research-engineer
Academic Research Engineer
An uncompromising Academic Research Engineer that applies scientific rigor, objective criticism, and zero fluff to engineering challenges. Focuses on theoretical correctness, formal verification, and optimal implementation.
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Tester
Utilisation de "research-engineer". Give me a regex to parse HTML tags.
RĂ©sultat attendu:
REJECTED. Parsing HTML with Regular Expressions is mathematically impossible because HTML is not a regular language (Chomsky Type-2). Using Type-3 grammars for Type-2 structures leads to undefined behavior on nested tags.
CORRECT APPROACH: Use a dedicated parser (lxml in Python, gumbo in C). Implementation using BeautifulSoup:
Utilisation de "research-engineer". Implement a lock-free queue in C++.
RĂ©sultat attendu:
This implementation uses the Michael-Scott queue algorithm with std::atomic. It guarantees lock-freedom but not wait-freedom. Note ABA problem mitigation using tagged pointers for minimal overhead.
Utilisation de "research-engineer". Analyze the complexity of recursive Fibonacci.
RĂ©sultat attendu:
The naive recursive algorithm F(n) = F(n-1) + F(n-2) has time complexity O(phi^n) where phi is the Golden Ratio. This is unacceptable for n > 50.
OPTIMIZATION: Using Matrix Exponentiation reduces to O(log n).
Audit de sécurité
Risque faibleStatic analysis detected patterns for external_commands and weak cryptographic algorithms. Manual review confirms these are FALSE POSITIVES. The backtick characters are markdown code formatting (e.g., `// insert logic here`), not shell execution. The word 'algorithm' refers to computational complexity analysis, not cryptography. This is a pure persona/configuration skill with no dangerous capabilities.
Problèmes à risque moyen (2)
Score de qualité
Ce que vous pouvez construire
Algorithm Analysis and Optimization
Get rigorous analysis of algorithm complexity with mathematical proofs and optimization recommendations.
Code Review with Scientific Rigor
Receive objective, unflinching critique of code implementations with focus on correctness and best practices.
Technology Stack Selection
Get evidence-based recommendations for programming languages and tools based on domain requirements.
Essayez ces prompts
Analyze the following algorithm for time and space complexity. Provide mathematical proofs and suggest optimizations if available. [INSERT ALGORITHM OR CODE]
Critique the following code implementation. Focus on correctness, edge cases, thread safety, and potential bugs. Do not soften your feedback. [INSERT CODE]
Recommend the optimal programming language and framework for the following use case. Consider performance, safety, ecosystem, and maintainability. Use case: [DESCRIBE USE CASE] Requirements: [LIST REQUIREMENTS]
Implement the following with strict correctness guarantees. Use the scientific method: define constraints, select optimal tools, implement with tests, and verify correctness. Goal: [DESCRIBE GOAL] Constraints: [LIST CONSTRAINTS]
Bonnes pratiques
- Provide precise problem constraints including time/space requirements
- State any known limitations or edge cases upfront
- Ask for the specific domain context to select optimal tools
- Be prepared for aggressive correction of flawed assumptions
Éviter
- Asking for simplified solutions that compromise correctness
- Requesting emoji or pleasantries in responses
- Using vague problem descriptions without specific constraints
- Ignoring the critique and asking for 'nicer' responses