Xianpeng Wang

63 papers B 5C 1Journal 52Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
IEEE Trans. Evol. Comput.
Xianpeng Wang, Jingchuan Zhang, Lixin Tang, Yaxue Liu
2026 J jnl
Swarm Evol. Comput.
Jingchuan Zhang, Yaxue Liu, Xianpeng Wang
2025 J jnl
IEEE Trans. Syst. Man Cybern. Syst.
Danjing Wang, Bin Xin, Jia Zhang, Qing Wang, Xianpeng Wang
2025 J jnl
J. Syst. Sci. Complex.
Danjing Wang, Bin Xin, Yipeng Wang, Jia Zhang, Fang Deng, Xianpeng Wang
2025 J jnl
Adv. Eng. Informatics
Yumeng Zhao, Xianpeng Wang, Xiangman Song
2025 B conf
CEC
Zhiming Dong, Xianpeng Wang
2025 J jnl
Adv. Eng. Informatics
Meng Jiang, Guodong Zhao, Xianpeng Wang
2025 J jnl
IEEE Trans. Evol. Comput.
Xianpeng Wang, Yumeng Zhao, Lixin Tang, Xin Yao
2025 B conf
CEC
Yaxue Liu, Jingchuan Zhang, Xianpeng Wang
2025 J jnl
IEEE Trans Autom. Sci. Eng.
Yao Wang, Xianpeng Wang, Yu Xue
2025 J jnl
Neurocomputing
Tianchen Zhao, Xianpeng Wang, Xiangman Song
2025 J jnl
IEEE Trans. Syst. Man Cybern. Syst.
Yuhang Wang, Yuyan Han, Yuting Wang, Xianpeng Wang, Yiping Liu, Kaizhou Gao
2025 J jnl
IEEE Trans. Instrum. Meas.
Jingchuan Zhang, Guodong Zhao, Xianpeng Wang
2024 J jnl
Swarm Evol. Comput.
Tenghui Hu, Xianpeng Wang, Lixin Tang, Qingfu Zhang
2024 J jnl
Neurocomputing
Yao Wang, Xianpeng Wang
2024 J jnl
Complex Intell. Syst.
Qiang Li, Jingchuan Zhang, Wenhao Wang, Xianpeng Wang
2024 J jnl
IEEE Trans. Syst. Man Cybern. Syst.
Lixin Tang, Chang Liu, Jiyin Liu, Xianpeng Wang
2024 J jnl
Swarm Evol. Comput.
Yao Wang, Xianpeng Wang, Lixin Tang
2024 J jnl
IEEE Trans. Instrum. Meas.
Zan Wang, Hui Lu, Yuhui Shi, Xianpeng Wang
2024 J jnl
Complex Intell. Syst.
Wei Wang, Xianpeng Wang, Xiangman Song
2024 J jnl
IEEE Trans. Evol. Comput.
Xianpeng Wang, Yao Wang, Lixin Tang, Qingfu Zhang
2023 J jnl
Appl. Soft Comput.
Tianchen Zhao, Xianpeng Wang, Xiangman Song, Chang Liu
2023 J jnl
Swarm Evol. Comput.
Xianpeng Wang, Hangyu Lou, Zhiming Dong, Chentao Yu, Renquan Lu
2023 conf
BIC-TA (1)
Yumeng Zhao, Jingchuan Zhang, Meng Jiang, Kai Fu, Qiyuan Deng, Xianpeng Wang
2023 J jnl
Complex Intell. Syst.
Qingqing Liu, Xianpeng Wang, Yao Wang, Xiangman Song
2023 J jnl
IEEE Trans. Evol. Comput.
Xianpeng Wang, Zhiming Dong, Lixin Tang, Qingfu Zhang
2023 J jnl
Complex Intell. Syst.
Qingqing Liu, Xianpeng Wang, Xiangman Song
2022 J jnl
IEEE Trans. Neural Networks Learn. Syst.
Xianpeng Wang, Tenghui Hu, Lixin Tang
2022 J jnl
Swarm Evol. Comput.
Hangyu Lou, Xianpeng Wang, Zhiming Dong, Yang Yang
2022 J jnl
IEEE Trans Autom. Sci. Eng.
Xianpeng Wang, Yao Wang, Lixin Tang
2021 J jnl
Memetic Comput.
Linlin Li, Xianpeng Wang
2021 J jnl
IEEE Trans Autom. Sci. Eng.
Zhiming Dong, Xianpeng Wang, Lixin Tang
2021 J jnl
CoRR
Xianpeng Wang, Zhiming Dong, Lixin Tang, Qingfu Zhang
2021 C conf
EMO
Tenghui Hu, Xianpeng Wang, Yao Wang, Zhiming Dong, Xinyu Zhuang
2020 J jnl
Inf. Sci.
Shuangshuang Yao, Zhiming Dong, Xianpeng Wang, Lei Ren
2020 B conf
CEC
Yao Wang, Zhiming Dong, Tenghui Hu, Xianpeng Wang
2020 J jnl
Inf. Sci.
Zhiming Dong, Xianpeng Wang, Lixin Tang
2020 J jnl
IEEE Trans. Syst. Man Cybern. Syst.
Xianpeng Wang, Zhiming Dong, Lixin Tang
2019 J jnl
IEEE Access
Linlin Li, Zan Wang, Xianpeng Wang, Lixin Tang
2019 J jnl
IEEE Trans. Cybern.
Lixin Tang, Xianpeng Wang, Zhiming Dong
2019 J jnl
Soft Comput.
Qiong Xia, Xianpeng Wang, Lixin Tang
2019 J jnl
IEEE Access
Bo Zhang, Zan Wang, Xianpeng Wang
2017 J jnl
Comput. Oper. Res.
Xianpeng Wang, Lixin Tang
2016 B conf
CEC
Xianpeng Wang, Zhiming Dong, Lixin Tang
2016 J jnl
Inf. Sci.
Xianpeng Wang, Lixin Tang
2013 J jnl
IEEE Trans. Evol. Comput.
Lixin Tang, Xianpeng Wang
2013 J jnl
Comput. Oper. Res.
Jianxun Tang, Lixin Tang, Xianpeng Wang
2012 J jnl
Appl. Soft Comput.
Xianpeng Wang, Lixin Tang
2012 B conf
IEEE Congress on Evolutionary Computation
Xianpeng Wang, Lixin Tang
2011 conf
ICSI (2)
Xianpeng Wang, Lixin Tang
2011 J jnl
IEEE Trans. Control. Syst. Technol.
Lixin Tang, Xianpeng Wang
2011 J jnl
J. Oper. Res. Soc.
Xianpeng Wang, Lixin Tang
2010 J jnl
IEEE Trans. Control. Syst. Technol.
Lixin Tang, Xianpeng Wang
2010 J jnl
Comput. Oper. Res.
Xianpeng Wang, Lixin Tang
2010 J jnl
IEEE Trans. Control. Syst. Technol.
Lixin Tang, Xianpeng Wang
2010 conf
ICSI (1)
Xianpeng Wang, Lixin Tang
2009 J jnl
Comput. Oper. Res.
Xianpeng Wang, Lixin Tang
2009 conf
CDC
Xianpeng Wang, Lixin Tang
2009 J jnl
Comput. Oper. Res.
Xianpeng Wang, Lixin Tang
2009 J jnl
Eur. J. Oper. Res.
Lixin Tang, Xianpeng Wang
2008 conf
ICIC (2)
Xianpeng Wang, Lixin Tang
2008 J jnl
J. Oper. Res. Soc.
Lixin Tang, Xianpeng Wang
2008 J jnl
IEEE Trans Autom. Sci. Eng.
Lixin Tang, Xianpeng Wang, Jiyin Liu
redb/extractors/decompiler/_archive/DecompileBinja-archive.py
← Index redb/extractors/decompiler/_archive/DecompileBinja-archive.py python
import hashlib
import inspect
import json
import os
import time
import threading
from datetime import datetime, timezone
from typing import Dict, Any, Optional

from redb.extractors.enum import Tag
from redb.extractors.extractor import Extractor
import magic
import pefile
import ppdeep
import tlsh

# Import our BinjaDecompiler (conditional)
from redb.extractors.decompiler.bninja.decompiler import BinaryNinjaDecompiler

class DecompileBinja(Extractor):
    def __init__(
        self,
        filepath,
        log,
        exporters=None,
        index_prefix=None,
        elastic_index=None,
        known_benign=False,
        known_malicious=False,
        filetype=None,
    ):
        super().__init__(
            filepath,
            log,
            exporters,
            index_prefix,
            elastic_index,
            known_benign,
            known_malicious,
        )
        self.log.debug(inspect.currentframe().f_code.co_name)

        # Check if Binary Ninja is available
       # if not BINARYNINJA_AVAILABLE:
        #     self.log.error("Binary Ninja is not available in this container")
        #    raise ImportError(
        #        "Binary Ninja module not found - not available in feature extraction container"
        #    )
        self.analysis_results = None
        self.binja_decompiler = None
        self.filetype = filetype

        # Convert TIMEOUT to integer with a default of 1200 seconds (20 minutes)
        try:
            self.BINJA_TIMEOUT = int(os.getenv("BINJA_TIMEOUT", "1200"))
        except ValueError:
            self.log.warning(
                "Invalid BINJA_TIMEOUT value, using default of 1200 seconds"
            )
            self.BINJA_TIMEOUT = 1200

        # Convert TIMEOUT to integer with a default of 1200 seconds (20 minutes)
        try:
            self.DECOMPILE_EXTRACTOR_TIMEOUT = int(
                os.getenv("DECOMPILE_EXTRACTOR_TIMEOUT", "2580")
            )
        except ValueError:
            self.log.warning(
                "Invalid DECOMPILE_EXTRACTOR_TIMEOUT value, using default of 2580 seconds"
            )
            self.DECOMPILE_EXTRACTOR_TIMEOUT = 2580

    def __enter__(self):
        return self

    def __exit__(self, exc_type, exc_val, exc_tb):
        self.cleanup_run()

    def calculate_md5(self, input_str):
        """Calculate MD5 hash of a string."""
        return hashlib.md5(input_str.encode("utf-8")).hexdigest()

    def is_dotnet(self):
        """Check if the binary is a .NET assembly.

        Returns:
            bool: True if the file is a .NET assembly, False otherwise
        """
        try:
            if self.filetype == "pebin":
                file_type = magic.from_buffer(self.binary)
                if ".Net" in file_type:
                    return True
                pe = pefile.PE(self.filepath)
                for entry in pe.OPTIONAL_HEADER.DATA_DIRECTORY:
                    # IMAGE_DIRECTORY_ENTRY_COM_DESCRIPTOR is typically 14
                    if (
                        entry.name == "IMAGE_DIRECTORY_ENTRY_COM_DESCRIPTOR"
                        and entry.Size > 0
                    ):
                        return True
                return False
        except AttributeError as e:
            self.log.error(
                f"AttributeError error dotnet file {self.hash.sha256} Full error : {e}"
            )
            return False

    def cleanup_run(self):
        """Clean up after analysis."""
        try:
            # BinaryNinjaDecompiler uses context manager pattern (__enter__/__exit__)
            # Cleanup happens automatically when exiting the 'with' block
            self.binja_decompiler = None

            # Force garbage collection
            import gc

            gc.collect()

        except Exception as e:
            self.log.error(f"Error in cleanup: {e}")

    def analyze_binary(self) -> Optional[Dict[str, Any]]:
        """Run Binary Ninja analysis and return results."""
        self.log.debug("Starting binary analysis")

        try:
            # Use BinaryNinjaDecompiler as a context manager to ensure proper setup/cleanup
            with BinaryNinjaDecompiler(
                filepath=self.filepath,
                timeout=self.BINJA_TIMEOUT,
                log=self.log,
                exporters=self.exporters,
                index_prefix=self.index_prefix,
                filetype=self.filetype,
            ) as decompiler:
                self.binja_decompiler = decompiler

                if decompiler.extract():
                    # Store results before context manager exits
                    results = decompiler.analysis_results
                    return results
                else:
                    self.log.error("BinaryNinjaDecompiler extraction failed")
                    return None

        except Exception as e:
            self.log.error(f"Error in Binary Ninja analysis: {e}")
            import traceback
            self.log.error(f"Traceback: {traceback.format_exc()}")
            return None

        finally:
            self.cleanup_run()

    def extract(self):
        """Extract and process all analysis results."""
        self.log.debug(inspect.currentframe().f_code.co_name)

        # Create a flag to track if extraction completed
        extraction_completed = False
        extraction_result = False
        extraction_error = None

        # Define the extraction process as a separate function
        def do_extraction():
            nonlocal extraction_completed, extraction_result, extraction_error
            try:
                results = self.analyze_binary()
                if not results:
                    extraction_result = False
                else:
                    self.analysis_results = results
                    extraction_result = True
            except Exception as e:
                extraction_error = e
                extraction_result = False
            finally:
                extraction_completed = True

        # Start extraction in a separate thread
        extraction_thread = threading.Thread(target=do_extraction)
        extraction_thread.daemon = True
        extraction_thread.start()

        # Wait for the extraction to complete or timeout
        start_time = time.time()
        while (
            not extraction_completed
            and (time.time() - start_time) < self.DECOMPILE_EXTRACTOR_TIMEOUT
        ):
            time.sleep(1)

        if not extraction_completed:
            self.log.error(
                f"Extraction timed out after {self.DECOMPILE_EXTRACTOR_TIMEOUT} seconds"
            )
            # Force cleanup
            self.cleanup_run()
            return None

        if extraction_error:
            self.log.error(f"Error in extraction: {extraction_error}")
            return None

        # Return the actual analysis results, not just a boolean
        return self.analysis_results if extraction_result else None

    def prepare_export_data(self, exporter_type: str) -> Any:
        """Prepare data for database export."""
        self.log.debug(inspect.currentframe().f_code.co_name)
        if not self.analysis_results:
            return None

        # # Delegate to the BinjaDecompiler for consistent export formatting
        # if self.binja_decompiler:
        #     return self.binja_decompiler.prepare_export_data(exporter_type)
        # else:
        #     self.log.error("BinjaDecompiler not available for export preparation")
        #     return None

        if exporter_type == "ClickHouseExporter":
            now = datetime.now(timezone.utc)

            def prepare_array_field(value, array_type):
                """Helper to prepare array fields with proper null handling"""
                if value is None:
                    return []
                return value

            # Add a helper function to handle empty strings
            def ensure_not_empty(value, default="UNKNOWN"):
                """Ensure a string value is not empty"""
                if value is None or value == "":
                    return default
                return value

            def ssdeep_disassembly(func):
                try:
                    if len(func) > 1:
                        return ppdeep.hash(func)
                    return ""
                except Exception as e:
                    self.log.error(f"Error in disassembly ssdeep hash calculation: {e}")
                    return ""

            def tlsh_disassembly(func):
                try:
                    if len(func) >= 50:
                        return tlsh.hash(func.encode("utf-8"))
                    return ""
                except Exception as e:
                    self.log.error(f"Error in disassembly tlsh hash calculation: {e}")
                    return ""

            return {
                "multi_table": True,
                "decompiled_content": {
                    "table": "code_binja_decompiled_functions_content",
                    "data": [
                        [
                            f["decompiled_function_hash"],
                            f["decompiled_function"],
                            f["function_type"],
                            now,
                        ]
                        for f in self.analysis_results["decompiled"]
                    ],
                    "column_names": [
                        "decompiled_function_hash",
                        "decompiled_function",
                        "function_type",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "String",
                        "Enum8('USER'=1, 'LIBRARY'=2, 'THUNK'=3, 'EXTERNAL'=4, 'UNKNOWN'=5)",
                        "DateTime64(3, 'UTC')",
                    ],
                },
                "decompiled_refs": {
                    "table": "code_binja_decompiled_functions_references",
                    "data": [
                        [
                            self.analysis_results["sha256"],
                            self.analysis_results["sha1"],
                            self.analysis_results["md5"],
                            f["decompiled_function_hash"],
                            f["disassembled_function_hash"],  # New linking field
                            f["decompiled_function_name"],
                            f["decompiled_function_prototype"],
                            f["decompiled_function_address"],
                            now,
                        ]
                        for f in self.analysis_results["decompiled"]
                    ],
                    "column_names": [
                        "sha256",
                        "sha1",
                        "md5",
                        "decompiled_function_hash",
                        "disassembled_function_hash",  # New linking field
                        "decompiled_function_name",
                        "decompiled_function_prototype",
                        "decompiled_function_address",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "FixedString(40)",
                        "FixedString(32)",
                        "FixedString(64)",
                        "Nullable(FixedString(64))",  # New linking field
                        "LowCardinality(String)",
                        "LowCardinality(String)",
                        "UInt64",
                        "DateTime64(3, 'UTC')",
                    ],
                },
                "disassembled_content": {
                    "table": "code_binja_disassembled_functions_content",
                    "data": [
                        [
                            f["disassembled_function_hash"],
                            f.get("disassembled_function", ""),
                            f.get("disassembled_function_no_addresses", ""),
                            f.get("function_type", "UNKNOWN"),
                            f.get("instructions_count", 0),
                            prepare_array_field(
                                f.get("instructions_types"), "LowCardinality(String)"
                            ),
                            f.get("control_flow_count", 0),
                            prepare_array_field(
                                f.get("memory_access_pattern"), "LowCardinality(String)"
                            ),
                            prepare_array_field(
                                f.get("register_usage"), "LowCardinality(String)"
                            ),
                            f.get("data_references_count", 0),
                            f.get("max_block_size", 0),
                            f.get("num_calls", 0),
                            f.get("stack_size", 0),
                            now,
                        ]
                        for f in self.analysis_results["disassembled"]
                    ],
                    "column_names": [
                        "disassembled_function_hash",
                        "disassembled_function",
                        "disassembled_function_no_addresses",
                        "function_type",
                        "instructions_count",
                        "instructions_types",
                        "control_flow_count",
                        "memory_access_pattern",
                        "register_usage",
                        "data_references_count",
                        "max_block_size",
                        "num_calls",
                        "stack_size",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "String",
                        "String",
                        "Enum8('USER'=1, 'LIBRARY'=2, 'THUNK'=3, 'EXTERNAL'=4, 'UNKNOWN'=5)",
                        "UInt32",
                        "Array(LowCardinality(String))",
                        "UInt32",
                        "Array(LowCardinality(String))",
                        "Array(LowCardinality(String))",
                        "UInt32",
                        "Nullable(UInt32)",
                        "Nullable(UInt32)",
                        "Nullable(Int32)",
                        "DateTime64(3, 'UTC')",
                    ],
                },
                "disassembled_refs": {
                    "table": "code_binja_disassembled_functions_references",
                    "data": [
                        [
                            self.analysis_results["sha256"],
                            self.analysis_results["sha1"],
                            self.analysis_results["md5"],
                            f["disassembled_function_hash"],
                            f["decompiled_function_hash"],
                            f["disassembled_function_name"],
                            f["disassembled_function_address"],
                            ssdeep_disassembly(
                                f.get("disassembled_function_no_addresses", "")
                            ),
                            tlsh_disassembly(
                                f.get("disassembled_function_no_addresses", "")
                            ),
                            now,
                        ]
                        for f in self.analysis_results["disassembled"]
                    ],
                    "column_names": [
                        "sha256",
                        "sha1",
                        "md5",
                        "disassembled_function_hash",
                        "decompiled_function_hash",
                        "disassembled_function_name",
                        "disassembled_function_address",
                        "ssdeep_disassembly",
                        "tlsh_disassembly",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "FixedString(40)",
                        "FixedString(32)",
                        "FixedString(64)",
                        "Nullable(FixedString(64))",
                        "LowCardinality(String)",
                        "UInt64",
                        "Nullable(String)",
                        "Nullable(FixedString(72))",
                        "DateTime64(3, 'UTC')",
                    ],
                },
                "cfg_blocks": {
                    "table": "code_binja_cfg_blocks",
                    "data": [
                        [
                            b["block_id"],
                            self.analysis_results["sha256"],
                            self.analysis_results["sha1"],
                            self.analysis_results["md5"],
                            b["function_address"],
                            b["block_start_address"],
                            b["block_end_address"],
                            b["block_size"],
                            b["instructions_count"],
                            b["block_instructions"],  # MD5 hash of instructions
                            b["predecessor_blocks"],
                            b["successor_blocks"],
                            b["depth"],
                            b["position"],
                            b["branch_type"],
                            b["block_type"],
                            b["flags"],
                            b["dominators"],
                            b["post_dominators"],
                            now,
                        ]
                        # Flatten: iterate through all functions, then all blocks in each function
                        for func_cfg in self.analysis_results["cfg"]
                        if func_cfg is not None  # Handle None from failed extractions
                        for b in func_cfg["blocks"]
                    ],
                    "column_names": [
                        "block_id",
                        "sha256",
                        "sha1",
                        "md5",
                        "function_address",
                        "block_start_address",
                        "block_end_address",
                        "block_size",
                        "instructions_count",
                        "block_instructions_hash",
                        "predecessor_blocks",
                        "successor_blocks",
                        "depth",
                        "position",
                        "branch_type",
                        "block_type",
                        "flags",
                        "dominators",
                        "post_dominators",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",  # block_id (SHA256)
                        "FixedString(64)",  # sha256
                        "FixedString(40)",  # sha1
                        "FixedString(32)",  # md5
                        "UInt64",  # function_address
                        "UInt64",  # block_start_address
                        "UInt64",  # block_end_address
                        "UInt32",  # block_size
                        "UInt16",  # instructions_count
                        "FixedString(32)",  # block_instructions_hash (MD5)
                        "Array(UInt64)",  # predecessor_blocks
                        "Array(UInt64)",  # successor_blocks
                        "UInt16",  # depth
                        "UInt16",  # position
                        "Enum8('DIRECT'=1, 'CONDITIONAL'=2, 'CALL'=3, 'RETURN'=4, 'FALLTHROUGH'=5, 'INDIRECT'=6, 'UNKNOWN'=7)",  # branch_type
                        "Enum8('CODE'=1, 'DATA'=2, 'THUNK'=3)",  # block_type
                        "Array(String)",  # flags (EntryBlock, ExitBlock, LoopBlock)
                        "Array(UInt16)",  # dominators
                        "Array(UInt16)",  # post_dominators
                        "DateTime64(3, 'UTC')",  # analysis_date
                    ],
                },
                "function_analysis_errors": {
                    "table": "function_analysis_errors_binja",
                    "data": [
                        [
                            self.analysis_results["sha256"],
                            f["function_name"],
                            f["function_address"],
                            f.get("error_location", "unknown"),
                            f.get("error_message", ""),
                            f.get("error_details", ""),
                            f.get("error_type", "unknown"),
                            self.calculate_md5(
                                f"{f['error_message']}{f['function_name']}{f['function_address']}{f['error_location']}"
                            ),
                            "new",
                            now,
                        ]
                        for f in self.analysis_results["errors"]
                    ],
                    "column_names": [
                        "sha256",
                        "function_name",
                        "function_address",
                        "error_location",
                        "error_message",
                        "error_details",
                        "error_type",
                        "error_hash",
                        "status",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "Nullable(String)",
                        "UInt64",
                        "LowCardinality(String)",
                        "Nullable(String)",
                        "Nullable(String)",
                        "Nullable(String)",
                        "FixedString(32)",
                        "Enum8('new'=1, 'investigating'=2, 'fixed'=3, 'wontfix'=4)",
                        "DateTime64(3, 'UTC')",
                    ],
                },
            }

    def tag(self) -> str:
        """Return the tag for this extractor."""
        return Tag.DECOMPILED.value

    def get_clickhouse_table(self) -> str:
        """Not used directly as we're handling multiple tables."""
        pass


if __name__ == "__main__":
    # Setup basic logging
    import logging

    logging.basicConfig(level=logging.INFO)
    logger = logging.getLogger("DecompileBinja")

    # Parse command line arguments
    import argparse

    parser = argparse.ArgumentParser(description="Binary Ninja Decompiler Wrapper")
    parser.add_argument("filepath", help="Path to the binary file to analyze")
    parser.add_argument(
        "--output", "-o", help="Output JSON file path (default: stdout)"
    )
    parser.add_argument(
        "--timeout",
        "-t",
        type=int,
        default=1200,
        help="Analysis timeout in seconds (default: 1200)",
    )
    args = parser.parse_args()

    # Create and run the extractor
    with DecompileBinja(args.filepath, logger) as extractor:
        success = extractor.extract()

        if not success:
            logger.error("Analysis failed")
            exit(1)

        # Output results
        if args.output:
            with open(args.output, "w") as f:
                json.dump(extractor.analysis_results, f)
            logger.info(f"Results written to {args.output}")
        else:
            print(json.dumps(extractor.analysis_results))