Error! Test case #12581 not found in DB.

CacheDB: 2026-04-04 07:08:22

0637-arvore-de-natal

arvore-de-natal

B Difficulty

README.md Preview

# 0637 - Árvore de Natal | **Version**: 1.0
`arvore-de-natal` | Difficulty: **B** | **Updated**: 2026-04-09 00:35:18

**Sync Status:** ✅ Local: OK | ✅ Maratona: OK | ✅ API: OK (01/11/19 20:23)

## Overview
Ajude Roberto a podar árvores de natal para maximizar sua beleza, respeitando regras complexas de desempate.

## Metadata
- **Author**: Unknown
- **Editorial Author**: alessio
- **Editorial**: Utilize Programação Dinâmica em Árvores (DP on Trees). Para cada galho (u, v), a decisão de mantê-lo depende se o ganho acumulado w(u,v) + f(v) é positivo. Se for <= 0, o galho deve ser cortado para maximizar a beleza e minimizar o número de galhos (conforme regra de desempate). Use DFS interativa ou aumente o limite da pilha para lidar com N=10^6.
- **Success Msg**: Parabéns! Você resolveu um problema complexo de Programação Dinâmica em Árvores com restrições de escala real!

| Time Limit | Memory Limit | Time Complexity | Space Complexity |
| :--- | :--- | :--- | :--- |
| 1s | 128MB | O(N) | O(1) |

## Stats
| Metric | Count |
| :--- | :--- |
| Test Scenarios | 62 |
| Solutions | 2 |

## Statements
| ID | Status | Level | Natural Languages | Skills |
| :--- | :--- | :--- | :--- | :--- |
| `a-arvore-de-natal` | ✅ | A | pt | wok |

## Test Scenarios
| Name | Description | Count | Type | Level | Skills | DB Sync |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| **Teste de Carga e Performance** | Estrutura complexa com 1.000.000 de nós e pesos variados para testar eficiência máxima. | 33 | Performance | A | complexity-analysis, dp-on-tree | ❌ 0/33 |
| **Árvore Linear Profunda** | Uma árvore em forma de linha com 1.000.000 de nós para testar limites de recursão. | 4 | TDD | B | busca-profundidade, recursion, complexity-analysis | ❌ 0/4 |
| **Árvore Estrela Larga** | Raiz conectada a 999.999 folhas. Testa a eficiência no processamento de muitos filhos. | 4 | TDD | B | busca-profundidade, grafos | ❌ 0/4 |
| **Desempate de Ganho Zero** | Casos onde manter ou cortar um galho resulta na mesma beleza. | 4 | TDD | C | algoritmo-guloso, dp-on-tree, logica | ❌ 0/4 |
| **Todos Pesos Negativos** | Cenário onde todos os galhos são feios (pesos negativos). | 5 | TDD | C | algoritmo-guloso, logica | ❌ 0/5 |
| **Exemplo do Enunciado** | Valida o caso base fornecido no enunciado e a formatação básica da saída. | 12 | TDD | D | simulation-ad-hoc, io-formatacao-parsing | ⚠️ 1/12 |

## Solutions
- **Solução Ótima** (`a-optimal`)
  - Languages: `cpp, java, java, py, py`
- **Solução Sub-ótima (Recursiva)** (`b-suboptimal`)
  - Languages: `py`

## Components
- ✅ Statements
- ✅ Solutions
- ✅ Test Cases

Actions

Workflow do Problema

Local Workspace

Pasta criada no disco
Metadados

Informações básicas preenchidas
Validação

Soluções passam nos testes
4

Sincronização

Enviado para DB e GitLab

Components

Statements ✅
Solutions 2 ✅
Test Cases 61 ✅

Database Info

DB ID 637

Name Arvore_de_Natal

Time Limit 8.0s

Mem Limit 195 MB

Test Cases 42

🚀 Quick Prompts

Structure Scaffolding

Generate metadata & folder structure

ID: 1.1

Context & Description

Draft description & editorial

ID: 1.2

Statements List

ID	Level	Natural Languages	Skills	Status	Action
a-arvore-de-natal	A	a b c d	wok	⚠️

Statement Details

Select a statement above to view details.

Actions

Statistics

1 Total Statements

By Type (ID)

a-arvore-de-natal 1

By Level

Level A 1

🚀 Quick Prompts

Statement Analysis

Analyze ambiguity & clarity

ID: 2.1

WOK Statement Generation

Rewrite in WOK Universe theme

ID: 2.2

Statement Expansion

Expand to 4 difficulty levels

ID: 2.3

Database Test Cases 42 cases

ID	Rank	Status	Scenario	Filename	MD5	Description	Image	Disk Sync
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12581	2	Sample	—	-	I `bbe34e8bee3be3919cf74dfd35997924`	1	-	⚠️ Unlinked MD5 mismatch & name not found 🔎 Scan
12581	2	Sample	—	-	O `302cebb0496ed600446126e71c8eacf2`	1	-	⚠️ Unlinked MD5 mismatch & name not found 🔎 Scan
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12614	35		—	-	I `e9d0f62215308bda91b11956e2bf2f4e`	34	-	✅ Linked
12614	35		—	-	O `fe8926a34c241f6b7ca324f7e70a7225`	34	-	✅ Linked
12615	36		—	-	I `1a96d956d94334cc0f55cca7c55cfa32`	35	-	✅ Linked
12615	36		—	-	O `40e9a3c19ba22dec55e8ffc177af8477`	35	-	✅ Linked
12616	37		—	-	I `6adab6bd4af841846dfbb6a52d62fd36`	36	-	✅ Linked
12616	37		—	-	O `37627db4f755b4434b7c3a6354f41a0e`	36	-	✅ Linked
12617	38		—	-	I `d5b28505e479d03ff59b02ffbaad780a`	37	-	✅ Linked
12617	38		—	-	O `fd3c2e331e43f25482dbc1d58853cd1b`	37	-	✅ Linked
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📊 Sync Statistics

Total (Disk) 61

Total (Database) 42

✓ Synchronized 41

⚠ Desynchronized 20

Duplicates (MD5)

Duplicates in (MD5) 0

Desync = (DB missing on Disk) + (Disk missing on DB)

Actions

Testcase Scenarios Sync

YAML Source vs Database

Slug	Level	Name	Type	Skills	Status	Actions
`a-performance-load`	A	Teste de Carga e Performance Estrutura complexa com 1.000.000 de nós e...	PERFORMANCE	complexity-analysis 1pts dp-on-tree 1pts	Not in DB	Details
`b-star-wide`	B	Árvore Estrela Larga Raiz conectada a 999.999 folhas. Testa a...	TDD	busca-profundidade 1pts grafos 1pts	Not in DB	Details
`b-linear-deep`	B	Árvore Linear Profunda Uma árvore em forma de linha com 1.000.000 de...	TDD	busca-profundidade 1pts recursion 1pts complexity-analysis 1pts	Not in DB	Details
`c-zero-gain-tiebreak`	C	Desempate de Ganho Zero Casos onde manter ou cortar um galho resulta...	TDD	algoritmo-guloso 1pts dp-on-tree 1pts logica 1pts	Not in DB	Details
`c-all-negative`	C	Todos Pesos Negativos Cenário onde todos os galhos são feios (pesos...	TDD	algoritmo-guloso 1pts logica 1pts	Not in DB	Details
`d-sample`	D	Exemplo do Enunciado Valida o caso base fornecido no enunciado e a...	TDD	simulation-ad-hoc 1pts io-formatacao-parsing 1pts	Not in DB	Details

Local Test Cases (Disk)

Scenario: a-performance-load 33 cases

Name	Files (Input / Output)	Status	Actions
performance-load-01 📄 📷	Input `performance-load-01.in` e0efb2e3a24f4a0d7f51df8d8c46b012 Output `performance-load-01.out` d196f7a4332c5a4ddc1ab71579809734	🆕 Not in DB	🔍 Details 🔎 Scan
performance-load-02 #12596 📄 📷	Input `performance-load-02.in` 874e90b67554821f77e1723e9f44e739 Output `performance-load-02.out` b6de524459c3184bf977aa3dac361fd2	✅ Synced (ID: 12596)	🔍 Details
performance-load-03 #12597 📄 📷	Input `performance-load-03.in` de3cbac135d382c0390f93f4902f160f Output `performance-load-03.out` 162fdd41e138ad006c8cc087f66302fc	✅ Synced (ID: 12597)	🔍 Details
performance-load-04 #12598 📄 📷	Input `performance-load-04.in` 76f07f671bf0c3caa3b0d59beb6bdc9b Output `performance-load-04.out` 04137537080034e860bc4176aae44628	✅ Synced (ID: 12598)	🔍 Details
performance-load-05 #12599 📄 📷	Input `performance-load-05.in` 0a681af92769558109df30f0db8f650a Output `performance-load-05.out` 8c08c3ff32935d3c23dd7b81b3fd0aa9	✅ Synced (ID: 12599)	🔍 Details
performance-load-06 #12600 📄 📷	Input `performance-load-06.in` 8c489c158ff24cc5b12a7a2f6b0337e6 Output `performance-load-06.out` bbf2fcc835fb8f656322fabf59447020	✅ Synced (ID: 12600)	🔍 Details
performance-load-07 #12601 📄 📷	Input `performance-load-07.in` f34f5a767661d4e70c029f897c9f30a9 Output `performance-load-07.out` 7c5899d001ca5477b91ce61d9e508a70	✅ Synced (ID: 12601)	🔍 Details
performance-load-08 #12602 📄 📷	Input `performance-load-08.in` 077c3c24d0a0cf81d9ad422bde830544 Output `performance-load-08.out` 6bce9cf3f96a0392ac923155fcd9937d	✅ Synced (ID: 12602)	🔍 Details
performance-load-09 #12603 📄 📷	Input `performance-load-09.in` 4dd678d047220bca1a40752162b5a303 Output `performance-load-09.out` 64dfb8ea4ab0aa39ca007d8127b76ef7	✅ Synced (ID: 12603)	🔍 Details
performance-load-10 #12604 📄 📷	Input `performance-load-10.in` 232a0333fd79b3415bdf83d3aa294a7b Output `performance-load-10.out` 51566662c917c331650f0d51bf2e0d57	✅ Synced (ID: 12604)	🔍 Details
performance-load-11 #12605 📄 📷	Input `performance-load-11.in` 4f05b79b3f8a8c941aaa5100d75d3344 Output `performance-load-11.out` d83220a9bea93dac87f57e6bcf2c795a	✅ Synced (ID: 12605)	🔍 Details
performance-load-12 📄 📷	Input `performance-load-12.in` f74970df8d947574690c7a4388de7907 Output `performance-load-12.out` 911c9edc2d0da58a1919ea7de807c9ef	🆕 Not in DB	🔍 Details 🔎 Scan
performance-load-13 #12606 📄 📷	Input `performance-load-13.in` 52d6778869043574bc2c909568b79d7a Output `performance-load-13.out` 6082081d27e82ca9c7b3e52364b6857c	✅ Synced (ID: 12606)	🔍 Details
performance-load-14 #12607 📄 📷	Input `performance-load-14.in` f2ff4f723b043a663ab3e20971128216 Output `performance-load-14.out` 8e7ee98a4448d4d2b3b5a3aac8abf5bf	✅ Synced (ID: 12607)	🔍 Details
performance-load-15 #12608 📄 📷	Input `performance-load-15.in` b2f7910a6dfda049668c61b44c102474 Output `performance-load-15.out` 71837b60bbbcd2d8ccd9b31540f1f14e	✅ Synced (ID: 12608)	🔍 Details
performance-load-16 #12609 📄 📷	Input `performance-load-16.in` df1620f7d530af3aae77c928244b88b0 Output `performance-load-16.out` 032ada19fb747f11ed0190a37a21537f	✅ Synced (ID: 12609)	🔍 Details
performance-load-17 #12610 📄 📷	Input `performance-load-17.in` 6a6f2010de6da304f9cb21f5103fb3a4 Output `performance-load-17.out` edfb0182237cb66bc6af65bdfad5cb92	✅ Synced (ID: 12610)	🔍 Details
performance-load-18 #12611 📄 📷	Input `performance-load-18.in` 1ac161438a4dedccadb8430533c8242f Output `performance-load-18.out` a98f180c461a0fb907c7d52a6342a1cc	✅ Synced (ID: 12611)	🔍 Details
performance-load-19 #12612 📄 📷	Input `performance-load-19.in` 360cac6fab2da780607386d7017f767a Output `performance-load-19.out` 0637efaa730770b7634b182b36ee1e9b	✅ Synced (ID: 12612)	🔍 Details
performance-load-20 #12613 📄 📷	Input `performance-load-20.in` a632feb2e6169d34d1902a1947d01963 Output `performance-load-20.out` 6d612e860cc4ebf54068b31beb9909f7	✅ Synced (ID: 12613)	🔍 Details
performance-load-21 #12614 📄 📷	Input `performance-load-21.in` e9d0f62215308bda91b11956e2bf2f4e Output `performance-load-21.out` fe8926a34c241f6b7ca324f7e70a7225	✅ Synced (ID: 12614)	🔍 Details
performance-load-22 #12615 📄 📷	Input `performance-load-22.in` 1a96d956d94334cc0f55cca7c55cfa32 Output `performance-load-22.out` 40e9a3c19ba22dec55e8ffc177af8477	✅ Synced (ID: 12615)	🔍 Details
performance-load-23 📄 📷	Input `performance-load-23.in` 46a872a31387dcaffc7d8c9b3b4a60f2 Output `performance-load-23.out` 564614b7cc1ae5941c56c3e980427fa2	🆕 Not in DB	🔍 Details 🔎 Scan
performance-load-24 #12616 📄 📷	Input `performance-load-24.in` 6adab6bd4af841846dfbb6a52d62fd36 Output `performance-load-24.out` 37627db4f755b4434b7c3a6354f41a0e	✅ Synced (ID: 12616)	🔍 Details
performance-load-25 #12617 📄 📷	Input `performance-load-25.in` d5b28505e479d03ff59b02ffbaad780a Output `performance-load-25.out` fd3c2e331e43f25482dbc1d58853cd1b	✅ Synced (ID: 12617)	🔍 Details
performance-load-26 #12618 📄 📷	Input `performance-load-26.in` b6982abefc306c3966c9035eeeb5efb4 Output `performance-load-26.out` f84b0ac15ad7bcdc001f68f68e1e69fa	✅ Synced (ID: 12618)	🔍 Details
performance-load-27 #12619 📄 📷	Input `performance-load-27.in` ce3a0e3a6d89b655ce145f7200525bb9 Output `performance-load-27.out` ef0d4283674490ead8329582802b5973	✅ Synced (ID: 12619)	🔍 Details
performance-load-28 #12590 📄 📷	Input `performance-load-28.in` 405b414af7e331471dc3dcbdfa8ddbf3 Output `performance-load-28.out` a021bd60498cdcfa374144ca87878f68	✅ Synced (ID: 12590)	🔍 Details
performance-load-29 #12591 📄 📷	Input `performance-load-29.in` 45b8bfd0ad91cf898255ba00b4aeddd2 Output `performance-load-29.out` 4fed83f648c3a467b2a23c919537a88d	✅ Synced (ID: 12591)	🔍 Details
performance-load-30 #12592 📄 📷	Input `performance-load-30.in` 82cb711d9c7fda8d10572197e168efab Output `performance-load-30.out` 8fc426dbae702fed1d2d0422f99c85f7	✅ Synced (ID: 12592)	🔍 Details
performance-load-31 #12593 📄 📷	Input `performance-load-31.in` 31895b0044014f7e200821e2ea9a226f Output `performance-load-31.out` 456a55f56c14b1a403a8ad85ae70f221	✅ Synced (ID: 12593)	🔍 Details
performance-load-32 #12594 📄 📷	Input `performance-load-32.in` 4644b5dfbd7b94ae48ae70fe1b3b22c5 Output `performance-load-32.out` d9f2660003ba4c76156cde3a85511e91	✅ Synced (ID: 12594)	🔍 Details
performance-load-33 #12595 📄 📷	Input `performance-load-33.in` dca89f061ff141ddeec06e3de3f254f0 Output `performance-load-33.out` 6e900319d6eea4a09b76c8833d6b0f5f	✅ Synced (ID: 12595)	🔍 Details

Scenario: b-linear-deep 4 cases

Name	Files (Input / Output)	Status	Actions
linear-deep-01 📄 📷	Input `linear-deep-01.in` e5b032d8d997c101e0bb4b9334c8e0be Output `linear-deep-01.out` 99afe9bc877a9ea0f6cfd2b290805482	🆕 Not in DB	🔍 Details 🔎 Scan
linear-deep-02 📄 📷	Input `linear-deep-02.in` b5e063736ae3a775dd4dbc2c48582a7d Output `linear-deep-02.out` d1db9421ad9310d623e7dff8aefc1f02	🆕 Not in DB	🔍 Details 🔎 Scan
linear-deep-03 📄 📷	Input `linear-deep-03.in` 99e94e36f65497bda3e03715e89d6ea6 Output `linear-deep-03.out` f6d48a651558af11cdd0f33d7fc68386	🆕 Not in DB	🔍 Details 🔎 Scan
linear-deep-04 📄 📷	Input `linear-deep-04.in` 4a455aa57f86a5c777ad3e744c9c7570 Output `linear-deep-04.out` 684efb728593594923a00633ded40f83	🆕 Not in DB	🔍 Details 🔎 Scan

Scenario: b-star-wide 3 cases

Name	Files (Input / Output)	Status	Actions
star-wide-01 📄 📷	Input `star-wide-01.in` 864c9228fe1b26e97af3ce97c637d41d Output `star-wide-01.out` 2d0ba34d09f3e41d1223ed6c32cbdc97	🆕 Not in DB	🔍 Details 🔎 Scan
star-wide-02 📄 📷	Input `star-wide-02.in` 6903ccd2b5c05d65d077280ee1032631 Output `star-wide-02.out` 7cd6c64b0ebe92eae1edc17a1e7b50c5	🆕 Not in DB	🔍 Details 🔎 Scan
star-wide-03 📄 📷	Input `star-wide-03.in` 08506263baa24e1a55c08e1b4bf667ba Output `star-wide-03.out` b4107404ef8a5c428d50d29e5b529b53	🆕 Not in DB	🔍 Details 🔎 Scan

Scenario: c-all-negative 5 cases

Name	Files (Input / Output)	Status	Actions
all-negative-01 📄 📷	Input `all-negative-01.in` aa73bf486b5c2baf41ab50b090cc7b50 Output `all-negative-01.out` 19e657d86e9e376dce1d0db64c20b3bf	🆕 Not in DB	🔍 Details 🔎 Scan
all-negative-02 📄 📷	Input `all-negative-02.in` 78e51fda8c6a484667b104f9a7e32614 Output `all-negative-02.out` 2a4eff027b67b81b6cc9a32d0e782f9d	🆕 Not in DB	🔍 Details 🔎 Scan
all-negative-03 📄 📷	Input `all-negative-03.in` 89cd6c8f11531828a0828d27d3c15e61 Output `all-negative-03.out` 681192e51150f7b0d292835316266336	🆕 Not in DB	🔍 Details 🔎 Scan
all-negative-04 #12622 📄 📷	Input `all-negative-04.in` 84364bd4aa8d3ebd3300af7120943f17 Output `all-negative-04.out` 0bc1d506c656efc0f1f75fd31bd1c249	✅ Synced (ID: 12622)	🔍 Details
all-negative-05 📄 📷	Input `all-negative-05.in` 3b0ec618cdd6d1662357f2b9817ed2de Output `all-negative-05.out` a2779432d580ec504934e5b54da3f30e	🆕 Not in DB	🔍 Details 🔎 Scan

Scenario: c-zero-gain-tiebreak 4 cases

Name	Files (Input / Output)	Status	Actions
zero-gain-tiebreak-01 📄 📷	Input `zero-gain-tiebreak-01.in` e8194497e06471d7a9ada8f4bc8979c7 Output `zero-gain-tiebreak-01.out` 3fc260da5a34f0be3833d78191df87e7	🆕 Not in DB	🔍 Details 🔎 Scan
zero-gain-tiebreak-02 📄 📷	Input `zero-gain-tiebreak-02.in` 55484457b81164d093e4ba17517926fc Output `zero-gain-tiebreak-02.out` a2779432d580ec504934e5b54da3f30e	🆕 Not in DB	🔍 Details 🔎 Scan
zero-gain-tiebreak-03 📄 📷	Input `zero-gain-tiebreak-03.in` 84ceb1e4cbfd678fff133aaaa03b197f Output `zero-gain-tiebreak-03.out` ff187cfce283fbbaa70a56899d2cc939	🆕 Not in DB	🔍 Details 🔎 Scan
zero-gain-tiebreak-04 #12623 📄 📷	Input `zero-gain-tiebreak-04.in` a503426bae15e7b2b07f9ee61d1658a7 Output `zero-gain-tiebreak-04.out` f0372f7264c9281de5a8cc746d35b280	✅ Synced (ID: 12623)	🔍 Details

Scenario: d-sample 12 cases

Name	Files (Input / Output)	Status	Actions
sample-01 #12580 📄 📷	Input `sample-01.in` 3276dcc8a16b0474a78dc39144d4ab64 Output `sample-01.out` e4c703561af6c705be517ce1e92249d7	✅ Synced (ID: 12580)	🔍 Details
sample-02 #12585 📄 📷	Input `sample-02.in` a8988cff0e8553a629948a1dd79af251 Output `sample-02.out` 263d47e1f642724a3eac17e0841fc044	✅ Synced (ID: 12585)	🔍 Details
sample-03 #12586 📄 📷	Input `sample-03.in` adbf38f2a528d064c557133cd2d5ee11 Output `sample-03.out` c39c1553cc10de82b3ee137e640df816	✅ Synced (ID: 12586)	🔍 Details
sample-04 #12587 📄 📷	Input `sample-04.in` 030f0c563ee8ca4020e1d377207cff7d Output `sample-04.out` c94241d1623db00248e51da8e3adbffd	✅ Synced (ID: 12587)	🔍 Details
sample-05 #12588 📄 📷	Input `sample-05.in` b46e864098f5b786e667aff18982a700 Output `sample-05.out` e51de9e101837a75824f9cf74fb0344e	✅ Synced (ID: 12588)	🔍 Details
sample-06 📄 📷	Input `sample-06.in` dc2912d733c14b85d1518bbfc27118ee Output `sample-06.out` b5cf5af79c635ea9cd3a22e42af22655	🆕 Not in DB	🔍 Details 🔎 Scan
sample-07 📄 📷	Input `sample-07.in` 8c135560bad45f8fab63a01d3dd0c134 Output `sample-07.out` 073452441fdeb0710f05bddad577deba	🆕 Not in DB	🔍 Details 🔎 Scan
sample-09 #12589 📄 📷	Input `sample-09.in` 495f7a4166a935312f2225fd595f49e5 Output `sample-09.out` b79b33615d2bc845ee0dab7244bb9433	✅ Synced (ID: 12589)	🔍 Details
sample-10 #12581 📄 📷	Input `sample-10.in` bbe34e8bee3be3919cf74dfd35997924 Output `sample-10.out` 6e24b4e1d10fb1c941e55ffb5e488007	⚠️ Output Diff (ID: 12581)	🔍 Details
sample-11 #12582 📄 📷	Input `sample-11.in` 99c1063288543b91a818b4e80733ab01 Output `sample-11.out` 2f53a17e919092b4d6d15d40d4de1040	✅ Synced (ID: 12582)	🔍 Details
sample-12 #12583 📄 📷	Input `sample-12.in` 7171230fc5539503cfe9dd86741a813e Output `sample-12.out` b75583ca5979059ec2e5e6ffcd53c564	✅ Synced (ID: 12583)	🔍 Details
sample-13 #12584 📄 📷	Input `sample-13.in` 87e0656497ddfb99a60279a3fea88cf2 Output `sample-13.out` 37b83c7ac6ace2aa16edae1dc0408079	✅ Synced (ID: 12584)	🔍 Details

📊 Sync Statistics

Total (Disk) 61

Total (Database) 42

✓ Synchronized 41

⚠ Desynchronized 20

Duplicates (MD5)

Duplicates in (MD5) 0

Desync = (DB missing on Disk) + (Disk missing on DB)

Actions

Solução Ótima

ID: a-optimal

Abordagem de Programação Dinâmica em Árvores processada de forma iterativa para garantir eficiência O(N) e segurança contra estouro de pilha.

Implementations

Solução Sub-ótima (Recursiva)

ID: b-suboptimal

Abordagem recursiva padrão em Python que falha em entradas grandes devido ao limite de profundidade de recursão.

Implementations

py Imperative

✅ suboptimal.py

Solutions Check Report

## Solutions Check Report (Detalhado / Debug)
**Generated**: 2026-04-12T10:16:39.457568
**Solution**: `solutions/a-optimal/optimal.py`

### Compilation
✅ No compilation needed

### Resultados

<table class="results-table"><thead><tr><th>Test Case</th><th>Result</th><th>Time (s)</th></tr></thead><tbody>
<tr class="scenario-row"><td colspan="3"><strong>a-performance-load - Performance</strong></td></tr>
<tr id="row-a-performance-load-performance-load-01-in"><td>performance-load-01.in</td><td>✅ PASS</td><td>2.943</td></tr>
<tr id="row-a-performance-load-performance-load-02-in"><td>performance-load-02.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-a-performance-load-performance-load-03-in"><td>performance-load-03.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-a-performance-load-performance-load-04-in"><td>performance-load-04.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-a-performance-load-performance-load-05-in"><td>performance-load-05.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-a-performance-load-performance-load-06-in"><td>performance-load-06.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-a-performance-load-performance-load-07-in"><td>performance-load-07.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-a-performance-load-performance-load-08-in"><td>performance-load-08.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-a-performance-load-performance-load-09-in"><td>performance-load-09.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-a-performance-load-performance-load-10-in"><td>performance-load-10.in</td><td>✅ PASS</td><td>0.014</td></tr>
<tr id="row-a-performance-load-performance-load-11-in"><td>performance-load-11.in</td><td>✅ PASS</td><td>0.014</td></tr>
<tr id="row-a-performance-load-performance-load-12-in"><td>performance-load-12.in</td><td>✅ PASS</td><td>4.343</td></tr>
<tr id="row-a-performance-load-performance-load-13-in"><td>performance-load-13.in</td><td>✅ PASS</td><td>0.016</td></tr>
<tr id="row-a-performance-load-performance-load-14-in"><td>performance-load-14.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-a-performance-load-performance-load-15-in"><td>performance-load-15.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-a-performance-load-performance-load-16-in"><td>performance-load-16.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-a-performance-load-performance-load-17-in"><td>performance-load-17.in</td><td>✅ PASS</td><td>0.380</td></tr>
<tr id="row-a-performance-load-performance-load-18-in"><td>performance-load-18.in</td><td>✅ PASS</td><td>0.388</td></tr>
<tr id="row-a-performance-load-performance-load-19-in"><td>performance-load-19.in</td><td>✅ PASS</td><td>0.340</td></tr>
<tr id="row-a-performance-load-performance-load-20-in"><td>performance-load-20.in</td><td>✅ PASS</td><td>0.336</td></tr>
<tr id="row-a-performance-load-performance-load-21-in"><td>performance-load-21.in</td><td>✅ PASS</td><td>0.339</td></tr>
<tr id="row-a-performance-load-performance-load-22-in"><td>performance-load-22.in</td><td>✅ PASS</td><td>0.338</td></tr>
<tr id="row-a-performance-load-performance-load-23-in"><td>performance-load-23.in</td><td>✅ PASS</td><td>4.699</td></tr>
<tr id="row-a-performance-load-performance-load-24-in"><td>performance-load-24.in</td><td>✅ PASS</td><td>0.369</td></tr>
<tr id="row-a-performance-load-performance-load-25-in"><td>performance-load-25.in</td><td>✅ PASS</td><td>0.432</td></tr>
<tr id="row-a-performance-load-performance-load-26-in"><td>performance-load-26.in</td><td>✅ PASS</td><td>0.308</td></tr>
<tr id="row-a-performance-load-performance-load-27-in"><td>performance-load-27.in</td><td>✅ PASS</td><td>0.343</td></tr>
<tr id="row-a-performance-load-performance-load-28-in"><td>performance-load-28.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-a-performance-load-performance-load-29-in"><td>performance-load-29.in</td><td>✅ PASS</td><td>0.016</td></tr>
<tr id="row-a-performance-load-performance-load-30-in"><td>performance-load-30.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-a-performance-load-performance-load-31-in"><td>performance-load-31.in</td><td>✅ PASS</td><td>0.014</td></tr>
<tr id="row-a-performance-load-performance-load-32-in"><td>performance-load-32.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-a-performance-load-performance-load-33-in"><td>performance-load-33.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr class="scenario-row"><td colspan="3"><strong>b-linear-deep - TDD</strong></td></tr>
<tr id="row-b-linear-deep-linear-deep-01-in"><td>linear-deep-01.in</td><td>✅ PASS</td><td>0.014</td></tr>
<tr id="row-b-linear-deep-linear-deep-02-in"><td>linear-deep-02.in</td><td>✅ PASS</td><td>0.159</td></tr>
<tr id="row-b-linear-deep-linear-deep-03-in"><td>linear-deep-03.in</td><td>✅ PASS</td><td>1.580</td></tr>
<tr id="row-b-linear-deep-linear-deep-04-in"><td>linear-deep-04.in</td><td>✅ PASS</td><td>1.512</td></tr>
<tr class="scenario-row"><td colspan="3"><strong>b-star-wide - TDD</strong></td></tr>
<tr id="row-b-star-wide-star-wide-01-in"><td>star-wide-01.in</td><td>✅ PASS</td><td>0.015</td></tr>
<tr id="row-b-star-wide-star-wide-02-in"><td>star-wide-02.in</td><td>✅ PASS</td><td>0.157</td></tr>
<tr id="row-b-star-wide-star-wide-03-in"><td>star-wide-03.in</td><td>✅ PASS</td><td>1.542</td></tr>
<tr class="scenario-row"><td colspan="3"><strong>c-all-negative - TDD</strong></td></tr>
<tr id="row-c-all-negative-all-negative-01-in"><td>all-negative-01.in</td><td>✅ PASS</td><td>0.012</td></tr>
<tr id="row-c-all-negative-all-negative-02-in"><td>all-negative-02.in</td><td>✅ PASS</td><td>0.014</td></tr>
<tr id="row-c-all-negative-all-negative-03-in"><td>all-negative-03.in</td><td>✅ PASS</td><td>0.279</td></tr>
<tr id="row-c-all-negative-all-negative-04-in"><td>all-negative-04.in</td><td>✅ PASS</td><td>0.029</td></tr>
<tr id="row-c-all-negative-all-negative-05-in"><td>all-negative-05.in</td><td>✅ PASS</td><td>0.012</td></tr>
<tr class="scenario-row"><td colspan="3"><strong>c-zero-gain-tiebreak - TDD</strong></td></tr>
<tr id="row-c-zero-gain-tiebreak-zero-gain-tiebreak-01-in"><td>zero-gain-tiebreak-01.in</td><td>✅ PASS</td><td>0.012</td></tr>
<tr id="row-c-zero-gain-tiebreak-zero-gain-tiebreak-02-in"><td>zero-gain-tiebreak-02.in</td><td>✅ PASS</td><td>0.012</td></tr>
<tr id="row-c-zero-gain-tiebreak-zero-gain-tiebreak-03-in"><td>zero-gain-tiebreak-03.in</td><td>✅ PASS</td><td>0.012</td></tr>
<tr id="row-c-zero-gain-tiebreak-zero-gain-tiebreak-04-in"><td>zero-gain-tiebreak-04.in</td><td>✅ PASS</td><td>0.027</td></tr>
<tr class="scenario-row"><td colspan="3"><strong>d-sample - TDD</strong></td></tr>
<tr id="row-d-sample-sample-01-in"><td>sample-01.in</td><td>✅ PASS</td><td>0.012</td></tr>
<tr id="row-d-sample-sample-02-in"><td>sample-02.in</td><td>✅ PASS</td><td>0.012</td></tr>
<tr id="row-d-sample-sample-03-in"><td>sample-03.in</td><td>✅ PASS</td><td>0.012</td></tr>
<tr id="row-d-sample-sample-04-in"><td>sample-04.in</td><td>✅ PASS</td><td>0.012</td></tr>
<tr id="row-d-sample-sample-05-in"><td>sample-05.in</td><td>✅ PASS</td><td>0.012</td></tr>
<tr id="row-d-sample-sample-06-in"><td>sample-06.in</td><td>✅ PASS</td><td>0.012</td></tr>
<tr id="row-d-sample-sample-07-in"><td>sample-07.in</td><td>✅ PASS</td><td>0.013</td></tr>
<tr id="row-d-sample-sample-09-in"><td>sample-09.in</td><td>✅ PASS</td><td>0.013</td></tr>
<tr id="row-d-sample-sample-10-in"><td>sample-10.in</td><td>✅ PASS</td><td>0.012</td></tr>
<tr id="row-d-sample-sample-11-in"><td>sample-11.in</td><td>✅ PASS</td><td>0.012</td></tr>
<tr id="row-d-sample-sample-12-in"><td>sample-12.in</td><td>✅ PASS</td><td>0.013</td></tr>
<tr id="row-d-sample-sample-13-in"><td>sample-13.in</td><td>✅ PASS</td><td>0.012</td></tr>
</tbody></table>

✅ Verification

Validate your solutions against test cases using the metadata rules.

🚀 Quick Prompts

Solution Generation

Create Optimal/Sub-optimal code

ID: 3.1

📄 Enunciados

A 1

Idiomas: pt

💡 Soluções

cpp: 1 java: 2 py: 3

✅ 0 ❌ 0

🧪 Casos de Teste

6 Scen.

Total no Disco 61

Total no Banco 42

Sincronização 67.0%

Metadata (form)

Version

Name

Slug

ID Beecrowd

Difficulty

Time Complexity

Space Complexity

Time Limit (s)

Memory Limit (MB)

Origin

Author (Problem)

Author (Editorial)

Default Statement

Topics

Skills

Description

Editorial

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# yaml-language-server: $schema=https://api.mundodocodigo.com.br/api/public/json/wok-problem.json --- version: '1.0' id: 637 name: Árvore de Natal slug: arvore-de-natal timelimit: 8.0 memlimit: 195 difficultyLevelId: B author: Unknown source: Mundo do Código tags: [] testScenarios: - id: d-sample name: Exemplo do Enunciado description: Valida o caso base fornecido no enunciado e a formatação básica da saída. helpTip: Certifique-se de que sua saída segue exatamente o formato 'D M' (Beleza e Número de Cortes) e que os IDs estão ordenados. level: D testType: TDD skills: - skill: simulation-ad-hoc points: 1 - skill: io-formatacao-parsing points: 1 - id: b-linear-deep name: Árvore Linear Profunda description: Uma árvore em forma de linha com 1.000.000 de nós para testar limites de recursão. helpTip: Para árvores muito profundas, uma DFS recursiva padrão pode causar estouro de pilha. Considere uma abordagem iterativa. level: B testType: TDD skills: - skill: busca-profundidade points: 1 - skill: recursion points: 1 - skill: complexity-analysis points: 1 - id: b-star-wide name: Árvore Estrela Larga description: Raiz conectada a 999.999 folhas. Testa a eficiência no processamento de muitos filhos. helpTip: Verifique se a representação da sua árvore e a travessia dos filhos são eficientes. level: B testType: TDD skills: - skill: busca-profundidade points: 1 - skill: grafos points: 1 - id: c-zero-gain-tiebreak name: Desempate de Ganho Zero description: Casos onde manter ou cortar um galho resulta na mesma beleza. helpTip: A regra de desempate exige minimizar o número de galhos. Se o ganho de uma subárvore for zero, você deve podar. level: C testType: TDD skills: - skill: algoritmo-guloso points: 1 - skill: dp-on-tree points: 1 - skill: logica points: 1 - id: a-performance-load name: Teste de Carga e Performance description: Estrutura complexa com 1.000.000 de nós e pesos variados para testar eficiência máxima. helpTip: O limite de tempo é generoso (8s), mas a eficiência O(N) é necessária para 1 milhão de nós. level: A testType: PERFORMANCE skills: - skill: complexity-analysis points: 1 - skill: dp-on-tree points: 1 - id: c-all-negative name: Todos Pesos Negativos description: Cenário onde todos os galhos são feios (pesos negativos). helpTip: Neste caso, a árvore ideal deve conter apenas a raiz (beleza 0). level: C testType: TDD skills: - skill: algoritmo-guloso points: 1 - skill: logica points: 1 solutions: - id: a-optimal name: Solução Ótima description: Abordagem de Programação Dinâmica em Árvores processada de forma iterativa para garantir eficiência O(N) e segurança contra estouro de pilha. level: A implementations: - language: cpp filenames: - optimal.cpp paradigm: Imperative - language: java filenames: - Optimal.java paradigm: Imperative main: Optimal - language: java filenames: - Natal.java paradigm: Imperative main: Natal - language: py filenames: - optimal.py paradigm: Imperative - language: py filenames: - natal.py paradigm: Imperative - id: b-suboptimal name: Solução Sub-ótima (Recursiva) description: Abordagem recursiva padrão em Python que falha em entradas grandes devido ao limite de profundidade de recursão. level: B implementations: - language: py filenames: - suboptimal.py paradigm: Imperative origin: wok description: Ajude Roberto a podar árvores de natal para maximizar sua beleza, respeitando regras complexas de desempate. editorial: Utilize Programação Dinâmica em Árvores (DP on Trees). Para cada galho (u, v), a decisão de mantê-lo depende se o ganho acumulado w(u,v) + f(v) é positivo. Se for <= 0, o galho deve ser cortado para maximizar a beleza e minimizar o número de galhos (conforme regra de desempate). Use DFS interativa ou aumente o limite da pilha para lidar com N=10^6. successmsg: Parabéns! Você resolveu um problema complexo de Programação Dinâmica em Árvores com restrições de escala real! timeComplexity: O(N) skills: - grafos - algoritmo-prog-dinamica - arvores - logica statements: - id: a-arvore-de-natal testScenarioLevel: A thematicSkills: - skill: wok points: 1 authorSlugProblem: Unknown topics: - programacao-dinamica - grafos - arvores authorSlugEditorial: alessio spaceComplexity: O(1) timeLimitSegs: 4 memoryLimitMb: 256 defaultStatement: c_pt_arvore-de-natal.md

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