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from __future__ import annotations
from typing import List
from .base import Skill, SkillResult, SkillContext, SkillCategory, SkillPriority
class AlgorithmDesignSkill(Skill):
"""Thiết kế thuật toán: complexity analysis, optimization, data structure selection."""
category = SkillCategory.REASONING
priority = SkillPriority.MEDIUM
keywords: List[str] = [
"algorithm", "thuật toán", "complexity", "độ phức tạp",
"big o", "big-o", "optimize", "tối ưu",
"data structure", "cấu trúc dữ liệu", "sort", "sắp xếp",
"search", "tìm kiếm", "graph", "đồ thị", "tree", "cây",
"dynamic programming", "quy hoạch động",
]
@property
def name(self) -> str:
return "algorithm_design"
@property
def description(self) -> str:
return (
"Thiết kế thuật toán: chọn data structure, phân tích complexity, "
"optimize time/space, so sánh approaches, implement clean."
)
def execute(self, context: SkillContext) -> SkillResult:
approaches = [
"Brute force (baseline)",
"Greedy algorithm",
"Divide and conquer",
"Dynamic programming",
"Backtracking",
"Branch and bound",
"Graph algorithms (BFS, DFS, Dijkstra, A*)",
"Two pointers / Sliding window",
"Binary search",
"Monotonic stack / queue",
"Topological sort",
"Union-Find (Disjoint Set)",
"Segment tree / Fenwick tree",
"Sparse table",
]
return SkillResult(
success=True,
output=f"[AlgorithmDesign] Considering {len(approaches)} approaches.",
metadata={
"skill": self.name,
"approaches": approaches,
"complexity_targets": ["O(1)", "O(log n)", "O(n)", "O(n log n)", "O(n²)"],
},
suggestions=[
"Start with brute force, then optimize",
"Analyze time AND space complexity",
"Consider edge cases (empty, single, large inputs)",
],
)
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