voyage with intensity multiplier 0.2, completed the three-state comparison on 20 common validation paths with the same fixed synthetic history.

Comparison state Viewings, displayed Ticket revenue, DEMO units
Before the shock 741.5 10,381.00
Existing schedule after the shock 619.6 8,675.10
Re-programmed schedule after the shock 620.4 8,684.90

The paired replanning gain was 0.70 admissions, with interval [0.30, 1.10] and Recommend the improved schedule. Search completed two rounds with 48 candidate evaluations. Use the paired statistic rather than subtracting rounded table values. This is conditional simulation evidence, not calibrated real-market forecast accuracy or a causal effect.

The multiplier 6 disabled the run action. The valid boundary 0 enabled it; numerical evaluation at zero was not run. The tested numerical shock used 0.2. The sample contains no confirmed bookings; preservation of real bookings was not tested. The English demo guide explains the experiments and units.

Presentations, navigation and package

The revised proposals retain 44 Response sections and 59 Audience sections and their original visual systems, with byte-identical main/compatibility pairs. Case A slide 03 restores the two-column operating structure. Classroom provenance/audit notices that interrupted the solution narrative are moved into presenter notes and each case’s Markdown appendix. Modeling assumptions, operating constraints, backtesting and decision evaluation remain in the relevant slides. Case A retains its published 1.5 bytes; Case B's release 1.8 rebuild embeds the restored annual catalog while retaining the existing simulation engine.

The hub and reading views retain course portal styling. Case A's new operator shell matches Case B's dark sidebar/light workspace/fixed action bar. The public allowlist contains 31 files, including the Response planning assets and the shared comparison page/Markdown. manifest.json identifies delivered checksums; THIRD_PARTY_NOTICES.md preserves 11 library notices and three font families. Private archives, grading notes, student work and customer records are excluded.

Release 1.5 exact-app Node verification passed 39/39, alongside the independent parser's 25 passes and the scoped live upload/configuration/export observations above. Final exact-build browser Run–Pause–Finish, responsive Import/Results review and actual CSV reimport passed. The 29-file assembler, approved installer/site build, node tests/worked-examples.mjs and node tests/assignments.mjs passed on the staged assembly, including archive/publication-boundary checks. These are fresh 1.5 results; older passes are not substituted. These checks preceded publication. The same release was subsequently deployed to GitHub Pages (commit 7c183a9, successful workflow run 38187603308). Public checks confirmed both direct MD downloads, both proposal/guide/definition pages, all 29 ZIP files and both complete default demo workflows.

Fresh course-prefix CUA ran the exact staged app through the complete pipeline: 4,969 → 5,247 / 1,742 evaluations / 2,600 iterations / 89 retained screenings / PASS. Its home link returned to the hub. The Response guide and original proposal also returned to the hub. Course portal reached Assignment 1, and Open worked examples reopened the hub. The refreshed hub showed the new Import workflow copy.

Remaining checks and limits

These instructor-authorized examples use synthetic data and follow the public assignment brief.

Presentation flow in release 1.7

The main slides develop the operating problem, the model and the proposed decision process. Case A starts from forecasting and timetable programming, examines why programming changes response, and develops constrained optimization and an operating loop. Case B starts from individual movie intent, connects choices and competition to demand and capacity, then develops schedule evaluation and replanning. Presenter notes and the appended Markdown guidance retain the assumptions and evidence that the original generic notice slides carried. Short labels still identify illustrative inputs, prepared values and proposed components.

The separate one-page comparison consolidates the brief-versus-case data and assumption differences. Main slides focus on the solution and operator process. The release 1.7 presentation revision added no learning, BO, M1, measured customer effects or new demo algorithms. Release 1.8 restores the existing annual simulator's catalog in Case B; it adds no new numerical algorithm. Checksums identify the delivered files, and the historical numerical/public evidence above remains scoped to its stated app and fixture. Fresh annual-sample observations belong to the current section.