Weihang Zhu

38 papers B 2Misc 1Journal 27Unranked 8
YearRankTypeTitle / Venue / Authors
2025 J jnl
IEEE Trans. Instrum. Meas.
Yongqiang Yin, Rui Yuan, Yong Lv, Hongan Wu, Hewenxuan Li, Weihang Zhu
2025 J jnl
Comput.
Abdollah Zakeri, Mulham Fawakherji, Jiming Kang, Bikram Koirala, Venkatesh Balan, Weihang Zhu, Driss Benhaddou, Fatima A. Merchant
2025 J jnl
Comput.
Abdollah Zakeri, Bikram Koirala, Jiming Kang, Venkatesh Balan, Weihang Zhu, Driss Benhaddou, Fatima A. Merchant
2024 J jnl
Comput.
Arturo Haces-Garcia, Weihang Zhu
2024 J jnl
CoRR
Abdollah Zakeri, Mulham Fawakherji, Jiming Kang, Bikram Koirala, Venkatesh Balan, Weihang Zhu, Driss Benhaddou, Fatima A. Merchant
2024 J jnl
IEEE Trans. Instrum. Meas.
Bowen Li, Rui Yuan, Yong Lv, Hongan Wu, Hongyu Zhong, Weihang Zhu
2023 J jnl
Algorithms
Ezra Wari, Weihang Zhu, Gino J. Lim
2023 J jnl
Algorithms
Ezra Wari, Weihang Zhu, Gino J. Lim
2023 J jnl
Comput. Chem. Eng.
Ezra Wari, Weihang Zhu, Gino J. Lim
2023 J jnl
IEEE Trans. Instrum. Meas.
Hongan Wu, Yong Lv, Rui Yuan, Xingkai Yang, Ke Feng, Weihang Zhu
2020 J jnl
Reliab. Eng. Syst. Saf.
Yue Shi, Weihang Zhu, Yisha Xiang, Qianmei Feng
2020 J jnl
Sensors
Linchu Yang, Ji'an Chen, Weihang Zhu
2019 J jnl
Int. J. Prod. Res.
Ezra Wari, Weihang Zhu
2019 J jnl
Ind. Robot
Huiling Chen, Liguo Shuai, Weihang Zhu, Mei Miao
2019 J jnl
IEEE Trans. Reliab.
Zhicheng Zhu, Yisha Xiang, Mingyang Li, Weihang Zhu, Kellie Schneider
2017 J jnl
Comput. Chem. Eng.
Alem Demissie, Weihang Zhu, Chanyalew Taye Belachew
2017 J jnl
Int. J. Prod. Res.
Arash Abedi, Weihang Zhu
2017 conf
AHFE (24)
Anirudh Juloori, Yueqing Li, Weihang Zhu
2017 J jnl
IEEE Trans. Haptics
Julia A. Griffin, Weihang Zhu, Chang S. Nam
2016 J jnl
Appl. Soft Comput.
Ezra Wari, Weihang Zhu
2016 J jnl
Comput. Chem. Eng.
Ezra Wari, Weihang Zhu
2013 Misc conf
WSC
James Curry, Weihang Zhu, Brian A. Craig, Lonnie Turpin, Majed Bokhari, Pavan Mhasavekar
2011 J jnl
New Gener. Comput.
Weihang Zhu, Ashraf Yaseen, Yaohang Li
2011 J jnl
J. Glob. Optim.
Weihang Zhu
2011 J jnl
Appl. Soft Comput.
Weihang Zhu
2011 B conf
IEEE Congress on Evolutionary Computation
Wen-Chyuan Chiang, Gangshu Cai, Xiaojing Xu, Ganesh Mudunuri, Weihang Zhu
2010 conf
BADS@ICAC
Weihang Zhu, Yaohang Li
2010 conf
IPDPS Workshops
Yaohang Li, Weihang Zhu
2009 conf
GEC Summit
Weihang Zhu
2009 conf
ICCS (1)
Weihang Zhu, James Curry
2009 B conf
SMC
Weihang Zhu, James Curry
2009 conf
SIS
Weihang Zhu, James Curry
2008 J jnl
J. Comput. Inf. Sci. Eng.
Weihang Zhu
2005 J jnl
Comput. Aided Des.
Yongfu Ren, Weihang Zhu, Yuan-Shin Lee
2005 conf
WHC
Brandon Itkowitz, Josh Handley, Weihang Zhu
2004 J jnl
Comput. Ind.
Weihang Zhu, Yuan-Shin Lee
2004 J jnl
Comput. Aided Des.
Weihang Zhu, Yuan-Shin Lee
2004 conf
HAPTICS
Weihang Zhu, Yuan-Shin Lee
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)