Performance optimizations #714
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Use serialize and deserialize efficiently to handle multiple items at once when appropriate. • Reduce repetitive error handling by consolidating error handling patterns. • Replace all unwrap() calls in test cases with appropriate error propagation (?) or assertions for robustness.
Consider providing a default implementation for schemes that may not require randomness. Use a more descriptive return type or embed additional metadata if needed. Allow commit to consume input to avoid unnecessary clones for owned types
Enhanced Readability for Circuit Encryption Run cargo clippy to identify minor issues like unnecessary clones, redundant field initializations, and potential performance improvements. • Optimize iteration by using iterators instead of repeatedly calling .to_vec(). • Avoid unnecessary cloning of vectors in encryption logic by using references. • Simplify deeply nested logic in functions like apply_counter_mode_stream using early returns and modular helper functions. • Add explicit type annotations for variables like data_vars_states, encrypted_output_var_states, and others to improve code readability. • Use macros or utility functions to iterate over curve types and reduce repetition.
Organized related logic into methods and helper functions for better readability. Added doc comments for clarity. Provided meaningful error messages via ParameterError. Avoided unnecessary operations and ensured reusability of helper functions. Included comprehensive test cases to validate functionality.
Split repetitive logic into helper methods (compute_commitment, build_merkle_nodes, validate_nodes). • Simplified code logic and added meaningful function names to make the code self-explanatory. • Test cases reused helper functions for cleaner structure. • Removed unnecessary nested closures for clarity. • Documented functions with concise descriptions. • Optimized test function calls using a loop over multiple field types.
Renamed methods and variables for better understanding. • Grouped logically related sections together. • Consolidated repeated code logic into helper functions like test_builder_helper. • Improved error messages for better debugging. • Added comments to clarify functionality in critical sections. • Simplified test cases by reusing helper functions for different configurations. • Removed redundant checks and unnecessary assignments.
• Improved comments to clarify functionality. • Simplified the HasherDigest trait by directly supporting RustCrypto-compatible hashers. • Made HasherNode serialization/deserialization more modular and robust. • Enhanced error messages for better debugging. • Added a top-level example to clarify usage. • Detailed comments for types and methods. • Simplified test cases with reusable patterns.
• Introduced helper functions like digest_branch to avoid redundant code. • Simplified match statements for better readability. • Added detailed documentation for all major functions and structures. • Clear parameter descriptions and return types for public APIs. • Improved error propagation using Result and clear error messages. • Simplified the logic in verify_merkle_proof to make it more concise and efficient. • Combined similar logic (e.g., node value extraction) into shared methods like value(). • Introduced meaningful variable names and consistent formatting for improved readability.
Clear separation between AppendableMerkleTreeScheme, UniversalMerkleTreeScheme, and other traits. • Each function and trait now includes concise, meaningful descriptions. • Simplified result-handling functions with clear error differentiation. • Removed unnecessary comments and redundant definitions.
Each method has a clear scope of responsibility, and reused logic is abstracted. Expanded test cases for both successful and error scenarios. Better handling of scenarios like exceeding capacity. Well-structured code, consistent variable names, and thorough documentation.
Unified logic in loops and variable usage. Detailed comments explaining each section and macro usage. Clearer descriptions for error scenarios. Removed redundancy in ToTraversalPath implementations.
Simplified and structured implementation of key components. Unified formatting and comments for better understanding. Centralized error propagation for digest functions. Streamlined macro logic for implementing 32-byte hash functions. Logical grouping and type aliasing for better usability.
Segregated key components into smaller functions to improve readability and modularity. Added a separate validate_inputs function for cleaner validation logic. Consolidated transcript setup logic in setup_transcript. Created utility functions like generate_qx_proofs and evaluate_polynomials for common operations. Added clear and concise comments for better understanding.
Validation logic for dimensions was moved into a separate function (validate_poly_dims). Added concise comments and documentation to improve code clarity. Used existing functionality (e.g., merge_polynomials) wherever applicable to reduce redundancy. Improved error messages to provide more context.
The extract_prover_param and extract_verifier_param methods now reuse the slicing logic. • Common functionality (e.g., trimming) has been centralized for maintainability. • Improved error messages for better debugging. • Used consistent naming conventions for variables and methods. • Kept test-specific functionality under a #[cfg(test)] module. • Removed unnecessary steps and inline redundancies. • Reused methods instead of duplicating similar logic.
Used consistent error messages. • Simplified the build_l and compute_w_circ_l functions. • Explained steps where logic might be unclear (e.g., univariate polynomial construction, degree calculations). • Reused helper functions like get_uni_domain and bit_decompose. • Improved error messages for invalid inputs. • Used iterators where possible to reduce intermediate allocations. • Organized related utility functions together (e.g., domain utilities, polynomial composition).
Extracted repetitive logic into smaller, reusable functions (add_commitments, add_evaluations). • Added helper macros (ensure_eq, validate_lengths) for consistent input validation. • Broke long functions into smaller, manageable parts. • Replaced nested loops with functional abstractions like .chain(). • Improved error messages and ensured exhaustive validation checks. • Isolated transcript setup and challenge computations (create_challenge_vars, append_extra_message). • Clarified the purpose and steps of complex operations.
Separated functionality into helper methods (e.g., merge_point_variables, create_point_variables). • Added private methods for common tasks like validation (validate_merge, validate_partial_verify_inputs) and field information computation (compute_non_native_field_info). • Standardized error messages for validation steps. • Centralized input validation to avoid redundant code. • Modularized point variable creation and merging, making it easier to maintain or extend the logic. • Clear and descriptive method names. • Logical grouping of functions and helper methods. • Retained existing tests but added validation points to check for specific failure cases (e.g., mismatched domains or merged keys).
Separated core functionalities into smaller helper functions like compute_zeta_n, compute_zeta_n_minus_one, compute_lagrange_at_1, etc. • Encapsulated logic for Lagrange evaluations (compute_lagrange_evaluations) and public input combination (combine_lagrange_evaluations). • Improved readability with descriptive function and variable names. • Minimized deeply nested logic by breaking down tasks into smaller methods. • Created reusable components like compute_zeta_n and combine_lagrange_evaluations for common operations. • Added detailed error messages where relevant. • Precomputed v_i outside critical loops to reduce redundant computations.
Moved shared logic into smaller reusable functions (compute_lagrange_coeff, compute_trivial_lagrange_coeffs, compute_nontrivial_lagrange_coeffs). • Simplified logic and added descriptive function/variable names. • Removed redundant comments, making the code self-explanatory. • Minimized redundant computations by factoring out shared components. • Added explicit panic with a clear message for out-of-range scenarios. • Modularized test logic into test_range_lagrange_coeff for reusability.
Enhanced assert! statements with meaningful error messages for better debugging. • Introduced helper functions like compute_byte_frequencies to isolate logic and improve readability. • Reused logic across tests with utility functions. • Improved comments and reduced redundancy in test assertions. • Unified naming conventions and formatting.
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For god sake, the typo fixing bot has upgraded into renaming and code shuffling bot. Thank you AI. |
I wonder if these's an LLM backed |
fair enough, thanks for your effort! removing necessary (and defense in depth) unit tests is not helping. (which is what this PR does, for example, it removes all the trait implementation for I do agree that our code doc is far from perfect and their clarity can always improve. (same applies to actual code) but it's impossible to carefully review a PR with such large diff. It's also extremely hard to judge the actual quality improvement. If you have concrete concern or improvement idea to our code and code comment, we always warmly welcome you creating an issue and we can discuss in the issue threads about the problems and potential solutions. Then you can chartered towards submitting a PR implementing the agreed upon solution. This will save both yours and maintainers' time. |
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Hello
I made some small changes to optimize a bit of your code.
It s not much but it s honest work and hope it helps Espresso sys
Best regards
Tudor