diff --git a/16-asides/README.md b/16-asides/README.md
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+Style #16
+==============================
+
+Constraints:
+
+- The problem is decomposed using some form of abstraction (procedures, functions, objects, etc.)
+
+- Aspects of the problem are added to the main program without any
+  edits to the abstractions. These side functions latch on the main
+  functions by naming "join points"
+
+
+Possible names:
+
+- Asides
+- Aspect-oriented style
+- Rewriting the story
diff --git a/16-asides/tf-16.py b/16-asides/tf-16.py
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+import sys, re, operator, string, time
+
+#
+# The functions
+#
+def extract_words(path_to_file):
+    """
+    Takes a path to a file and returns the non-stop
+    words, after properly removing nonalphanumeric chars
+    and normalizing for lower case
+    """
+    with open(path_to_file) as f:
+        str_data = f.read()
+    pattern = re.compile('[\W_]+')
+    word_list = pattern.sub(' ', str_data).lower().split()
+    with open('../stop_words.txt') as f:
+        stop_words = f.read().split(',')
+    stop_words.extend(list(string.ascii_lowercase))
+    return [w for w in word_list if not w in stop_words]
+
+def frequencies(word_list):
+    """
+    Takes a list of words and returns a dictionary associating
+    words with frequencies of occurrence
+    """
+    word_freqs = {}
+    for w in word_list:
+        if w in word_freqs:
+            word_freqs[w] += 1
+        else:
+            word_freqs[w] = 1
+    return word_freqs
+
+def sort(word_freq):
+    """
+    Takes a dictionary of words and their frequencies
+    and returns a list of pairs where the entries are
+    sorted by frequency 
+    """
+    return sorted(word_freq.iteritems(), key=operator.itemgetter(1), reverse=True)
+
+# The side functionality
+def profile(f):
+    def profilewrapper(*arg, **kw):
+        start_time = time.time()
+        ret_value = f(*arg, **kw)
+        elapsed = time.time() - start_time
+        print "%s(...) took %s secs" % (f.__name__, elapsed)
+        return ret_value
+    return profilewrapper
+
+# join points
+tracked_functions = [extract_words, frequencies, sort]
+# weaver
+for func in tracked_functions:
+    globals()[func.func_name]=profile(func)
+
+#
+# The main function
+#
+word_freqs = sort(frequencies(extract_words(sys.argv[1])))
+
+for tf in word_freqs[0:25]:
+    print tf[0], ' - ', tf[1]
+