Kangwei Xu

20 papers A 1B 2Journal 14Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
ACM Trans. Design Autom. Electr. Syst.
Kangwei Xu, Grace Li Zhang, Xunzhao Yin, Cheng Zhuo, Ulf Schlichtmann, Bing Li
2025 J jnl
IEEE Access
Kangwei Xu, Ruwei Huang
2025 J jnl
CoRR
Kangwei Xu, Grace Li Zhang, Ulf Schlichtmann, Bing Li
2025 A conf
ICCAD
Kangwei Xu, Bing Li, Grace Li Zhang, Ulf Schlichtmann
2025 J jnl
CoRR
Kangwei Xu, Bing Li, Grace Li Zhang, Ulf Schlichtmann
2025 conf
SOCC
Kangwei Xu, Denis Schwachhofer, Jason Blocklove, Ilia Polian, Peter Domanski, Dirk Pflüger, Siddharth Garg, Ramesh Karri, Ozgur Sinanoglu, Johann Knechtel, Zhuorui Zhao, Ulf Schlichtmann, Bing Li
2025 J jnl
CoRR
Kangwei Xu, Denis Schwachhofer, Jason Blocklove, Ilia Polian, Peter Domanski, Dirk Pflüger, Siddharth Garg, Ramesh Karri, Ozgur Sinanoglu, Johann Knechtel, Zhuorui Zhao, Ulf Schlichtmann, Bing Li
2025 B conf
ETS
Chandan Kumar Jha, Muhammad Hassan, Khushboo Qayyum, Sallar Ahmadi-Pour, Kangwei Xu, Ruidi Qiu, Jason Blocklove, Luca Collini, Andre Nakkab, Ulf Schlichtmann, Grace Li Zhang, Ramesh Karri, Bing Li, Siddharth Garg, Rolf Drechsler
2025 J jnl
CoRR
Xu Kang, Siqi Jiang, Kangwei Xu, Jiahao Li, Ruibo Wu
2025 J jnl
CoRR
Siyuan Lu, Kangwei Xu, Peng Xie, Rui Wang, Yuanqing Cheng
2025 J jnl
Integr.
Siyuan Lu, Kangwei Xu, Peng Xie, Rui Wang, Yuanqing Cheng
2024 conf
MLCAD
Kangwei Xu, Grace Li Zhang, Xunzhao Yin, Cheng Zhuo, Ulf Schlichtmann, Bing Li
2024 J jnl
CoRR
Kangwei Xu, Grace Li Zhang, Xunzhao Yin, Cheng Zhuo, Ulf Schlichtmann, Bing Li
2024 J jnl
CoRR
Kangwei Xu, Ruidi Qiu, Zhuorui Zhao, Grace Li Zhang, Ulf Schlichtmann, Bing Li
2024 B conf
ASPDAC
Kangwei Xu, Grace Li Zhang, Ulf Schlichtmann, Bing Li
2023 J jnl
CoRR
Kangwei Xu, Grace Li Zhang, Ulf Schlichtmann, Bing Li
2022 J jnl
ACM J. Emerg. Technol. Comput. Syst.
Kangwei Xu, Dongrong Zhang, Qiang Ren, Yuanqing Cheng, Patrick Girard
2022 J jnl
IEEE Trans. Very Large Scale Integr. Syst.
Rongmei Chen, Lin Chen, Jie Liang, Yuanqing Cheng, Souhir Elloumi, Jaehyun Lee, Kangwei Xu, Vihar P. Georgiev, Kai Ni, Peter Debacker, Asen Asenov, Aida Todri-Sanial
2022 J jnl
IEEE Trans. Very Large Scale Integr. Syst.
Rongmei Chen, Lin Chen, Jie Liang, Yuanqing Cheng, Souhir Elloumi, Jaehyun Lee, Kangwei Xu, Vihar P. Georgiev, Kai Ni, Peter Debacker, Asen Asenov, Aida Todri-Sanial
2022 conf
ASP-DAC
Kangwei Xu, Yuanqing Cheng
redb/extractors/decompiler/bninja/similarity/minhasher.py
← Index redb/extractors/decompiler/bninja/similarity/minhasher.py python
import logging
import random
from enum import Enum

from ..analysis.medium_level_normalization import MediumLevelNormalization

try:
    from .minhashcustom import MinHashCustom
    from ..analysis.low_level_normalization import LowLevelNormalization
except ImportError:
    # Fallback to absolute imports (for multiprocessing spawned processes)
    from redb.extractors.decompiler.bninja.similarity.minhashcustom import MinHashCustom
    from redb.extractors.decompiler.bninja.analysis.low_level_normalization import LowLevelNormalization

## Values for this configuration were extracted from https://github.com/danielplohmann/mcrit/blob/main/mcrit/config/MinHashConfig.py#L10
# Length in number of Shingles of which a minhash consists
# this value represents the length of sha256sum hash truncated
MINHASH_SIGNATURE_LENGTH: int = 64
# Number of bits per signature element (1-32 bits)
MINHASH_SIGNATURE_BITS: int = 8


class TokenKind(Enum):
    LLIL = "llil"
    TYPED_LLIL = "typed_llil"
    MLIL = "mlil"
    TYPED_MLIL = "typed_mlil"


class MinHasher:
    # stick to the default method
    MINHASH_STRATEGY_HASH_ALL = 1

    def __init__(self, seed, il_function, kind: TokenKind = TokenKind.LLIL):
        self._minhash_seeds = []
        self.il_func = il_function
        self.kind = kind
        self._minhash_permutation = []
        self._signature_segments = []
        self._initMinhashing(seed)

    def _initMinhashing(self, MINHASH_SEED=None):
        random.seed(MINHASH_SEED)
        # init sequence of seeds
        self._minhash_seeds = [
            random.randint(0, MinHashCustom.getHashMax()) for _ in range(MINHASH_SIGNATURE_LENGTH)
        ]

    def make_ngrams(self, tokens, n=3):
        """Take the ngrams of the IL we try to pass into the functions"""
        return [tuple(tokens[i:i+n]) for i in range(len(tokens) - n + 1)]

    def _extract_tokens(self):
        """Extract the IL tokens from the IL function, picking the right
        normalizer (LLIL/MLIL) and the right normalization mode
        (skeleton/typed) based on self.kind."""
        if self.kind in (TokenKind.LLIL, TokenKind.TYPED_LLIL):
            normalizer = LowLevelNormalization()
        elif self.kind in (TokenKind.MLIL, TokenKind.TYPED_MLIL):
            normalizer = MediumLevelNormalization()
        else:
            raise ValueError(f"Unsupported token kind: {self.kind}")

        # typed variants include operand type info, skeleton variants don't
        if self.kind in (TokenKind.TYPED_LLIL, TokenKind.TYPED_MLIL):
            normalize = normalizer.normalize_instr_with_operands
        else:
            normalize = normalizer.normalize_instruction_all_levels

        instructions = []
        for basic_block in self.il_func.basic_blocks:
            for il in basic_block:
                instructions.append(normalize(il))

        return instructions

    def calculateMinHash(self):
        """Calculate hash function every time, then take minimum shingle per shingler"""
        minhash_result = MinHashCustom(minhash_bits=MINHASH_SIGNATURE_BITS)
        minhash_signature = []

        tokens = self._extract_tokens()
        shingles = self.make_ngrams(tokens, n=3)

        # Functions with fewer than 3 IL instructions can't produce n-grams
        # Return empty minhash for such small functions (thunks, stubs, etc.)
        # Triggered by 39d8ad95b0323c37bd3134ab93ac4af44c66a1a8443a41c1ac02cec19bb2816a
        if not shingles:
            return []

        # Generate the MinHash
        for seed in self._minhash_seeds:
            hashed_shingles = [
                self.shingle_hash(shingle, seed) for shingle in shingles
            ]
            min_value = min(hashed_shingles)

            if MINHASH_SIGNATURE_BITS < 32:
                min_value %= (2 ** MINHASH_SIGNATURE_BITS)

            minhash_signature.append(min_value)

        minhash_result.setMinHash(minhash_signature)
        return minhash_result.getMinHashInt()

    def shingle_hash(self, shingle, hash_seed=0):
        """Produce a single 32bit UINT hash for a given shingle"""
        return MinHashCustom.hashData(shingle, hash_seed)