Varun Joshi

14 papers Journal 9Unranked 5
YearRankTypeTitle / Venue / Authors
2025 J jnl
J. Open Source Softw.
Aravind Sundararajan, Varun Joshi, Brian R. Umberger, Matthew C. O'Neill
2025 J jnl
Comput. Appl. Math.
Navneet Kaur, Varun Joshi
2024 J jnl
Expert Syst. J. Knowl. Eng.
Rakesh Kumar, Varun Joshi, Gaurav Dhiman, Wattana Viriyasitavat
2024 J jnl
CoRR
Daphna Raz, Varun Joshi, Brian R. Umberger, Necmiye Ozay
2024 J jnl
Math. Comput. Simul.
Navneet Kaur, Varun Joshi
2023 J jnl
Comput. Syst. Sci. Eng.
Geeta Arora, Pinkey Chauhan, Muhammad Imran Asjad, Varun Joshi, Homan Emadifar, Fahd Jarad
2022 conf
VLSI Technology and Circuits
Aida Varzaghani, Bardia Bozorgzadeh, Jack Lam, Ankush Goel, Xiaobin Yuan, Mohamed Elzeftawi, Mehran Izad, Sudipta Sarkar, Alberto Baldisserotto, Seong-Ryong Ryu, Steven Mikes, Jeffrey Hwang, Varun Joshi, Shahrzad Naraghi, Darshan Kadia, Mohammad Ranjbar, Paul Lee, Dimitri Loizos, Sotirios Zogopoulos, Shwetabh Verma, Stefanos Sidiropoulos
2022 J jnl
IEEE Trans. Biomed. Eng.
Varun Joshi, Elliott J. Rouse, Edward S. Claflin, Chandramouli Krishnan
2021 J jnl
Int. J. Fuzzy Syst.
Rakesh Kumar, Rajesh Kumar Chandrawat, Biswajit Sarkar, Varun Joshi, Arunava Majumder
2019 conf
UEMCON
Ashutosh Kanitkar, Rutwik Kulkarni, Varun Joshi, Yash Karwa, Sanjyot Gindi, Geetanjali Vinayak Kale
2019 conf
CSE/EUC
Ashutosh Kanitkar, Rutwik Kulkarni, Varun Joshi, Yash Karwa, Sanjyot Gindi, Geetanjali Vinayak Kale
2019 conf
IC3
Ashutosh Kanitkar, Yash Karwa, Geetanjali Vinayak Kale, Varun Joshi, Sanjyot Gindi
2016 conf
CHI Extended Abstracts
Yi Yang, Yunqi Hu, Yidi Hong, Varun Joshi, Radhika Kolathumani
2014 J jnl
Biomed. Signal Process. Control.
Varun Joshi, Ram Bilas Pachori, V. Antony Vijesh
tests/unit/test_decompile_utils.py
← Index tests/unit/test_decompile_utils.py python
"""Unit tests for decompiler utility modules:
- bninja/utils/hashes.py
- bninja/utils/json_encoder.py
- bninja/analysis/low_level_normalization.py
"""
import hashlib
import json
import pytest


# ============================================================================
# 1a. hashes.py
# ============================================================================

from redb.extractors.decompiler.bninja.utils.hashes import (
    calculate_md5,
    calculate_sha256,
    calculate_tlsh,
)


class TestCalculateMD5:
    def test_calculate_md5_known_value(self):
        expected = hashlib.md5(b"test").hexdigest()
        assert calculate_md5("test") == expected

    def test_calculate_md5_empty(self):
        expected = hashlib.md5(b"").hexdigest()
        assert calculate_md5("") == expected


class TestCalculateSHA256:
    def test_calculate_sha256_known_value(self):
        expected = hashlib.sha256(b"hello world").hexdigest()
        assert calculate_sha256("hello world") == expected

    def test_calculate_sha256_empty_string(self):
        result = calculate_sha256("")
        assert len(result) == 64
        assert all(c in "0123456789abcdef" for c in result)


class TestCalculateTLSH:
    def test_calculate_tlsh_long_data(self):
        # TLSH requires >= 50 bytes
        data = "A" * 100
        result = calculate_tlsh(data)
        assert result is not None
        assert isinstance(result, str)

    def test_calculate_tlsh_short_data(self):
        data = "A" * 10
        result = calculate_tlsh(data)
        assert result is None

    def test_calculate_tlsh_deterministic(self):
        data = "x" * 200
        assert calculate_tlsh(data) == calculate_tlsh(data)



# ============================================================================
# 1b. json_encoder.py
# ============================================================================

from redb.extractors.decompiler.bninja.utils.json_encoder import BinaryNinjaEncoder


class TestBinaryNinjaEncoder:
    def test_encode_value_confidence_object(self):
        obj = type("VC", (), {"value": 42, "confidence": 255})()
        result = json.dumps(obj, cls=BinaryNinjaEncoder)
        assert json.loads(result) == 42

    def test_encode_str_fallback(self):
        obj = type("Obj", (), {"__str__": lambda self: "custom_repr"})()
        result = json.dumps(obj, cls=BinaryNinjaEncoder)
        assert json.loads(result) == "custom_repr"

    def test_encode_normal_types(self):
        data = {"a": 1, "b": [2, 3], "c": "hello"}
        result = json.dumps(data, cls=BinaryNinjaEncoder)
        assert json.loads(result) == data

    def test_encode_set_via_str(self):
        # Python sets have __str__, so BinaryNinjaEncoder converts them
        # to their string repr instead of raising TypeError.
        result = json.dumps(set([1, 2, 3]), cls=BinaryNinjaEncoder)
        parsed = json.loads(result)
        assert isinstance(parsed, str)
        assert "1" in parsed


# ============================================================================
# 1c. low_level_normalization.py
# ============================================================================

from redb.extractors.decompiler.bninja.analysis.low_level_normalization import (
    LowLevelNormalization,
)


class MockIL:
    """Mock IL node for normalization tests."""
    def __init__(self, operation, operands=None):
        self.operation = operation
        self.operands = operands or []


class TestLowLevelNormalization:
    def setup_method(self):
        self.normalizer = LowLevelNormalization()

    def test_normalize_single_instruction(self):
        node = MockIL(operation=5)
        result = self.normalizer.normalize_instruction_all_levels(node)
        assert result == [5]

    def test_normalize_nested_operands(self):
        child1 = MockIL(operation=10)
        child2 = MockIL(operation=20)
        root = MockIL(operation=1, operands=[child1, child2])
        result = self.normalizer.normalize_instruction_all_levels(root)
        assert result == [1, 10, 20]

    def test_normalize_empty_operands(self):
        node = MockIL(operation=42, operands=[])
        result = self.normalizer.normalize_instruction_all_levels(node)
        assert result == [42]

    def test_normalize_list_operands(self):
        # Simulates phi-node style list operands
        inner = MockIL(operation=99)
        node = MockIL(operation=7, operands=[[inner]])
        result = self.normalizer.normalize_instruction_all_levels(node)
        assert result == [7, 99]

    def test_normalize_none_input(self):
        result = self.normalizer.normalize_instruction_all_levels(None)
        assert result == []