tools: rename "deadlock_detector" to "deadlock" (#2152) (#2160)

This renames the `deadlock_detector.py` tool to `deadlock.py` to make
the name more diagram-friendly and to be consistent with the naming of the
other tools.
diff --git a/tools/deadlock.py b/tools/deadlock.py
new file mode 100755
index 0000000..1784872
--- /dev/null
+++ b/tools/deadlock.py
@@ -0,0 +1,556 @@
+#!/usr/bin/python
+#
+# deadlock  Detects potential deadlocks (lock order inversions)
+#           on a running process. For Linux, uses BCC, eBPF.
+#
+# USAGE: deadlock.py [-h] [--binary BINARY] [--dump-graph DUMP_GRAPH]
+#                    [--verbose] [--lock-symbols LOCK_SYMBOLS]
+#                    [--unlock-symbols UNLOCK_SYMBOLS]
+#                    pid
+#
+# This traces pthread mutex lock and unlock calls to build a directed graph
+# representing the mutex wait graph:
+#
+# - Nodes in the graph represent mutexes.
+# - Edge (A, B) exists if there exists some thread T where lock(A) was called
+#   and lock(B) was called before unlock(A) was called.
+#
+# If the program finds a potential lock order inversion, the program will dump
+# the cycle of mutexes and the stack traces where each mutex was acquired, and
+# then exit.
+#
+# This program can only find potential deadlocks that occur while the program
+# is tracing the process. It cannot find deadlocks that may have occurred
+# before the program was attached to the process.
+#
+# Since this traces all mutex lock and unlock events and all thread creation
+# events on the traced process, the overhead of this bpf program can be very
+# high if the process has many threads and mutexes. You should only run this on
+# a process where the slowdown is acceptable.
+#
+# Note: This tool does not work for shared mutexes or recursive mutexes.
+#
+# For shared (read-write) mutexes, a deadlock requires a cycle in the wait
+# graph where at least one of the mutexes in the cycle is acquiring exclusive
+# (write) ownership.
+#
+# For recursive mutexes, lock() is called multiple times on the same mutex.
+# However, there is no way to determine if a mutex is a recursive mutex
+# after the mutex has been created. As a result, this tool will not find
+# potential deadlocks that involve only one mutex.
+#
+# Copyright 2017 Facebook, Inc.
+# Licensed under the Apache License, Version 2.0 (the "License")
+#
+# 01-Feb-2017   Kenny Yu   Created this.
+
+from __future__ import (
+    absolute_import, division, unicode_literals, print_function
+)
+from bcc import BPF
+from collections import defaultdict
+import argparse
+import json
+import os
+import subprocess
+import sys
+import time
+
+
+class DiGraph(object):
+    '''
+    Adapted from networkx: http://networkx.github.io/
+    Represents a directed graph. Edges can store (key, value) attributes.
+    '''
+
+    def __init__(self):
+        # Map of node -> set of nodes
+        self.adjacency_map = {}
+        # Map of (node1, node2) -> map string -> arbitrary attribute
+        # This will not be copied in subgraph()
+        self.attributes_map = {}
+
+    def neighbors(self, node):
+        return self.adjacency_map.get(node, set())
+
+    def edges(self):
+        edges = []
+        for node, neighbors in self.adjacency_map.items():
+            for neighbor in neighbors:
+                edges.append((node, neighbor))
+        return edges
+
+    def nodes(self):
+        return self.adjacency_map.keys()
+
+    def attributes(self, node1, node2):
+        return self.attributes_map[(node1, node2)]
+
+    def add_edge(self, node1, node2, **kwargs):
+        if node1 not in self.adjacency_map:
+            self.adjacency_map[node1] = set()
+        if node2 not in self.adjacency_map:
+            self.adjacency_map[node2] = set()
+        self.adjacency_map[node1].add(node2)
+        self.attributes_map[(node1, node2)] = kwargs
+
+    def remove_node(self, node):
+        self.adjacency_map.pop(node, None)
+        for _, neighbors in self.adjacency_map.items():
+            neighbors.discard(node)
+
+    def subgraph(self, nodes):
+        graph = DiGraph()
+        for node in nodes:
+            for neighbor in self.neighbors(node):
+                if neighbor in nodes:
+                    graph.add_edge(node, neighbor)
+        return graph
+
+    def node_link_data(self):
+        '''
+        Returns the graph as a dictionary in a format that can be
+        serialized.
+        '''
+        data = {
+            'directed': True,
+            'multigraph': False,
+            'graph': {},
+            'links': [],
+            'nodes': [],
+        }
+
+        # Do one pass to build a map of node -> position in nodes
+        node_to_number = {}
+        for node in self.adjacency_map.keys():
+            node_to_number[node] = len(data['nodes'])
+            data['nodes'].append({'id': node})
+
+        # Do another pass to build the link information
+        for node, neighbors in self.adjacency_map.items():
+            for neighbor in neighbors:
+                link = self.attributes_map[(node, neighbor)].copy()
+                link['source'] = node_to_number[node]
+                link['target'] = node_to_number[neighbor]
+                data['links'].append(link)
+        return data
+
+
+def strongly_connected_components(G):
+    '''
+    Adapted from networkx: http://networkx.github.io/
+    Parameters
+    ----------
+    G : DiGraph
+    Returns
+    -------
+    comp : generator of sets
+        A generator of sets of nodes, one for each strongly connected
+        component of G.
+    '''
+    preorder = {}
+    lowlink = {}
+    scc_found = {}
+    scc_queue = []
+    i = 0  # Preorder counter
+    for source in G.nodes():
+        if source not in scc_found:
+            queue = [source]
+            while queue:
+                v = queue[-1]
+                if v not in preorder:
+                    i = i + 1
+                    preorder[v] = i
+                done = 1
+                v_nbrs = G.neighbors(v)
+                for w in v_nbrs:
+                    if w not in preorder:
+                        queue.append(w)
+                        done = 0
+                        break
+                if done == 1:
+                    lowlink[v] = preorder[v]
+                    for w in v_nbrs:
+                        if w not in scc_found:
+                            if preorder[w] > preorder[v]:
+                                lowlink[v] = min([lowlink[v], lowlink[w]])
+                            else:
+                                lowlink[v] = min([lowlink[v], preorder[w]])
+                    queue.pop()
+                    if lowlink[v] == preorder[v]:
+                        scc_found[v] = True
+                        scc = {v}
+                        while (
+                            scc_queue and preorder[scc_queue[-1]] > preorder[v]
+                        ):
+                            k = scc_queue.pop()
+                            scc_found[k] = True
+                            scc.add(k)
+                        yield scc
+                    else:
+                        scc_queue.append(v)
+
+
+def simple_cycles(G):
+    '''
+    Adapted from networkx: http://networkx.github.io/
+    Parameters
+    ----------
+    G : DiGraph
+    Returns
+    -------
+    cycle_generator: generator
+       A generator that produces elementary cycles of the graph.
+       Each cycle is represented by a list of nodes along the cycle.
+    '''
+
+    def _unblock(thisnode, blocked, B):
+        stack = set([thisnode])
+        while stack:
+            node = stack.pop()
+            if node in blocked:
+                blocked.remove(node)
+                stack.update(B[node])
+                B[node].clear()
+
+    # Johnson's algorithm requires some ordering of the nodes.
+    # We assign the arbitrary ordering given by the strongly connected comps
+    # There is no need to track the ordering as each node removed as processed.
+    # save the actual graph so we can mutate it here
+    # We only take the edges because we do not want to
+    # copy edge and node attributes here.
+    subG = G.subgraph(G.nodes())
+    sccs = list(strongly_connected_components(subG))
+    while sccs:
+        scc = sccs.pop()
+        # order of scc determines ordering of nodes
+        startnode = scc.pop()
+        # Processing node runs 'circuit' routine from recursive version
+        path = [startnode]
+        blocked = set()  # vertex: blocked from search?
+        closed = set()  # nodes involved in a cycle
+        blocked.add(startnode)
+        B = defaultdict(set)  # graph portions that yield no elementary circuit
+        stack = [(startnode, list(subG.neighbors(startnode)))]
+        while stack:
+            thisnode, nbrs = stack[-1]
+            if nbrs:
+                nextnode = nbrs.pop()
+                if nextnode == startnode:
+                    yield path[:]
+                    closed.update(path)
+                elif nextnode not in blocked:
+                    path.append(nextnode)
+                    stack.append((nextnode, list(subG.neighbors(nextnode))))
+                    closed.discard(nextnode)
+                    blocked.add(nextnode)
+                    continue
+            # done with nextnode... look for more neighbors
+            if not nbrs:  # no more nbrs
+                if thisnode in closed:
+                    _unblock(thisnode, blocked, B)
+                else:
+                    for nbr in subG.neighbors(thisnode):
+                        if thisnode not in B[nbr]:
+                            B[nbr].add(thisnode)
+                stack.pop()
+                path.pop()
+        # done processing this node
+        subG.remove_node(startnode)
+        H = subG.subgraph(scc)  # make smaller to avoid work in SCC routine
+        sccs.extend(list(strongly_connected_components(H)))
+
+
+def find_cycle(graph):
+    '''
+    Looks for a cycle in the graph. If found, returns the first cycle.
+    If nodes a1, a2, ..., an are in a cycle, then this returns:
+        [(a1,a2), (a2,a3), ... (an-1,an), (an, a1)]
+    Otherwise returns an empty list.
+    '''
+    cycles = list(simple_cycles(graph))
+    if cycles:
+        nodes = cycles[0]
+        nodes.append(nodes[0])
+        edges = []
+        prev = nodes[0]
+        for node in nodes[1:]:
+            edges.append((prev, node))
+            prev = node
+        return edges
+    else:
+        return []
+
+
+def print_cycle(binary, graph, edges, thread_info, print_stack_trace_fn):
+    '''
+    Prints the cycle in the mutex graph in the following format:
+
+    Potential Deadlock Detected!
+
+    Cycle in lock order graph: M0 => M1 => M2 => M0
+
+    for (m, n) in cycle:
+        Mutex n acquired here while holding Mutex m in thread T:
+            [ stack trace ]
+
+        Mutex m previously acquired by thread T here:
+            [ stack trace ]
+
+    for T in all threads:
+        Thread T was created here:
+            [ stack trace ]
+    '''
+
+    # List of mutexes in the cycle, first and last repeated
+    nodes_in_order = []
+    # Map mutex address -> readable alias
+    node_addr_to_name = {}
+    for counter, (m, n) in enumerate(edges):
+        nodes_in_order.append(m)
+        # For global or static variables, try to symbolize the mutex address.
+        symbol = symbolize_with_objdump(binary, m)
+        if symbol:
+            symbol += ' '
+        node_addr_to_name[m] = 'Mutex M%d (%s0x%016x)' % (counter, symbol, m)
+    nodes_in_order.append(nodes_in_order[0])
+
+    print('----------------\nPotential Deadlock Detected!\n')
+    print(
+        'Cycle in lock order graph: %s\n' %
+        (' => '.join([node_addr_to_name[n] for n in nodes_in_order]))
+    )
+
+    # Set of threads involved in the lock inversion
+    thread_pids = set()
+
+    # For each edge in the cycle, print where the two mutexes were held
+    for (m, n) in edges:
+        thread_pid = graph.attributes(m, n)['thread_pid']
+        thread_comm = graph.attributes(m, n)['thread_comm']
+        first_mutex_stack_id = graph.attributes(m, n)['first_mutex_stack_id']
+        second_mutex_stack_id = graph.attributes(m, n)['second_mutex_stack_id']
+        thread_pids.add(thread_pid)
+        print(
+            '%s acquired here while holding %s in Thread %d (%s):' % (
+                node_addr_to_name[n], node_addr_to_name[m], thread_pid,
+                thread_comm
+            )
+        )
+        print_stack_trace_fn(second_mutex_stack_id)
+        print('')
+        print(
+            '%s previously acquired by the same Thread %d (%s) here:' %
+            (node_addr_to_name[m], thread_pid, thread_comm)
+        )
+        print_stack_trace_fn(first_mutex_stack_id)
+        print('')
+
+    # Print where the threads were created, if available
+    for thread_pid in thread_pids:
+        parent_pid, stack_id, parent_comm = thread_info.get(
+            thread_pid, (None, None, None)
+        )
+        if parent_pid:
+            print(
+                'Thread %d created by Thread %d (%s) here: ' %
+                (thread_pid, parent_pid, parent_comm)
+            )
+            print_stack_trace_fn(stack_id)
+        else:
+            print(
+                'Could not find stack trace where Thread %d was created' %
+                thread_pid
+            )
+        print('')
+
+
+def symbolize_with_objdump(binary, addr):
+    '''
+    Searches the binary for the address using objdump. Returns the symbol if
+    it is found, otherwise returns empty string.
+    '''
+    try:
+        command = (
+            'objdump -tT %s | grep %x | awk {\'print $NF\'} | c++filt' %
+            (binary, addr)
+        )
+        output = subprocess.check_output(command, shell=True)
+        return output.decode('utf-8').strip()
+    except subprocess.CalledProcessError:
+        return ''
+
+
+def strlist(s):
+    '''Given a comma-separated string, returns a list of substrings'''
+    return s.strip().split(',')
+
+
+def main():
+    examples = '''Examples:
+    deadlock 181                 # Analyze PID 181
+
+    deadlock 181 --binary /lib/x86_64-linux-gnu/libpthread.so.0
+                                 # Analyze PID 181 and locks from this binary.
+                                 # If tracing a process that is running from
+                                 # a dynamically-linked binary, this argument
+                                 # is required and should be the path to the
+                                 # pthread library.
+
+    deadlock 181 --verbose
+                                 # Analyze PID 181 and print statistics about
+                                 # the mutex wait graph.
+
+    deadlock 181 --lock-symbols my_mutex_lock1,my_mutex_lock2 \\
+        --unlock-symbols my_mutex_unlock1,my_mutex_unlock2
+                                 # Analyze PID 181 and trace custom mutex
+                                 # symbols instead of pthread mutexes.
+
+    deadlock 181 --dump-graph graph.json
+                                 # Analyze PID 181 and dump the mutex wait
+                                 # graph to graph.json.
+    '''
+    parser = argparse.ArgumentParser(
+        description=(
+            'Detect potential deadlocks (lock inversions) in a running binary.'
+            '\nMust be run as root.'
+        ),
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=examples,
+    )
+    parser.add_argument('pid', type=int, help='Pid to trace')
+    # Binaries with `:` in the path will fail to attach uprobes on kernels
+    # running without this patch: https://lkml.org/lkml/2017/1/13/585.
+    # Symlinks to the binary without `:` in the path can get around this issue.
+    parser.add_argument(
+        '--binary',
+        type=str,
+        default='',
+        help='If set, trace the mutexes from the binary at this path. '
+        'For statically-linked binaries, this argument is not required. '
+        'For dynamically-linked binaries, this argument is required and '
+        'should be the path of the pthread library the binary is using. '
+        'Example: /lib/x86_64-linux-gnu/libpthread.so.0',
+    )
+    parser.add_argument(
+        '--dump-graph',
+        type=str,
+        default='',
+        help='If set, this will dump the mutex graph to the specified file.',
+    )
+    parser.add_argument(
+        '--verbose',
+        action='store_true',
+        help='Print statistics about the mutex wait graph.',
+    )
+    parser.add_argument(
+        '--lock-symbols',
+        type=strlist,
+        default=['pthread_mutex_lock'],
+        help='Comma-separated list of lock symbols to trace. Default is '
+        'pthread_mutex_lock. These symbols cannot be inlined in the binary.',
+    )
+    parser.add_argument(
+        '--unlock-symbols',
+        type=strlist,
+        default=['pthread_mutex_unlock'],
+        help='Comma-separated list of unlock symbols to trace. Default is '
+        'pthread_mutex_unlock. These symbols cannot be inlined in the binary.',
+    )
+    args = parser.parse_args()
+    if not args.binary:
+        try:
+            args.binary = os.readlink('/proc/%d/exe' % args.pid)
+        except OSError as e:
+            print('%s. Is the process (pid=%d) running?' % (str(e), args.pid))
+            sys.exit(1)
+
+    bpf = BPF(src_file=b'deadlock.c')
+
+    # Trace where threads are created
+    bpf.attach_kretprobe(event=bpf.get_syscall_fnname('clone'), fn_name='trace_clone')
+
+    # We must trace unlock first, otherwise in the time we attached the probe
+    # on lock() and have not yet attached the probe on unlock(), a thread can
+    # acquire mutexes and release them, but the release events will not be
+    # traced, resulting in noisy reports.
+    for symbol in args.unlock_symbols:
+        try:
+            bpf.attach_uprobe(
+                name=args.binary,
+                sym=symbol,
+                fn_name='trace_mutex_release',
+                pid=args.pid,
+            )
+        except Exception as e:
+            print('%s. Failed to attach to symbol: %s' % (str(e), symbol))
+            sys.exit(1)
+    for symbol in args.lock_symbols:
+        try:
+            bpf.attach_uprobe(
+                name=args.binary,
+                sym=symbol,
+                fn_name='trace_mutex_acquire',
+                pid=args.pid,
+            )
+        except Exception as e:
+            print('%s. Failed to attach to symbol: %s' % (str(e), symbol))
+            sys.exit(1)
+
+    def print_stack_trace(stack_id):
+        '''Closure that prints the symbolized stack trace.'''
+        for addr in bpf.get_table('stack_traces').walk(stack_id):
+            line = bpf.sym(addr, args.pid)
+            # Try to symbolize with objdump if we cannot with bpf.
+            if line == '[unknown]':
+                symbol = symbolize_with_objdump(args.binary, addr)
+                if symbol:
+                    line = symbol
+            print('@ %016x %s' % (addr, line))
+
+    print('Tracing... Hit Ctrl-C to end.')
+    while True:
+        try:
+            # Map of child thread pid -> parent info
+            thread_info = {
+                child.value: (parent.parent_pid, parent.stack_id, parent.comm)
+                for child, parent in bpf.get_table('thread_to_parent').items()
+            }
+
+            # Mutex wait directed graph. Nodes are mutexes. Edge (A,B) exists
+            # if there exists some thread T where lock(A) was called and
+            # lock(B) was called before unlock(A) was called.
+            graph = DiGraph()
+            for key, leaf in bpf.get_table('edges').items():
+                graph.add_edge(
+                    key.mutex1,
+                    key.mutex2,
+                    thread_pid=leaf.thread_pid,
+                    thread_comm=leaf.comm.decode('utf-8'),
+                    first_mutex_stack_id=leaf.mutex1_stack_id,
+                    second_mutex_stack_id=leaf.mutex2_stack_id,
+                )
+            if args.verbose:
+                print(
+                    'Mutexes: %d, Edges: %d' %
+                    (len(graph.nodes()), len(graph.edges()))
+                )
+            if args.dump_graph:
+                with open(args.dump_graph, 'w') as f:
+                    data = graph.node_link_data()
+                    f.write(json.dumps(data, indent=2))
+
+            cycle = find_cycle(graph)
+            if cycle:
+                print_cycle(
+                    args.binary, graph, cycle, thread_info, print_stack_trace
+                )
+                sys.exit(1)
+
+            time.sleep(1)
+        except KeyboardInterrupt:
+            break
+
+
+if __name__ == '__main__':
+    main()