OIer Helper

What Problem It Solves

When practicing for OI, ICPC, or ACM contests, learners often hit three frictions: not knowing where to start from a problem statement, knowing an algorithm name but not its version, complexity, or template, and struggling to locate WA or TLE causes in code. OIer Helper is aimed at algorithm competition study workflows. It organizes input around problems, algorithms, code, and problem sets, uses Chinese by default for explanations, and defaults generated code to C++17 while emphasizing both correctness and understanding.

Core Capabilities and Workflow

• Problem analysis: Given a problem link, problem ID, or statement from OJs such as Luogu, AtCoder, or Codeforces, it classifies the task, analyzes constraints and algorithmic direction, and provides a reference implementation; if no reliable editorial is found, it says so explicitly.
• Algorithm explanation: Given an algorithm such as Dijkstra, KMP, or segment tree, it refers to authoritative sources such as OI Wiki or CP-Algorithms, then explains intuition, correctness, complexity, common versions, and template differences.
• Code debugging: When both problem and code are provided, it first analyzes the expected solution, then compares it with the user's code to identify boundary, state, complexity, or output-format issues while preserving the original structure where possible.
• Problem recommendation: It searches problems by algorithm, difficulty, platform, and quantity; by default it only lists ID, title, difficulty, and link without editorial, and expands into analysis only after a problem is selected.

It also keeps competitive-programming assistant boundaries: it does not compile or run code, does not claim guaranteed AC, does not fabricate sources, and avoids copying long editorial text. Generated code is intended as a reference, and users should test it locally and avoid submitting generated code directly.

Scope and Limitations

It is useful for practice, algorithm learning, and code review, but not for real-time judging, automatic submission, or full test-suite training. If the statement, constraints, or OJ platform are incomplete, conclusions are limited. For pages that require login, are paywalled, or cannot be read reliably, it should fall back to the statement and publicly available material.