From 127bc6d1c3169a80c735b01588c968b85d2df944 Mon Sep 17 00:00:00 2001 From: Timotej Lazar Date: Wed, 4 Feb 2015 16:20:55 +0100 Subject: Minor cleanups in monkey.monkey --- monkey/monkey.py | 34 ++++++++++++++++++---------------- 1 file changed, 18 insertions(+), 16 deletions(-) diff --git a/monkey/monkey.py b/monkey/monkey.py index cd44bac..cae42ae 100755 --- a/monkey/monkey.py +++ b/monkey/monkey.py @@ -14,14 +14,10 @@ from .util import PQueue, Token # Return (solution, edits, time spent, #programs checked). If no solution is # found within [timeout] seconds, solution='' and edits=[]. def fix(name, code, edits, aux_code='', timeout=30, debug=False): - todo = PQueue() # priority queue of candidate solutions - done = set() # programs we have already visited - - inserts, removes, changes = classify_edits(edits) - # Generate states that can be reached from the given program with one edit. # Program code is given as a list of [lines], where each line is a list of # tokens. Rule ranges are given in [rules] (see prolog.util.decompose). + inserts, removes, changes = classify_edits(edits) def step(lines, rules, prev=None): # Apply edits in order from top to bottom; skip lines with index lower # than last step. @@ -106,18 +102,22 @@ def fix(name, code, edits, aux_code='', timeout=30, debug=False): i += 1 return new_steps - # Add the initial program to the queue. + # Prevents useless edits with cost=1.0. + step_cost = 0.99 + + # Main loop: best-first search through generated programs. + todo = PQueue() # priority queue of candidate solutions + done = set() # programs we have already visited + + # Each program gets a task with the sequence of edits that generated it and + # the associated cost. First candidate with cost 1 is the initial program. lines, rules = decompose(code) todo.push(((tuple(lines), tuple(rules)), (), 1.0), -1.0) - start_time = time.monotonic() n_tested = 0 - while True: - # Have we been at it for too long? - total_time = time.monotonic() - start_time - if total_time > timeout: - break - + start_time = time.monotonic() + total_time = 0 + while total_time < timeout: # Get next candidate. task = todo.pop() if task == None: @@ -130,6 +130,7 @@ def fix(name, code, edits, aux_code='', timeout=30, debug=False): continue done.add(code) + # Print some info about the current task. if debug: print('Cost {:.12f}'.format(path_cost)) for step_type, line, (before, after) in path: @@ -142,15 +143,16 @@ def fix(name, code, edits, aux_code='', timeout=30, debug=False): n_tested += 1 # Otherwise generate new solutions. - path = list(path) prev_step = path[-1] if path else None for new_lines, new_rules, new_step, new_cost in step(lines, rules, prev_step): - new_path_cost = path_cost * new_cost * 0.99 + new_path_cost = path_cost * new_cost * step_cost if new_path_cost < 0.005: continue - new_path = tuple(path + [new_step]) + new_path = path + (new_step,) todo.push(((tuple(new_lines), tuple(new_rules)), new_path, new_path_cost), -new_path_cost) + total_time = time.monotonic() - start_time + return '', [], total_time, n_tested # Return a list of character ranges modified by the sequence [edits]. -- cgit v1.2.1