Jack Chen

24 papers A* 2A 2Journal 11Unranked 8
YearRankTypeTitle / Venue / Authors
2025 J jnl
Sci. Robotics
Jack Chen, Alexander Alexiev, Anthony Sergnese, Niora Fabian, Andrew Pettinari, Yubin Cai, V. Perepelook, Kailyn Schmidt, Alison Hayward, A. Guevara, Benedict Laidlaw, Injoo Moon, Billy Markowitz, Ian Ballinger, Zhenming Yang, Carter Rosen, Nabil Shalabi, Stephanie Owyang, Giovanni Traverso
2025 J jnl
CoRR
Jack Chen, Fazhong Liu, Naruto Liu, Yuhan Luo, Erqu Qin, Harry Zheng, Tian Dong, Haojin Zhu, Yan Meng, Xiao Wang
2025 A* conf
SIGCOMM
Zhuqi Li, He Liu, Shenglan Huang, Baojin Geng, Jack Chen, Jialin Chen, Liyang Sun, Qianyun Ma, Peizhe Liu, Junjun Zhao, Yiting Liao, Jamie Chen, Qian Ma, Qiang Ma, Feng Qian
2024 J jnl
CoRR
Ryan Greenblatt, Carson Denison, Benjamin Wright, Fabien Roger, Monte MacDiarmid, Samuel Marks, Johannes Treutlein, Tim Belonax, Jack Chen, David Duvenaud, Akbir Khan, Julian Michael, Sören Mindermann, Ethan Perez, Linda Petrini, Jonathan Uesato, Jared Kaplan, Buck Shlegeris, Samuel R. Bowman, Evan Hubinger
2024 J jnl
CoRR
Yi Yao, Jun Wang, Yabai Hu, Lifeng Wang, Yi Zhou, Jack Chen, Xuming Gai, Zhenming Wang, Wenjun Liu
2024 conf
AIM
Hen-Wei Huang, Jack Chen, Philipp Rupp, Claas Ehmke, Peter R. Chai, Riya Dhar, Ian Ballinger, Giovanni Traverso
2022 conf
MLSys
Jiarong Xing, Leyuan Wang, Shang Zhang, Jack Chen, Ang Chen, Yibo Zhu
2022 conf
SIGMOD Conference
Adam Prout, Szu-Po Wang, Joseph Victor, Zhou Sun, Yongzhu Li, Jack Chen, Evan Bergeron, Eric N. Hanson, Robert Walzer, Rodrigo Gomes, Nikita Shamgunov
2021 J jnl
CoRR
Jiarong Xing, Leyuan Wang, Shang Zhang, Jack Chen, Ang Chen, Yibo Zhu
2021 J jnl
IEEE Access
Jack Chen, Hen-Wei Huang, Philipp Rupp, Anjali Sinha, Claas Ehmke, Giovanni Traverso
2020 conf
SiPS
Eric Sillekens, Wenting Yi, Daniel Semrau, Alessandro Ottino, Boris Karanov, Domaniç Lavery, Lídia Galdino, Polina Bayvel, Robert I. Killey, Sujie Zhou, Kevin Law, Jack Chen
2019 J jnl
Nat. Mach. Intell.
Walt Woods, Jack Chen, Christof Teuscher
2019 J jnl
CoRR
Eric Sillekens, Wenting Yi, Daniel Semrau, Alessandro Ottino, Boris Karanov, Sujie Zhou, Kevin Law, Jack Chen, Domaniç Lavery, Lídia Galdino, Polina Bayvel, Robert I. Killey
2019 J jnl
CoRR
Walt Woods, Jack Chen, Christof Teuscher
2016 J jnl
Proc. VLDB Endow.
Jack Chen, Samir Jindel, Robert Walzer, Rajkumar Sen, Nika Jimsheleishvilli, Michael Andrews
2015 conf
WBDB
Yan Tang, Bhaskar Gowda, Jack Chen, Xin Hao, Yi Zhou, Yi Yao, Lifeng Wang
2015 conf
IMDM@VLDB
Rajkumar Sen, Jack Chen, Nika Jimsheleishvilli
2015 conf
IRPS
Jan Gaudestad, Antonio Orozco, Jack Chen
2013 J jnl
RFC
John Jason Brzozowski, Jean-Francois Tremblay, Jack Chen, Tomasz Mrugalski
2005
Jack Chen
2003 A conf
IROS
Jonathan Engel, Jack Chen, Xuefeng Wang, Zhifang Fan, Chang Liu, Douglas L. Jones
2003 A conf
IROS
Jack Chen, Zhifang Fan, Jonathan Engel, Chang Liu
2001 conf
CHI Extended Abstracts
Anoop K. Sinha, Scott R. Klemmer, Jack Chen, James A. Landay, Cindy Chen
2000 A* conf
UIST
Scott R. Klemmer, Anoop K. Sinha, Jack Chen, James A. Landay, Nadeem Aboobaker, Annie Wang
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)