示例#1
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def flooding(S, E, T, graph):
    queue = list()
    queue.append({'stack': S.copy(), 'trace': T.copy()})
    seen_edges = set()
    while True:
        path = queue.pop(0)
        cur_stack = path['stack']
        cur_trace = path['trace']
        cur_node = cur_stack[-1]

        # check for bad test case
        if len(cur_trace) > 2 * len(graph.edges):
            continue

        # check if all edges covered
        if len(E - seen_edges) == 0:
            queue.append(path)
            return queue

        if cur_node.label == 'acc':
            queue.append(path.copy())
            continue
        # check if there is a reduce rule that may exist for this state
        reduce_edges = []
        if cur_node.reduce_rule is not None:
            for rule in cur_node.reduce_rule:
                reduce_edges.append(
                    get_reduce_edge(rule[0], rule[1], cur_node, cur_stack))

        # check if the previous move was reduce so we should shift a non-terminal
        if len(cur_trace) > 0 and cur_trace[-1].is_pop:
            shift_edge: Edge
            for edge in cur_node.edges:
                if edge.label == cur_trace[-1].label and not edge.is_pop:
                    shift_edge = edge
                    break
            seen_edges.add(shift_edge)
            push(cur_stack, cur_trace, queue, shift_edge)
        else:
            # if the previous step wasn't a reduce then we should shift on terminals and check
            # for valid reductions on all edges
            for edge in cur_node.edges:
                # avoid shifting on an self-loop
                if edge.label in graph.terminal and (
                        edge.next_node != cur_node or edge not in seen_edges):
                    seen_edges.add(edge)
                    push(cur_stack, cur_trace, queue, edge)
                # check that reduction edge is correct edge
                elif edge.label in graph.nonterminal and edge in reduce_edges:
                    for rule_index in range(len(reduce_edges)):
                        if edge == reduce_edges[rule_index]:
                            # pop nodes of stack
                            pop(cur_stack, cur_trace, queue, edge,
                                cur_node.reduce_rule[rule_index][1])
                            seen_edges.add(edge)
示例#2
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def path_completion(S, T, goal_label, graph):
    queue = list()
    queue.append({'stack': S.copy(), 'trace': T.copy()})
    while len(queue) > 0:
        path = queue.pop(0)
        cur_stack = path['stack']
        cur_trace = path['trace']
        cur_node = cur_stack[-1]

        # check if the destination has been reached
        if str(cur_node.label) == goal_label:
            return path

        # check for bad test case
        if len(cur_trace) > 2 * len(graph.edges):
            continue

        # check if there is a reduce rule that may exist for this state
        reduce_edges = []
        if cur_node.reduce_rule is not None:
            for rule in cur_node.reduce_rule:
                reduce_edges.append(
                    get_reduce_edge(rule[0], rule[1], cur_node, cur_stack))

        # check if the previous move was pop so we should shift a non-terminal
        if len(cur_trace) > 0 and cur_trace[-1].is_pop:
            shift_edge: Edge
            for edge in cur_node.edges:
                if edge.label == cur_trace[-1].label and not edge.is_pop:
                    shift_edge = edge
                    break
            push(cur_stack, cur_trace, queue, shift_edge)
        else:
            # if the previous step wasn't a pop then we should shift on terminals and check
            # for valid reductions on all edges
            for edge in cur_node.edges:
                if edge.label in graph.terminal and edge.next_node != cur_node:
                    push(cur_stack, cur_trace, queue, edge)
                # check that reduction edge is correct edge
                elif edge.label in graph.nonterminal and edge in reduce_edges:
                    # pop nodes of stack
                    for rule_index in range(len(reduce_edges)):
                        if edge == reduce_edges[rule_index]:
                            # pop nodes of stack
                            pop(cur_stack, cur_trace, queue, edge,
                                cur_node.reduce_rule[rule_index][1])
示例#3
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def lookback_for_pop(candidate, graph, unseen_edges):
    target_stack_depth = candidate.pop_count
    src = candidate.next_node
    target = candidate.source
    possible_solutions = []
    max_len = len(graph.edges)
    queue = list()
    queue.append({'stack': [src], 'trace': []})
    while len(queue) > 0:
        path = queue.pop(0)
        cur_stack = path['stack']
        cur_trace = path['trace']
        cur_node = cur_stack[-1]

        # check for bad test case
        if len(cur_trace) > max_len:
            continue

        if cur_node == target and len(cur_stack) - 1 == target_stack_depth:
            possible_solutions.append(path.copy())
            max_len = len(cur_trace)
            continue
        # check if there is a reduce rule that may exist for this state
        reduce_edges = []
        if cur_node.reduce_rule is not None:
            for rule in cur_node.reduce_rule:
                pop_amount = rule[1]
                # don't take excessively large pops
                if len(cur_stack) >= pop_amount + 1:
                    reduce_edges.append(
                        get_reduce_edge(rule[0], rule[1], cur_node, cur_stack))

        # check if the previous move was reduce so we should shift a non-terminal
        if len(cur_trace) > 0 and cur_trace[-1].is_pop:
            shift_edge: Edge
            for edge in cur_node.edges:
                if edge.label == cur_trace[-1].label and not edge.is_pop:
                    shift_edge = edge
                    break
            push(cur_stack, cur_trace, queue, shift_edge)
        else:
            # if the previous step wasn't a reduce then we should shift on terminals and check
            # for valid reductions on all edges
            for edge in cur_node.edges:
                if edge.label in graph.terminal:
                    push(cur_stack, cur_trace, queue, edge)
                # check that reduction edge is correct edge
                elif edge.label in graph.nonterminal and edge in reduce_edges:
                    for rule_index in range(len(reduce_edges)):
                        if edge == reduce_edges[rule_index]:
                            # pop nodes of stack
                            pop(cur_stack, cur_trace, queue, edge, pop_amount)
    # find the possible solution that covers as many new edges as possible
    best_path = possible_solutions[0]
    new_count = 0
    for e in best_path:
        if e in unseen_edges:
            new_count += 1
    for path in possible_solutions[1:]:
        count = 0
        for e in path:
            if e in unseen_edges:
                count += 1
        if count > new_count:
            new_count = count
            best_path = path
    return best_path
示例#4
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def path_completion_improved(S, T, goal_label, graph):
    """Complete a path that was generated during the flooding phase"""
    high_priority_queue = list()
    low_priority_queue = list()
    stack_depth_dict = precalc_node_stack_depth(T)
    high_priority_queue.append({
        'stack': S.copy(),
        'trace': T.copy(),
        'stack_history': stack_depth_dict
    })

    while len(high_priority_queue) + len(low_priority_queue) > 0:
        path = None
        if len(high_priority_queue) > 0:
            path = high_priority_queue.pop(0)
        else:
            path = low_priority_queue.pop(0)

        cur_stack = path['stack']
        cur_trace = path['trace']
        cur_node = cur_stack[-1]
        cur_stack_history = path['stack_history']

        # check if the destination has been reached
        if str(cur_node.label) == goal_label:
            return path

        # check for bad test case
        if len(cur_trace) > 2 * len(graph.edges):
            continue

        # check if there is a reduce rule that may exist for this state
        reduce_edges = []
        if cur_node.reduce_rule is not None:
            for rule in cur_node.reduce_rule:
                reduce_edges.append(
                    get_reduce_edge(rule[0], rule[1], cur_node, cur_stack))

        # check if the previous move was pop so we should shift a non-terminal
        if len(cur_trace) > 0 and cur_trace[-1].is_pop:
            shift_edge: Edge
            for edge in cur_node.edges:
                if edge.label == cur_trace[-1].label and not edge.is_pop:
                    shift_edge = edge
                    break
            # always push even if this is a loop
            push(cur_stack,
                 cur_trace,
                 high_priority_queue,
                 shift_edge,
                 cur_stack_history=cur_stack_history)
        else:
            # if the previous step wasn't a pop then we should shift on terminals and check
            # for valid reductions on all edges
            stuck_flag = True
            for edge in cur_node.edges:
                if edge.label in graph.terminal:
                    # if this is a loop we only take it if the stack does not increase in size
                    if edge.next_node.label not in cur_stack_history or (
                            edge.next_node.label in cur_stack_history
                            and cur_stack_history[edge.next_node.label] >=
                            len(cur_stack) + 1):
                        push(cur_stack,
                             cur_trace,
                             high_priority_queue,
                             edge,
                             cur_stack_history=cur_stack_history)
                    else:
                        push(cur_stack,
                             cur_trace,
                             low_priority_queue,
                             edge,
                             cur_stack_history=cur_stack_history)
                # check that reduction edge is correct edge
                elif edge.label in graph.nonterminal and edge in reduce_edges:
                    # pop nodes of stack
                    for rule_index in range(len(reduce_edges)):
                        if edge == reduce_edges[rule_index]:
                            # if this is a loop we only take it if the stack does not increase in size
                            if edge.next_node.label not in cur_stack_history or (
                                    edge.next_node.label in cur_stack_history
                                    and cur_stack_history[edge.next_node.label]
                                    >= len(cur_stack) - edge.pop_count):
                                # pop nodes of stack
                                pop(cur_stack,
                                    cur_trace,
                                    high_priority_queue,
                                    edge,
                                    cur_node.reduce_rule[rule_index][1],
                                    cur_stack_history=cur_stack_history)
                            else:
                                pop(cur_stack,
                                    cur_trace,
                                    low_priority_queue,
                                    edge,
                                    cur_node.reduce_rule[rule_index][1],
                                    cur_stack_history=cur_stack_history)
示例#5
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def flooding_improved(S, E, T, graph):
    fresh_queue = list(
    )  # traversals that have just covered a previously unseen edge
    stale_queue = list(
    )  # traversal that has covered a previously unseen edge but now has no more unseen edges to cover
    brute_force_queue = list(
    )  # traversal that covers an already seen edge as its last edge. Used when no fresh_queue
    fresh_queue.append({'stack': S.copy(), 'trace': T.copy()})
    seen_edges = set()
    while True:
        new_edge_seen = False
        path_from_brute = False
        path = None
        if len(fresh_queue) > 0:
            path = fresh_queue.pop(0)
        else:
            unblock(S, E, T, graph, seen_edges, fresh_queue, stale_queue)
            continue
        cur_stack = path['stack']
        cur_trace = path['trace']
        cur_node = cur_stack[-1]

        # check for bad test case
        if len(cur_trace) > 2 * len(graph.edges):
            continue

        # check if all edges covered
        if len(E - seen_edges) == 0:
            stale_queue.append(path)
            return stale_queue + fresh_queue

        if cur_node.label == 'acc':
            stale_queue.append(path.copy())
            continue
        # check if there is a reduce rule that may exist for this state
        reduce_edges = []
        if cur_node.reduce_rule is not None:
            for rule in cur_node.reduce_rule:
                reduce_edges.append(
                    get_reduce_edge(rule[0], rule[1], cur_node, cur_stack))

        # check if the previous move was reduce so we should shift a non-terminal
        if len(cur_trace) > 0 and cur_trace[-1].is_pop:
            shift_edge: Edge
            for edge in cur_node.edges:
                if edge.label == cur_trace[-1].label and not edge.is_pop:
                    shift_edge = edge
                    break
            if shift_edge not in seen_edges:
                push(cur_stack, cur_trace, fresh_queue, shift_edge)
                new_edge_seen = True
            else:
                push(cur_stack, cur_trace, brute_force_queue, shift_edge)
            seen_edges.add(shift_edge)

        else:
            # if the previous step wasn't a reduce then we should shift on terminals and check
            # for valid reductions on all edges
            for edge in cur_node.edges:
                # avoid shifting on an self-loop
                if edge.label in graph.terminal:
                    if edge not in seen_edges:
                        new_edge_seen = True
                        push(cur_stack, cur_trace, fresh_queue, edge)
                    else:
                        push(cur_stack, cur_trace, brute_force_queue, edge)
                    seen_edges.add(edge)
                # check that reduction edge is correct edge
                elif edge.label in graph.nonterminal and edge in reduce_edges:
                    for rule_index in range(len(reduce_edges)):
                        if edge == reduce_edges[rule_index]:
                            # pop nodes of stack
                            if edge not in seen_edges:
                                new_edge_seen = True
                                pop(cur_stack, cur_trace, fresh_queue, edge,
                                    cur_node.reduce_rule[rule_index][1])
                            else:
                                pop(cur_stack, cur_trace, brute_force_queue,
                                    edge, cur_node.reduce_rule[rule_index][1])
                            seen_edges.add(edge)
        if not new_edge_seen and not path_from_brute:
            stale_queue.append(path)