From d905558749cceff50e9872efb490450c54b6bd81 Mon Sep 17 00:00:00 2001
From: Martin Odersky <odersky@gmail.com>
Date: Fri, 13 Jul 2012 18:24:37 +0200
Subject: Variation #10 to optimze findMember

Undoing the memberType caching. This seems to make it slower rather than faster. Also, comparing new vs old statistics shows that only very few asSeenFrom operations are saved by the caching.
---
 src/compiler/scala/tools/nsc/MainBench.scala | 48 ++++++++++++++++++++++++++++
 1 file changed, 48 insertions(+)
 create mode 100644 src/compiler/scala/tools/nsc/MainBench.scala

(limited to 'src/compiler/scala/tools/nsc/MainBench.scala')

diff --git a/src/compiler/scala/tools/nsc/MainBench.scala b/src/compiler/scala/tools/nsc/MainBench.scala
new file mode 100644
index 0000000000..0037de7b94
--- /dev/null
+++ b/src/compiler/scala/tools/nsc/MainBench.scala
@@ -0,0 +1,48 @@
+/* NSC -- new Scala compiler
+ * Copyright 2005-2011 LAMP/EPFL
+ * @author  Martin Odersky
+ */
+
+package scala.tools.nsc
+
+import java.io.File
+import File.pathSeparator
+
+import scala.tools.nsc.interactive.{ RefinedBuildManager, SimpleBuildManager }
+import scala.tools.nsc.io.AbstractFile
+import scala.tools.nsc.reporters.{Reporter, ConsoleReporter}
+import scala.reflect.internal.util.{ BatchSourceFile, FakePos } //{Position}
+import Properties.{ versionString, copyrightString, residentPromptString, msilLibPath }
+import scala.reflect.internal.util.Statistics
+
+/** The main class for NSC, a compiler for the programming
+ *  language Scala.
+ */
+object MainBench extends Driver with EvalLoop {
+  
+  lazy val theCompiler = Global(settings, reporter)
+  
+  override def newCompiler() = theCompiler
+  
+  val NIter = 50
+  val NBest = 10
+  
+  override def main(args: Array[String]) = {
+    val times = new Array[Long](NIter)
+    var start = System.nanoTime()
+    for (i <- 0 until NIter) {
+      if (i == NIter-1) {
+        theCompiler.settings.Ystatistics.value = true
+        Statistics.enabled = true
+      }
+      process(args)
+      val end = System.nanoTime()
+      val duration = (end-start)/1000000
+      println(s"${duration}ms")
+      times(i) = duration
+      start = end
+    }
+    val avg = times.sorted.take(NBest).sum / NBest
+    println(s"avg shortest $NBest times ${avg}ms")
+  }
+}
-- 
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