@@ -29,6 +29,8 @@ and create an environment.
 and create a project.
 Check the field "Track changes" and, in case you want version control integration, configure the relevant fields.
 
+**Note**: Only executables associated to projects with a checked "track changes" field will be shown in the Overview and Timeline views.
+
 # Saving data
 Data is saved POSTing to `http://localhost:8000/result/add/`.
 
 
@@ -0,0 +1,56 @@
+import timeit, urllib, sys
+
+SPEEDURL = 'http://localhost:8000/'
+
+benchmarks = ['ai', 'django',  'spambayes', 'grid']
+
+def test_overview():
+    data = {
+        "trend": 10,
+        "baseline": 1,
+        "revision": 73893,
+        "executable": "1",
+        "host": "bigdog",
+    }
+    params = urllib.urlencode(data)
+    page= urllib.urlopen(SPEEDURL + 'overview/table/?' + params)
+    jsonstring = page.read()
+    page.close()
+    if not '<table id="results" class="tablesorter">' in jsonstring:
+        print "bad overview response"
+        sys.exit(1)
+
+def test_timeline(bench):
+    data = {
+        "executables": "1,2,6",
+        "baseline": "true",
+        "benchmark": bench,
+        "host": "bigdog",
+        "revisions": 200
+    }
+    params = urllib.urlencode(data)
+    page= urllib.urlopen(SPEEDURL + 'timeline/json/?' + params)
+    jsonstring = page.read()
+    #print jsonstring
+    page.close()
+    if not '"lessisbetter": " (less is better)", "baseline":' in jsonstring \
+        or not', "error": "None"}' in jsonstring:
+        print "bad timeline response"
+        sys.exit(1)
+
+if __name__ == "__main__":
+    t = timeit.Timer('test_overview()', 'from __main__ import test_overview')
+    results = t.repeat(20, 1)
+    print
+    print "OVERVIEW RESULTS"
+    print "min:", min(results)
+    print "avg:", sum(results)/len(results)
+    print
+    print "TIMELINE RESULTS"
+    for bench in benchmarks:
+        t = timeit.Timer('test_timeline("'+bench+'")', 'from __main__ import test_timeline')
+        results = t.repeat(20, 1)
+        print "benchmark =", bench
+        print "min:", min(results)
+        print "avg:", sum(results)/len(results)
+    print