J. Vijaya

14 papers Journal 9Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
Netw. Model. Anal. Health Informatics Bioinform.
J. Vijaya, Harshvardhan Sharma, Shantanu Gupta, Avani Gajallewar
2025 J jnl
Netw. Model. Anal. Health Informatics Bioinform.
J. Vijaya, Abhinav Roy, Bhavesh S. Gyanchandani, Jyoti Sahu
2025 conf
AICCONF
Mamta Nag, J. Vijaya, Mallikharjuna Rao K
2024 conf
ICCCNT
J. Vijaya, Ashutosh Singh, Khushdeep Singh, Amit Kumar
2023 J jnl
Multim. Tools Appl.
Panguluri Padmavathi, Jonnadula Harikiran, J. Vijaya
2023 conf
ICCCNT
J. Vijaya, Amaan A. Kazi, Kishan G. Mishra, Avala Praveen
2023 conf
ICCCNT
J. Vijaya, Vishal Nitnaware, Rachit Chaddha
2021 conf
ICACDS (1)
J. Vijaya, Hussian Syed
2019 J jnl
Int. J. Bus. Inf. Syst.
E. Sivasankar, J. Vijaya
2019 J jnl
Clust. Comput.
J. Vijaya, E. Sivasankar
2019 J jnl
Neural Comput. Appl.
E. Sivasankar, J. Vijaya
2018 J jnl
Computing
J. Vijaya, E. Sivasankar
2018 J jnl
Wirel. Pers. Commun.
R. Rajamohamed, T. Justin Jose, S. Sumithra, J. Vijaya
2015 J jnl
J. Comput. Sci.
M. Rajaram, J. Vijaya
redb/extractors/decompiler/bninja/similarity/minhashcustom.py
← Index redb/extractors/decompiler/bninja/similarity/minhashcustom.py python
import numpy as np
import mmh3

class MinHashCustom:
    """
    DTO for an actual MinHash
    <minhash>: a binary sequence of packed int8/32 values
    <minhash_int>: the equivalent representation of <minhash> but as list of int8/32
    """

    _HASH_MAX = 0xFFFFFFFF
    _MINHASH_BITS = 32

    def getSignatureEntrySize(self):
        return 1 if self.MINHASH_BITS <= 8 else 4

    def __init__(self, function_addr=None, minhash_bytes=None, minhash_signature=None, minhash_bits=32):
        self.minhash = b""
        self.minhash_int = []
        if minhash_bits:
            self._MINHASH_BITS = minhash_bits
        if minhash_bytes and minhash_signature:
            raise ValueError("Can use only one keyword argument")
        if minhash_bytes:
            if self._MINHASH_BITS <= 8:
                minhash_signature = np.frombuffer(minhash_bytes, dtype=np.uint8)
            else:
                minhash_signature = np.frombuffer(minhash_bytes, dtype=np.uint32)
            self.setMinHash(minhash_signature)
        elif minhash_signature:
            self.setMinHash(minhash_signature)

        self.shingler_composition = {}
        self.function_addr = function_addr

    def hasMinHash(self):
        return len(self.minhash) > 0

    def getMinHash(self):
        return self.minhash

    def getMinHashInt(self):
        return self.minhash_int

    def setMinHash(self, minhash_signature):
        self.minhash_int = [i % 2 ** self._MINHASH_BITS for i in minhash_signature]
        if self._MINHASH_BITS <= 8:
            self.minhash = np.array(self.minhash_int, dtype=np.uint8).tobytes()
        else:
            self.minhash = np.array(self.minhash_int, dtype=np.uint32).tobytes()

    def getComposition(self):
        return self.shingler_composition

    def scoreAgainst(self, other):
        return self.calculateMinHashScore(self.minhash, other.minhash, minhash_bits=self._MINHASH_BITS)

    @staticmethod
    def getHashMax():
        return MinHashCustom._HASH_MAX

    @staticmethod
    def hashData(data, seed) -> int:
        if isinstance(data, (str, bytes, bytearray)):
            return mmh3.hash(data, seed) & MinHashCustom._HASH_MAX
        elif isinstance(data, (list, tuple)):
            to_hash = "|".join(str(elem) for elem in data)
            return mmh3.hash(to_hash, seed) & MinHashCustom._HASH_MAX
        else:
            raise NotImplementedError(
                f"Type not supported for hashData: {type(data).__name__}"
            )

    @staticmethod
    def calculateMinHashScore(first, second, minhash_bits=32):
        if minhash_bits <= 8:
            first_np = np.frombuffer(first, dtype=np.uint8)
            second_np = np.frombuffer(second, dtype=np.uint8)
        else:
            first_np = np.frombuffer(first, dtype=np.uint32)
            second_np = np.frombuffer(second, dtype=np.uint32)
        return 100.0 * sum(first_np == second_np) / len(first_np)

    @staticmethod
    def calculateMinHashIntScore(first, second):
        score = 0
        num_hashes = len(first)
        if num_hashes:
            for index, part in enumerate(first):
                score += 1 if part == second[index] else 0
            return 100.0 * score / num_hashes
        return 0.0

    @property
    def MINHASH_BITS(self):
        return self._MINHASH_BITS