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dom_test.py
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dom_test.py
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import csv
import difflib
import json
import os
import re
from lxml import etree
ignoredAttrib = {'style', 'type'}
matched21 = {}
matched12 = {}
matched12_xpaths = {}
nodes_info = {1: {}, 2: {}}
chrome_tree = None
firefox_tree = None
THRESHOLD_LEVEL = 0.75
THRESHOLD_GLOBAL = 0.85
folder = 'data'
dom_files_chrome = ['_'.join(f.split('_')[:-1]) for f in os.listdir(folder) if 'dom' in f and 'chrome' in f]
dom_files_firefox = ['_'.join(f.split('_')[:-1]) for f in os.listdir(folder) if 'dom' in f and 'firefox' in f]
dom_files = list(set(dom_files_firefox) & set(dom_files_chrome))
tagsIgnore = {'A', 'AREA', 'B', 'BLOCKQUOTE',
'BR', 'CANVAS', 'CENTER', 'CSACTIONDICT', 'CSSCRIPTDICT', 'CUFON',
'CUFONTEXT', 'DD', 'EM', 'EMBED', 'FIELDSET', 'FONT', 'FORM',
'HEAD', 'HR', 'I', 'LABEL', 'LEGEND', 'LINK', 'MAP', 'MENUMACHINE',
'META', 'NOFRAMES', 'NOSCRIPT', 'OBJECT', 'OPTGROUP', 'OPTION',
'PARAM', 'S', 'SCRIPT', 'SMALL', 'SPAN', 'STRIKE', 'STRONG',
'STYLE', 'TBODY', 'TITLE', 'TR', 'TT', 'U', 'UL'}
tagsContainer = {'DD', 'DIV', 'DT', 'P',
'TD', 'TR'}
SIZE_DIFF_THRESH = 0.7
SIZE_DIFF_IGNORE = 0.1
def processAttributes(attrib):
for key in ignoredAttrib:
attrib.pop(key, None)
return attrib
def cleanAndCompare(str1, str2):
str1 = re.sub(r'[\'\'\\s]', '', str1)
str2 = re.sub(r'[\'\'\\s]', '', str2)
return str1 == str2
def mapDiff(x, y):
matchCount = 0
for key in x.keys():
if key in y.keys() and cleanAndCompare(x[key], y[key]):
matchCount += 1
for key in y.keys():
if key in x.keys() and cleanAndCompare(x[key], y[key]):
matchCount += 1
return matchCount
def getMapSimilarity(x, y):
if not x and not y:
return 1
total = len(x) + len(y)
return mapDiff(x, y) / total
def calculateMatchIndex(x, y):
XPATH = 0.75
ATTRIB = 0.25
xPath1 = chrome_tree.getpath(x)
xPath2 = firefox_tree.getpath(y)
if xPath1 == xPath2:
xPathSim = 1
else:
xPathSim = difflib.SequenceMatcher(None, xPath1, xPath2).ratio()
attrib_x = processAttributes(x.attrib)
attrib_y = processAttributes(y.attrib)
attribSim = getMapSimilarity(attrib_x, attrib_y)
return XPATH * xPathSim + ATTRIB * attribSim
def ExactMatchVisitor(root1, root2):
global matched21, matched12
for node1 in root1.iter(tag=etree.Element):
for node2 in root2.iter(tag=etree.Element):
if node1.tag == node2.tag:
if node2 not in matched21.keys():
matchIndex = calculateMatchIndex(node1, node2)
if matchIndex == 1.0:
matched12[node1] = node2
matched21[node2] = node1
break
def AssignLevelVisitor(root, sno):
levels = []
for node in root.iter(tag=etree.Element):
if node.getparent() is None:
nodes_info[sno][node]['level'] = 0
levels.append([])
levels[0].append(node)
else:
nodes_info[sno][node]['level'] = nodes_info[sno][node.getparent()]['level'] + 1
if len(levels) == nodes_info[sno][node]['level']:
levels.append([])
levels[nodes_info[sno][node]['level']].append(node)
return levels
def ApproxMatchVisitor(worklist, root2):
global matched21, matched12
for node1 in worklist:
bestMatchIndex = 0
bestMatchNode = None
for node2 in root2.iter(tag=etree.Element):
if node1.tag == node2.tag:
if node2 not in matched21.keys():
matchIndex = calculateMatchIndex(node1, node2)
if matchIndex > THRESHOLD_GLOBAL and matchIndex > bestMatchIndex:
bestMatchIndex = matchIndex
bestMatchNode = node2
if bestMatchNode is not None:
matched12[node1] = bestMatchNode
matched21[bestMatchNode] = node1
def do_match(root1, root2):
global matched21, matched12
# 1. perfect matching
ExactMatchVisitor(root1, root2)
# Assign Levels
AssignLevelVisitor(root1, 1)
levels2 = AssignLevelVisitor(root2, 2)
unmatched_nodes = [node for node in set(chrome_etree.iter(tag=etree.Element)) - set(matched12.keys())]
worklist = []
# 2. level matching
for node in unmatched_nodes:
level = nodes_info[1][node]['level']
if level < len(levels2):
lnodes = levels2[level]
bestMatchIndex = 0
bestMatchNode = None
for ln in lnodes:
if ln not in matched21.keys():
matchIndex = calculateMatchIndex(node, ln)
if matchIndex > THRESHOLD_LEVEL and matchIndex > bestMatchIndex:
bestMatchIndex = matchIndex
bestMatchNode = ln
if bestMatchNode is not None:
matched12[node] = bestMatchNode
matched21[bestMatchNode] = node
else:
worklist.append(node)
# 3. Approximate global matching
ApproxMatchVisitor(worklist, root2)
def isLayoutNode(node, xpath, loc):
if node.tag.upper() in tagsIgnore:
return False
if xpath not in loc:
return False
x1 = loc[xpath]['x']
y1 = loc[xpath]['y']
height = loc[xpath]['height']
width = loc[xpath]['width']
x2 = x1 + width
y2 = y1 + height
if x1 < 0 or y1 < 0 or x2 <= 0 or y2 <= 0:
return False
negligible_dim = 5
if height <= negligible_dim or width <= negligible_dim:
return False
if node.tag.upper() in tagsContainer:
if len(node) == 0:
return False
hasVisibleChild = False
for child in node:
if child.text is not None or child.tag.upper() not in tagsIgnore:
hasVisibleChild = True
if hasVisibleChild is False:
return False
return True
def contains(n, node, loc):
n_x1 = loc[n]['x']
n_y1 = loc[n]['y']
n_x2 = n_x1 + loc[n]['width']
n_y2 = n_y1 + loc[n]['height']
node_x1 = loc[node]['x']
node_y1 = loc[node]['y']
node_x2 = node_x1 + loc[node]['width']
node_y2 = node_y1 + loc[node]['height']
if n_x1 <= node_x1 and n_y1 <= node_y1 and n_x2 >= node_x2 and n_y2 >= node_y2:
return True
return False
def get_area(node, loc):
return loc[node]['height'] * loc[node]['width']
def hasSignificantSizeDiff(p, c):
pcSizeDiff = c / p
if pcSizeDiff < SIZE_DIFF_THRESH and pcSizeDiff > SIZE_DIFF_IGNORE:
return True
return False
def calcError(a, b, delta):
return abs(a - b) / delta
def populate_contain_alignments(parent, child, loc):
deltaH = 5
deltaW = 5
edge_info = {'SizeDiffX': False,
'xError': 0,
'hFill': False,
'LeftJustified': False,
'RightJustified': False,
'Centered': False,
'SizeDiffY': False,
'yError': 0,
'vFill': False,
'TopAligned': False,
'BottomAligned': False,
'Middle': False
}
p_x1 = loc[parent]['x']
p_x2 = loc[parent]['x'] + loc[parent]['width']
p_y1 = loc[parent]['y']
p_y2 = loc[parent]['y'] + loc[parent]['height']
c_x1 = loc[child]['x']
c_x2 = loc[child]['x'] + loc[child]['width']
c_y1 = loc[child]['y']
c_y2 = loc[child]['y'] + loc[child]['height']
px = (p_x1 + p_x2) / 2
py = (p_y1 + p_y2) / 2
cx = (c_x1 + c_x2) / 2
cy = (c_y1 + c_y2) / 2
pw = loc[parent]['width']
cw = loc[child]['width']
dW = cw / 3
ph = loc[parent]['height']
ch = loc[child]['height']
dH = ch / 3
if cw < 15 and pw < 15:
return edge_info
if hasSignificantSizeDiff(pw, cw):
edge_info['SizeDiffX'] = True
if abs(px - cx) <= deltaW and abs(p_x1 - c_x1) <= deltaW and abs(p_x2 - c_x2) <= deltaW:
edge_info['hFill'] = True
else:
if abs(c_x1 - p_x1) <= dW:
edge_info['LeftJustified'] = True
edge_info['xError'] = calcError(c_x1, p_x1, dW)
elif abs(c_x2 - c_x2) <= dW:
edge_info['RightJustified'] = True
edge_info['xError'] = calcError(c_x2, c_x2, dW)
elif abs(cx - px) <= dW:
edge_info['Centered'] = True
edge_info['xError'] = calcError(cx, px, dW)
if hasSignificantSizeDiff(ph, ch):
edge_info['SizeDiffY'] = True
if abs(py - cy) <= deltaW and abs(p_y1 - c_y1) <= deltaH and abs(p_y2 - c_y2) <= deltaH:
edge_info['hFill'] = True
else:
if abs(c_y1 - p_y1) <= dH:
edge_info['TopAligned'] = True
edge_info['yError'] = calcError(c_y1, p_y1, dH)
elif abs(c_y2 - p_y2) <= dH:
edge_info['BottomAligned'] = True
edge_info['yError'] = calcError(c_y2, p_y2, dH)
elif abs(cy - py) <= dH:
edge_info['Middle'] = True
edge_info['yError'] = calcError(cy, py, dH)
return edge_info
def populate_parent_edges(nodes, loc, contains_edge_info):
cMap = {}
while len(nodes) > 0:
node = nodes[0]
nodes.pop(0)
parent = None
for n in nodes:
if contains(n, node, loc):
if parent is not None and get_area(parent, loc) <= get_area(n, loc):
continue
parent = n
if parent is not None:
if parent not in cMap:
cMap[parent] = []
cMap[parent].append(node)
contains_edge_info[(parent, node)] = populate_contain_alignments(parent, node, loc)
return cMap
def populate_sibling_properties(node1, node2, loc):
deltaH = 5
deltaW = 5
edge_info = {'LeftEdgeAligned': False,
'RightEdgeAligned': False,
'TopEdgeAligned': False,
'BottomEdgeAligned': False,
'LeftRight': False,
'RightLeft': False,
'TopBottom': False,
'BottomTop': False,
'TBDiff': 0,
'BTDiff': 0,
'RLDiff': 0,
'LRDiff': 0
}
node1_x1 = loc[node1]['x']
node1_x2 = loc[node1]['x'] + loc[node1]['width']
node1_y1 = loc[node1]['y']
node1_y2 = loc[node1]['y'] + loc[node1]['height']
node2_x1 = loc[node2]['x']
node2_x2 = loc[node2]['x'] + loc[node2]['width']
node2_y1 = loc[node2]['y']
node2_y2 = loc[node2]['y'] + loc[node2]['height']
edge_info['TBDiff'] = abs(node1_y1 - node2_y2)
edge_info['BTDiff'] = abs(node1_y2 - node2_y1)
edge_info['LRDiff'] = abs(node1_x2 - node2_x1)
edge_info['RLDiff'] = abs(node1_x1 - node2_x2)
if abs(node1_x1 - node2_x1) <= deltaW:
edge_info['LeftEdgeAligned'] = True
if abs(node1_x2 - node2_x2) <= deltaW:
edge_info['RightEdgeAligned'] = True
if abs(node1_y1 - node2_y1) <= deltaH:
edge_info['TopEdgeAligned'] = True
if abs(node1_y2 - node2_y2) <= deltaH:
edge_info['BottomEdgeAligned'] = True
if node1_x2 < node2_x1:
edge_info['LeftRight'] = True
if node2_x2 < node1_x1:
edge_info['RightLeft'] = True
if node1_y2 < node2_y1:
edge_info['TopBottom'] = True
if node2_y2 < node1_y1:
edge_info['BottomTop'] = True
return edge_info
def populate_sibling_edges(cMap, loc, siblings_edge_info):
for value in cMap.values():
siblings = value[:]
while len(siblings) > 0:
node = siblings[0]
siblings.pop(0)
for n in siblings:
siblings_edge_info[(node, n)] = populate_sibling_properties(node, n, loc)
siblings_edge_info[(n, node)] = populate_sibling_properties(n, node, loc)
def get_parent(c, cMap):
for parent, children in cMap.items():
for child in children:
if child == c:
return parent
return None
def testSizeDiff(p1, p2, e1, e2):
if p1 ^ p2:
if p1 and e1 < 0.8:
return True
if p2 and e2 < 0.8:
return True
return False
def isSignificantDiff(a, b):
diffThreshold = 5
if abs(a - b) > diffThreshold:
return True
return False
def compare_parents(c1, c2, cMap1, cMap2, contains_edge_info1, contains_edge_info2):
issues = []
p1 = get_parent(c1, cMap1)
p2 = get_parent(c2, cMap2)
if p1 is None and p2 is None:
return issues
elif p1 is None and p2 is not None:
issues.append('MISSING-PARENT-1 %s %s' % (c1, c2))
return issues
elif p1 is not None and p2 is None:
issues.append('MISSING-PARENT-2 %s %s' % (c1, c2))
return issues
expected_p2 = matched12_xpaths[p1]
if expected_p2 != p2:
issues.append('PARENTS DIFFER (%s-%s) (%s-%s)' % (c1, c2, p2, expected_p2))
return issues
# matching SizeDiffY for both c1 and c2 as we are comparing y values in it. (different from xperts implementation)
if contains_edge_info1[(p1, c1)]['SizeDiffY'] and contains_edge_info2[(p2, c2)]['SizeDiffY']:
if testSizeDiff(contains_edge_info1[(p1, c1)]['TopAligned'], contains_edge_info2[(p2, c2)]['TopAligned'], contains_edge_info1[(p1, c1)]['yError'], contains_edge_info2[(p2, c2)]['yError']):
issues.append('TOP-ALIGNMENT %s %s' % (c1, c2))
if testSizeDiff(contains_edge_info1[(p1, c1)]['BottomAligned'], contains_edge_info2[(p2, c2)]['BottomAligned'], contains_edge_info1[(p1, c1)]['yError'], contains_edge_info2[(p2, c2)]['yError']):
issues.append('BOTTOM-ALIGNMENT %s %s' % (c1, c2))
if testSizeDiff(contains_edge_info1[(p1, c1)]['Middle'], contains_edge_info2[(p2, c2)]['Middle'], contains_edge_info1[(p1, c1)]['yError'], contains_edge_info2[(p2, c2)]['yError']):
issues.append('VMID-ALIGNMENT %s %s' % (c1, c2))
if contains_edge_info1[(p1, c1)]['vFill'] ^ contains_edge_info2[(p2, c2)]['vFill']:
issues.append('VFILL %s %s' % (c1, c2))
if contains_edge_info1[(p1, c1)]['SizeDiffX'] and contains_edge_info2[(p2, c2)]['SizeDiffX']:
if testSizeDiff(contains_edge_info1[(p1, c1)]['LeftJustified'], contains_edge_info2[(p2, c2)]['LeftJustified'], contains_edge_info1[(p1, c1)]['xError'], contains_edge_info2[(p2, c2)]['xError']):
issues.append('LEFT-JUSTIFICATION %s %s' % (c1, c2))
if testSizeDiff(contains_edge_info1[(p1, c1)]['RightJustified'], contains_edge_info2[(p2, c2)]['RightJustified'], contains_edge_info1[(p1, c1)]['xError'], contains_edge_info2[(p2, c2)]['xError']):
issues.append('RIGHT-JUSTIFICATION %s %s' % (c1, c2))
if testSizeDiff(contains_edge_info1[(p1, c1)]['Centered'], contains_edge_info2[(p2, c2)]['Centered'], contains_edge_info1[(p1, c1)]['xError'], contains_edge_info2[(p2, c2)]['xError']):
issues.append('CENTER-ALIGNMENT %s %s' % (c1, c2))
if contains_edge_info1[(p1, c1)]['hFill'] ^ contains_edge_info2[(p2, c2)]['hFill']:
issues.append('HFILL %s %s' % (c1, c2))
return issues
def get_siblings(c, cMap):
for parent, children in cMap.items():
for child in children:
if child == c:
children.remove(child)
return children[:]
return []
def compare_siblings(c1, c2, cMap1, cMap2, siblings_edge_info1, siblings_edge_info2):
issues = []
s_c1 = get_siblings(c1, cMap1)
s_c2 = get_siblings(c2, cMap2)
matched = {}
unmatch1 = []
unmatch2 = []
for s1 in s_c1:
match = False
for s2 in s_c2:
if matched12_xpaths[s1] == s2:
matched[s1] = s2
s_c2.remove(s2)
match = True
break
if match is False:
unmatch1.append(s1)
unmatch2 = s_c2
for sib in unmatch1:
issues.append('MISSING-SIBLING-1 - %s' % sib)
for sib in unmatch2:
issues.append('MISSING-SIBLING-2 - %s' % sib)
for x, y in matched.items():
if siblings_edge_info1[(c1, x)]['TopEdgeAligned'] ^ siblings_edge_info2[(c2, y)]['TopEdgeAligned']:
issues.append('TOP-EDGE-ALIGNMENT %s - %s' % (x, y))
if siblings_edge_info1[(c1, x)]['RightEdgeAligned'] ^ siblings_edge_info2[(c2, y)]['RightEdgeAligned']:
issues.append('RIGHT-EDGE-ALIGNMENT %s - %s' % (x, y))
if siblings_edge_info1[(c1, x)]['BottomEdgeAligned'] ^ siblings_edge_info2[(c2, y)]['BottomEdgeAligned']:
issues.append('BOTTOM-EDGE-ALIGNMENT %s - %s' % (x, y))
if siblings_edge_info1[(c1, x)]['LeftEdgeAligned'] ^ siblings_edge_info2[(c2, y)]['LeftEdgeAligned']:
issues.append('LEFT-EDGE-ALIGNMENT %s - %s' % (x, y))
if siblings_edge_info1[(c1, x)]['TopBottom'] ^ siblings_edge_info2[(c2, y)]['TopBottom'] and isSignificantDiff(siblings_edge_info1[(c1, x)]['TBDiff'], siblings_edge_info2[(c2, y)]['TBDiff']):
issues.append('TOP-BOTTOM %s - %s' % (x, y))
if siblings_edge_info1[(c1, x)]['BottomTop'] ^ siblings_edge_info2[(c2, y)]['BottomTop'] and isSignificantDiff(siblings_edge_info1[(c1, x)]['BTDiff'], siblings_edge_info2[(c2, y)]['BTDiff']):
issues.append('BOTTOM-TOP %s - %s' % (x, y))
if siblings_edge_info1[(c1, x)]['LeftRight'] ^ siblings_edge_info2[(c2, y)]['LeftRight'] and isSignificantDiff(siblings_edge_info1[(c1, x)]['LRDiff'], siblings_edge_info2[(c2, y)]['LRDiff']):
issues.append('LEFT-RIGHT %s - %s' % (x, y))
if siblings_edge_info1[(c1, x)]['RightLeft'] ^ siblings_edge_info2[(c2, y)]['RightLeft'] and isSignificantDiff(siblings_edge_info1[(c1, x)]['RLDiff'], siblings_edge_info2[(c2, y)]['RLDiff']):
issues.append('RIGHT-LEFT %s - %s' % (x, y))
return issues
# 1 -> chrome 2 -> firefox
results = []
for dom_file in dom_files:
matched21 = {}
matched12 = {}
matched12_xpaths = {}
chrome_dom_file = os.path.join(folder, dom_file + '_chrome.txt')
firefox_dom_file = os.path.join(folder, dom_file + '_firefox.txt')
chrome_loc_file = os.path.join(folder, dom_file.replace('dom', 'loc') + '_chrome.txt')
firefox_loc_file = os.path.join(folder, dom_file.replace('dom', 'loc') + '_firefox.txt')
print(chrome_dom_file)
print(firefox_dom_file)
with open(chrome_dom_file, 'r') as f:
chrome_dom = f.read()
with open(firefox_dom_file, 'r') as f:
firefox_dom = f.read()
with open(chrome_loc_file, 'r') as f:
chrome_loc = json.load(f)
with open(firefox_loc_file, 'r') as f:
firefox_loc = json.load(f)
chrome_etree = etree.HTML(chrome_dom)
firefox_etree = etree.HTML(firefox_dom)
chrome_tree = etree.ElementTree(chrome_etree)
firefox_tree = etree.ElementTree(firefox_etree)
for node in chrome_etree.iter(tag=etree.Element):
nodes_info[1][node] = {}
for node in firefox_etree.iter(tag=etree.Element):
nodes_info[2][node] = {}
chrome_nodes = list(chrome_etree.iter(tag=etree.Element))
firefox_nodes = list(firefox_etree.iter(tag=etree.Element))
print('Chrome Nodes : %d' % len(chrome_nodes))
print('Firefox Nodes : %d' % len(firefox_nodes))
# Below condition is not implemented in xpert. Since algorithm is slow, this is just a check.
if len(chrome_nodes) + len(firefox_nodes) > 1700:
print('Large number of nodes to match -- skipping\n\n')
continue
do_match(chrome_etree, firefox_etree)
print('Matched Nodes (without alignment): %d' % len(matched21))
vertices_chrome = []
vertices_firefox = []
for chrome_node, firefox_node in matched12.items():
chrome_xpath = chrome_tree.getpath(chrome_node)
firefox_xpath = firefox_tree.getpath(firefox_node)
matched12_xpaths[chrome_xpath] = firefox_xpath
if isLayoutNode(chrome_node, chrome_xpath, chrome_loc):
vertices_chrome.append(chrome_xpath)
if isLayoutNode(firefox_node, firefox_xpath, firefox_loc):
vertices_firefox.append(firefox_xpath)
vertices_chrome = sorted(vertices_chrome, key=lambda x: (chrome_loc[x]['height'] * chrome_loc[x]['width'], len(x)))
vertices_firefox = sorted(vertices_firefox, key=lambda x: (firefox_loc[x]['height'] * firefox_loc[x]['width'], len(x)))
chrome_contains_edge_info = {}
firefox_contains_edge_info = {}
chrome_cMap = populate_parent_edges(vertices_chrome[:], chrome_loc, chrome_contains_edge_info)
firefox_cMap = populate_parent_edges(vertices_firefox[:], firefox_loc, firefox_contains_edge_info)
chrome_siblings_edge_info = {}
firefox_siblings_edge_info = {}
populate_sibling_edges(chrome_cMap, chrome_loc, chrome_siblings_edge_info)
populate_sibling_edges(firefox_cMap, firefox_loc, firefox_siblings_edge_info)
issues = []
total_matched_nodes = len(matched21)
for chrome_xpath, firefox_xpath in matched12_xpaths.items():
parent_issues = compare_parents(chrome_xpath, firefox_xpath, chrome_cMap, firefox_cMap, chrome_contains_edge_info, firefox_contains_edge_info)
sibling_issues = compare_siblings(chrome_xpath, firefox_xpath, chrome_cMap, firefox_cMap, chrome_siblings_edge_info, firefox_siblings_edge_info)
if len(parent_issues) or len(sibling_issues):
total_matched_nodes -= 1
issues.extend(parent_issues)
issues.extend(sibling_issues)
print('Matched Nodes (with alignment): %d\n\n' % total_matched_nodes)
image_name = '_'.join(dom_file.split('_')[1:])
if total_matched_nodes == min(len(chrome_nodes), len(firefox_nodes)):
label = 'y'
else:
label = 'n'
results.append([image_name, label, total_matched_nodes, len(chrome_nodes), len(firefox_nodes)])
with open('dom_test_labels.csv', 'w', newline='') as f:
writer = csv.writer(f, delimiter=',')
writer.writerow(['Image Name', 'Label', 'Matched Nodes', 'Chrome Nodes', 'Firefox Nodes'])
for row in results:
writer.writerow(row)