FAILURE MAP

Understand the failure.
Verify the repair.

Small, reproducible software failures. The broken implementation, the fix that didn’t work, and the one that passed—preserved together.

Explore the cases ↓How results are verified ↗
100840Executable case variants
20168Distinct failure mechanisms
302520Executed implementations
20168Open-access cases

WHAT THE ARCHIVE CONTAINS

100840 executable cases. 20168 are open.

Every case records the implementation that fails, the fix that did not work, and the repair that passed its checks—with recorded outputs and source hashes. This release adds 100840 cases across 20168 failure mechanisms and 254 domains.

The open tier gives you the failure and the unsuccessful fix for one case in every mechanism. The remaining 80672 cases, 5 variants per mechanism, are member-only: the verified repair, its recorded checks, and the full fixture suite are held in the member archive. Read the methodology ↗

A RECORD OF WHAT WENT WRONG

Browse the archive / 100840

Python · Standard library
REFERENCEFAILURE MECHANISMDOMAINACCESS
FA-65301

Two-patch SIR with daily migration: local mixing denominator · case 01

Force of infection uses stale census sizes as migration reshapes the patches.

Epidemic compartment models● Open access↗
FA-65302

Two-patch SIR with daily migration: local mixing denominator · case 02

Force of infection uses stale census sizes as migration reshapes the patches.

Epidemic compartment models◈ Members↗
FA-65303

Two-patch SIR with daily migration: local mixing denominator · case 03

Force of infection uses stale census sizes as migration reshapes the patches.

Epidemic compartment models◈ Members↗
FA-65304

Two-patch SIR with daily migration: local mixing denominator · case 04

Force of infection uses stale census sizes as migration reshapes the patches.

Epidemic compartment models◈ Members↗
FA-65305

Two-patch SIR with daily migration: local mixing denominator · case 05

Force of infection uses stale census sizes as migration reshapes the patches.

Epidemic compartment models◈ Members↗
FA-65306

Two-patch SIR with daily migration: simultaneous exchange · case 01

Migration creates or destroys people when flows are applied sequentially.

Epidemic compartment models● Open access↗
FA-65307

Two-patch SIR with daily migration: simultaneous exchange · case 02

Migration creates or destroys people when flows are applied sequentially.

Epidemic compartment models◈ Members↗
FA-65308

Two-patch SIR with daily migration: simultaneous exchange · case 03

Migration creates or destroys people when flows are applied sequentially.

Epidemic compartment models◈ Members↗
FA-65309

Two-patch SIR with daily migration: simultaneous exchange · case 04

Migration creates or destroys people when flows are applied sequentially.

Epidemic compartment models◈ Members↗
FA-65310

Two-patch SIR with daily migration: simultaneous exchange · case 05

Migration creates or destroys people when flows are applied sequentially.

Epidemic compartment models◈ Members↗
FA-65311

Two-patch SIR with daily migration: infected mobility · case 01

The epidemic never reaches an unseeded patch.

Epidemic compartment models● Open access↗
FA-65312

Two-patch SIR with daily migration: infected mobility · case 02

The epidemic never reaches an unseeded patch.

Epidemic compartment models◈ Members↗
FA-65313

Two-patch SIR with daily migration: infected mobility · case 03

The epidemic never reaches an unseeded patch.

Epidemic compartment models◈ Members↗
FA-65314

Two-patch SIR with daily migration: infected mobility · case 04

The epidemic never reaches an unseeded patch.

Epidemic compartment models◈ Members↗
FA-65315

Two-patch SIR with daily migration: infected mobility · case 05

The epidemic never reaches an unseeded patch.

Epidemic compartment models◈ Members↗
FA-65316

Ross-Macdonald vector-borne R0: biting rate order · case 01

R0 scales linearly rather than quadratically with the biting rate.

Epidemic compartment models● Open access↗
FA-65317

Ross-Macdonald vector-borne R0: biting rate order · case 02

R0 scales linearly rather than quadratically with the biting rate.

Epidemic compartment models◈ Members↗
FA-65318

Ross-Macdonald vector-borne R0: biting rate order · case 03

R0 scales linearly rather than quadratically with the biting rate.

Epidemic compartment models◈ Members↗
FA-65319

Ross-Macdonald vector-borne R0: biting rate order · case 04

R0 scales linearly rather than quadratically with the biting rate.

Epidemic compartment models◈ Members↗
FA-65320

Ross-Macdonald vector-borne R0: biting rate order · case 05

R0 scales linearly rather than quadratically with the biting rate.

Epidemic compartment models◈ Members↗
FA-65321

Ross-Macdonald vector-borne R0: incubation survival · case 01

Survival through the extrinsic incubation period is almost zero for realistic parameters.

Epidemic compartment models● Open access↗
FA-65322

Ross-Macdonald vector-borne R0: incubation survival · case 02

Survival through the extrinsic incubation period is almost zero for realistic parameters.

Epidemic compartment models◈ Members↗
FA-65323

Ross-Macdonald vector-borne R0: incubation survival · case 03

Survival through the extrinsic incubation period is almost zero for realistic parameters.

Epidemic compartment models◈ Members↗
FA-65324

Ross-Macdonald vector-borne R0: incubation survival · case 04

Survival through the extrinsic incubation period is almost zero for realistic parameters.

Epidemic compartment models◈ Members↗
FA-65325

Ross-Macdonald vector-borne R0: incubation survival · case 05

Survival through the extrinsic incubation period is almost zero for realistic parameters.

Epidemic compartment models◈ Members↗
FA-65326

Ross-Macdonald vector-borne R0: mosquito lifespan divisor · case 01

R0 ignores the infectious lifespan of the mosquito.

Epidemic compartment models● Open access↗
FA-65327

Ross-Macdonald vector-borne R0: mosquito lifespan divisor · case 02

R0 ignores the infectious lifespan of the mosquito.

Epidemic compartment models◈ Members↗
FA-65328

Ross-Macdonald vector-borne R0: mosquito lifespan divisor · case 03

R0 ignores the infectious lifespan of the mosquito.

Epidemic compartment models◈ Members↗
FA-65329

Ross-Macdonald vector-borne R0: mosquito lifespan divisor · case 04

R0 ignores the infectious lifespan of the mosquito.

Epidemic compartment models◈ Members↗
FA-65330

Ross-Macdonald vector-borne R0: mosquito lifespan divisor · case 05

R0 ignores the infectious lifespan of the mosquito.

Epidemic compartment models◈ Members↗
FA-65331

Ross-Macdonald vector-borne R0: generational convention · case 01

The per-generation reproduction number halves R0 instead of taking its square root.

Epidemic compartment models● Open access↗
FA-65332

Ross-Macdonald vector-borne R0: generational convention · case 02

The per-generation reproduction number halves R0 instead of taking its square root.

Epidemic compartment models◈ Members↗
FA-65333

Ross-Macdonald vector-borne R0: generational convention · case 03

The per-generation reproduction number halves R0 instead of taking its square root.

Epidemic compartment models◈ Members↗
FA-65334

Ross-Macdonald vector-borne R0: generational convention · case 04

The per-generation reproduction number halves R0 instead of taking its square root.

Epidemic compartment models◈ Members↗
FA-65335

Ross-Macdonald vector-borne R0: generational convention · case 05

The per-generation reproduction number halves R0 instead of taking its square root.

Epidemic compartment models◈ Members↗
FA-65336

Ross-Macdonald vector-borne R0: bidirectional infection probability · case 01

Changing mosquito-side competence has no effect on R0.

Epidemic compartment models● Open access↗
FA-65337

Ross-Macdonald vector-borne R0: bidirectional infection probability · case 02

Changing mosquito-side competence has no effect on R0.

Epidemic compartment models◈ Members↗
FA-65338

Ross-Macdonald vector-borne R0: bidirectional infection probability · case 03

Changing mosquito-side competence has no effect on R0.

Epidemic compartment models◈ Members↗
FA-65339

Ross-Macdonald vector-borne R0: bidirectional infection probability · case 04

Changing mosquito-side competence has no effect on R0.

Epidemic compartment models◈ Members↗
FA-65340

Ross-Macdonald vector-borne R0: bidirectional infection probability · case 05

Changing mosquito-side competence has no effect on R0.

Epidemic compartment models◈ Members↗
FA-65341

Discrete logistic population with constant quota harvest: crowding feedback · case 01

Stocks never settle at carrying capacity; growth follows the initial density forever.

Ecological population dynamics● Open access↗
FA-65342

Discrete logistic population with constant quota harvest: crowding feedback · case 02

Stocks never settle at carrying capacity; growth follows the initial density forever.

Ecological population dynamics◈ Members↗
FA-65343

Discrete logistic population with constant quota harvest: crowding feedback · case 03

Stocks never settle at carrying capacity; growth follows the initial density forever.

Ecological population dynamics◈ Members↗
FA-65344

Discrete logistic population with constant quota harvest: crowding feedback · case 04

Stocks never settle at carrying capacity; growth follows the initial density forever.

Ecological population dynamics◈ Members↗
FA-65345

Discrete logistic population with constant quota harvest: crowding feedback · case 05

Stocks never settle at carrying capacity; growth follows the initial density forever.

Ecological population dynamics◈ Members↗
FA-65346

Discrete logistic population with constant quota harvest: harvest timing · case 01

Small stocks survive quotas that should wipe them out before spawning.

Ecological population dynamics● Open access↗
FA-65347

Discrete logistic population with constant quota harvest: harvest timing · case 02

Small stocks survive quotas that should wipe them out before spawning.

Ecological population dynamics◈ Members↗
FA-65348

Discrete logistic population with constant quota harvest: harvest timing · case 03

Small stocks survive quotas that should wipe them out before spawning.

Ecological population dynamics◈ Members↗
FA-65349

Discrete logistic population with constant quota harvest: harvest timing · case 04

Small stocks survive quotas that should wipe them out before spawning.

Ecological population dynamics◈ Members↗
FA-65350

Discrete logistic population with constant quota harvest: harvest timing · case 05

Small stocks survive quotas that should wipe them out before spawning.

Ecological population dynamics◈ Members↗
FA-65351

Discrete logistic population with constant quota harvest: extinction boundary · case 01

A stock harvested to exactly zero keeps a trajectory of zeros instead of stopping.

Ecological population dynamics● Open access↗
FA-65352

Discrete logistic population with constant quota harvest: extinction boundary · case 02

A stock harvested to exactly zero keeps a trajectory of zeros instead of stopping.

Ecological population dynamics◈ Members↗
FA-65353

Discrete logistic population with constant quota harvest: extinction boundary · case 03

A stock harvested to exactly zero keeps a trajectory of zeros instead of stopping.

Ecological population dynamics◈ Members↗
FA-65354

Discrete logistic population with constant quota harvest: extinction boundary · case 04

A stock harvested to exactly zero keeps a trajectory of zeros instead of stopping.

Ecological population dynamics◈ Members↗
FA-65355

Discrete logistic population with constant quota harvest: extinction boundary · case 05

A stock harvested to exactly zero keeps a trajectory of zeros instead of stopping.

Ecological population dynamics◈ Members↗
FA-65356

Discrete logistic population with constant quota harvest: trajectory seed · case 01

Trajectories are one year shorter and lose the starting stock.

Ecological population dynamics● Open access↗
FA-65357

Discrete logistic population with constant quota harvest: trajectory seed · case 02

Trajectories are one year shorter and lose the starting stock.

Ecological population dynamics◈ Members↗
FA-65358

Discrete logistic population with constant quota harvest: trajectory seed · case 03

Trajectories are one year shorter and lose the starting stock.

Ecological population dynamics◈ Members↗
FA-65359

Discrete logistic population with constant quota harvest: trajectory seed · case 04

Trajectories are one year shorter and lose the starting stock.

Ecological population dynamics◈ Members↗
FA-65360

Discrete logistic population with constant quota harvest: trajectory seed · case 05

Trajectories are one year shorter and lose the starting stock.

Ecological population dynamics◈ Members↗
FA-65361

Ricker map trajectory and dynamic regime: superstable boundary · case 01

The superstable case r=1 is labelled damped oscillation.

Ecological population dynamics● Open access↗
FA-65362

Ricker map trajectory and dynamic regime: superstable boundary · case 02

The superstable case r=1 is labelled damped oscillation.

Ecological population dynamics◈ Members↗
FA-65363

Ricker map trajectory and dynamic regime: superstable boundary · case 03

The superstable case r=1 is labelled damped oscillation.

Ecological population dynamics◈ Members↗
FA-65364

Ricker map trajectory and dynamic regime: superstable boundary · case 04

The superstable case r=1 is labelled damped oscillation.

Ecological population dynamics◈ Members↗
FA-65365

Ricker map trajectory and dynamic regime: superstable boundary · case 05

The superstable case r=1 is labelled damped oscillation.

Ecological population dynamics◈ Members↗
FA-65366

Ricker map trajectory and dynamic regime: period-doubling onset · case 01

The first period-doubling at r=2 is reported as a damped approach.

Ecological population dynamics● Open access↗
FA-65367

Ricker map trajectory and dynamic regime: period-doubling onset · case 02

The first period-doubling at r=2 is reported as a damped approach.

Ecological population dynamics◈ Members↗
FA-65368

Ricker map trajectory and dynamic regime: period-doubling onset · case 03

The first period-doubling at r=2 is reported as a damped approach.

Ecological population dynamics◈ Members↗
FA-65369

Ricker map trajectory and dynamic regime: period-doubling onset · case 04

The first period-doubling at r=2 is reported as a damped approach.

Ecological population dynamics◈ Members↗
FA-65370

Ricker map trajectory and dynamic regime: period-doubling onset · case 05

The first period-doubling at r=2 is reported as a damped approach.

Ecological population dynamics◈ Members↗
FA-65371

Ricker map trajectory and dynamic regime: exponent grouping · case 01

Populations above carrying capacity turn negative instead of being pulled down smoothly.

Ecological population dynamics● Open access↗
FA-65372

Ricker map trajectory and dynamic regime: exponent grouping · case 02

Populations above carrying capacity turn negative instead of being pulled down smoothly.

Ecological population dynamics◈ Members↗
FA-65373

Ricker map trajectory and dynamic regime: exponent grouping · case 03

Populations above carrying capacity turn negative instead of being pulled down smoothly.

Ecological population dynamics◈ Members↗
FA-65374

Ricker map trajectory and dynamic regime: exponent grouping · case 04

Populations above carrying capacity turn negative instead of being pulled down smoothly.

Ecological population dynamics◈ Members↗
FA-65375

Ricker map trajectory and dynamic regime: exponent grouping · case 05

Populations above carrying capacity turn negative instead of being pulled down smoothly.

Ecological population dynamics◈ Members↗
FA-65376

Ricker map trajectory and dynamic regime: neutral growth · case 01

A population with zero intrinsic growth is reported as monotone convergence.

Ecological population dynamics● Open access↗
FA-65377

Ricker map trajectory and dynamic regime: neutral growth · case 02

A population with zero intrinsic growth is reported as monotone convergence.

Ecological population dynamics◈ Members↗
FA-65378

Ricker map trajectory and dynamic regime: neutral growth · case 03

A population with zero intrinsic growth is reported as monotone convergence.

Ecological population dynamics◈ Members↗
FA-65379

Ricker map trajectory and dynamic regime: neutral growth · case 04

A population with zero intrinsic growth is reported as monotone convergence.

Ecological population dynamics◈ Members↗
FA-65380

Ricker map trajectory and dynamic regime: neutral growth · case 05

A population with zero intrinsic growth is reported as monotone convergence.

Ecological population dynamics◈ Members↗
FA-65381

Beverton-Holt recruitment convergence: density denominator · case 01

The stock settles well below the stated carrying capacity.

Ecological population dynamics● Open access↗
FA-65382

Beverton-Holt recruitment convergence: density denominator · case 02

The stock settles well below the stated carrying capacity.

Ecological population dynamics◈ Members↗
FA-65383

Beverton-Holt recruitment convergence: density denominator · case 03

The stock settles well below the stated carrying capacity.

Ecological population dynamics◈ Members↗
FA-65384

Beverton-Holt recruitment convergence: density denominator · case 04

The stock settles well below the stated carrying capacity.

Ecological population dynamics◈ Members↗
FA-65385

Beverton-Holt recruitment convergence: density denominator · case 05

The stock settles well below the stated carrying capacity.

Ecological population dynamics◈ Members↗
FA-65386

Beverton-Holt recruitment convergence: equilibrium branch · case 01

Declining stocks are judged against carrying capacity and never converge.

Ecological population dynamics● Open access↗
FA-65387

Beverton-Holt recruitment convergence: equilibrium branch · case 02

Declining stocks are judged against carrying capacity and never converge.

Ecological population dynamics◈ Members↗
FA-65388

Beverton-Holt recruitment convergence: equilibrium branch · case 03

Declining stocks are judged against carrying capacity and never converge.

Ecological population dynamics◈ Members↗
FA-65389

Beverton-Holt recruitment convergence: equilibrium branch · case 04

Declining stocks are judged against carrying capacity and never converge.

Ecological population dynamics◈ Members↗
FA-65390

Beverton-Holt recruitment convergence: equilibrium branch · case 05

Declining stocks are judged against carrying capacity and never converge.

Ecological population dynamics◈ Members↗
FA-65391

Beverton-Holt recruitment convergence: first-hit latch · case 01

Convergence year is the last year inside the band instead of the first.

Ecological population dynamics● Open access↗
FA-65392

Beverton-Holt recruitment convergence: first-hit latch · case 02

Convergence year is the last year inside the band instead of the first.

Ecological population dynamics◈ Members↗
FA-65393

Beverton-Holt recruitment convergence: first-hit latch · case 03

Convergence year is the last year inside the band instead of the first.

Ecological population dynamics◈ Members↗
FA-65394

Beverton-Holt recruitment convergence: first-hit latch · case 04

Convergence year is the last year inside the band instead of the first.

Ecological population dynamics◈ Members↗
FA-65395

Beverton-Holt recruitment convergence: first-hit latch · case 05

Convergence year is the last year inside the band instead of the first.

Ecological population dynamics◈ Members↗
FA-65396

Beverton-Holt recruitment convergence: band scale · case 01

Convergence is almost never detected for large stocks.

Ecological population dynamics● Open access↗
FA-65397

Beverton-Holt recruitment convergence: band scale · case 02

Convergence is almost never detected for large stocks.

Ecological population dynamics◈ Members↗
FA-65398

Beverton-Holt recruitment convergence: band scale · case 03

Convergence is almost never detected for large stocks.

Ecological population dynamics◈ Members↗
FA-65399

Beverton-Holt recruitment convergence: band scale · case 04

Convergence is almost never detected for large stocks.

Ecological population dynamics◈ Members↗
FA-65400

Beverton-Holt recruitment convergence: band scale · case 05

Convergence is almost never detected for large stocks.

Ecological population dynamics◈ Members↗

INSPECTABLE BY DESIGN

Every result has a runnable source.

Runnable implementations with recorded outputs, source hashes, and explicit contracts. Related variants share a failure mechanism and belong together in evaluation splits.

Read the methodology ↗