diff -r c7bdd7eac4cb -r 022e2cb1668d progs/thompson.scala
--- a/progs/thompson.scala	Sat Jul 04 16:58:12 2020 +0100
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,177 +0,0 @@
-// Thompson Construction
-// (needs  :load dfa.scala
-//         :load nfa.scala
-//         :load enfa.scala)
-
-
-// states for Thompson construction
-case class TState(i: Int) extends State
-
-object TState {
-  var counter = 0
-  
-  def apply() : TState = {
-    counter += 1;
-    new TState(counter - 1)
-  }
-}
-
-
-// some types abbreviations
-type NFAt = NFA[TState, Char]
-type NFAtrans = (TState, Char) :=> Set[TState]
-type eNFAtrans = (TState, Option[Char]) :=> Set[TState]
-
-
-// for composing an eNFA transition with a NFA transition
-implicit class RichPF(val f: eNFAtrans) extends AnyVal {
-  def +++(g: NFAtrans) : eNFAtrans = 
-  { case (q, None) =>  applyOrElse(f, (q, None)) 
-    case (q, Some(c)) => applyOrElse(f, (q, Some(c))) | applyOrElse(g, (q, c))  }
-}
-
-
-// NFA that does not accept any string
-def NFA_ZERO(): NFAt = {
-  val Q = TState()
-  NFA(Set(Q), { case _ => Set() }, Set())
-}
-
-// NFA that accepts the empty string
-def NFA_ONE() : NFAt = {
-  val Q = TState()
-  NFA(Set(Q), { case _ => Set() }, Set(Q))
-}
-
-// NFA that accepts the string "c"
-def NFA_CHAR(c: Char) : NFAt = {
-  val Q1 = TState()
-  val Q2 = TState()
-  NFA(Set(Q1), { case (Q1, d) if (c == d) => Set(Q2) }, Set(Q2))
-}
-
-// sequence of two NFAs
-def NFA_SEQ(enfa1: NFAt, enfa2: NFAt) : NFAt = {
-  val new_delta : eNFAtrans = 
-    { case (q, None) if enfa1.fins(q) => enfa2.starts }
-  
-  eNFA(enfa1.starts, new_delta +++ enfa1.delta +++ enfa2.delta, 
-       enfa2.fins)
-}
-
-// alternative of two NFAs
-def NFA_ALT(enfa1: NFAt, enfa2: NFAt) : NFAt = {
-  val new_delta : NFAtrans = { 
-    case (q, c) =>  applyOrElse(enfa1.delta, (q, c)) | 
-                    applyOrElse(enfa2.delta, (q, c)) }
-  val new_fins = (q: TState) => enfa1.fins(q) || enfa2.fins(q)
-
-  NFA(enfa1.starts | enfa2.starts, new_delta, new_fins)
-}
-
-// star of a NFA
-def NFA_STAR(enfa: NFAt) : NFAt = {
-  val Q = TState()
-  val new_delta : eNFAtrans = 
-    { case (Q, None) => enfa.starts
-      case (q, None) if enfa.fins(q) => Set(Q) }
-
-  eNFA(Set(Q), new_delta +++ enfa.delta, Set(Q))
-}
-
-
-
-// regular expressions
-abstract class Rexp
-case object ZERO extends Rexp                    // matches nothing
-case object ONE extends Rexp                     // matches the empty string
-case class CHAR(c: Char) extends Rexp            // matches a character c
-case class ALT(r1: Rexp, r2: Rexp) extends Rexp  // alternative
-case class SEQ(r1: Rexp, r2: Rexp) extends Rexp  // sequence
-case class STAR(r: Rexp) extends Rexp            // star
-
-
-
-
-// thompson construction 
-def thompson (r: Rexp) : NFAt = r match {
-  case ZERO => NFA_ZERO()
-  case ONE => NFA_ONE()
-  case CHAR(c) => NFA_CHAR(c)  
-  case ALT(r1, r2) => NFA_ALT(thompson(r1), thompson(r2))
-  case SEQ(r1, r2) => NFA_SEQ(thompson(r1), thompson(r2))
-  case STAR(r1) => NFA_STAR(thompson(r1))
-}
-
-//optional regular expression (one or zero times)
-def OPT(r: Rexp) = ALT(r, ONE)
-
-//n-times regular expression (explicitly expanded)
-def NTIMES(r: Rexp, n: Int) : Rexp = n match {
-  case 0 => ONE
-  case 1 => r
-  case n => SEQ(r, NTIMES(r, n - 1))
-}
-
-
-def tmatches(r: Rexp, s: String) : Boolean =
-  thompson(r).accepts(s.toList)
-
-def tmatches2(r: Rexp, s: String) : Boolean =
-  thompson(r).accepts2(s.toList)
-
-// dfa via subset construction
-def tmatches_dfa(r: Rexp, s: String) : Boolean =
-  subset(thompson(r)).accepts(s.toList)
-
-// Test Cases
-
-
-// the evil regular expression  a?{n} a{n}
-def EVIL1(n: Int) : Rexp = SEQ(NTIMES(OPT(CHAR('a')), n), NTIMES(CHAR('a'), n))
-
-// the evil regular expression (a*)*b
-val EVIL2 : Rexp = SEQ(STAR(STAR(CHAR('a'))), CHAR('b'))
-
-//for measuring time
-def time_needed[T](i: Int, code: => T) = {
-  val start = System.nanoTime()
-  for (j <- 1 to i) code
-  val end = System.nanoTime()
-  (end - start)/(i * 1.0e9)
-}
-
-// the size of the NFA can be large, 
-// thus slowing down the breadth-first search
-
-for (i <- 1 to 13) {
-  println(i + ": " + "%.5f".format(time_needed(2, tmatches(EVIL1(i), "a" * i))))
-}
-
-for (i <- 1 to 100 by 5) {
-  println(i + " " + "%.5f".format(time_needed(2, tmatches(EVIL2, "a" * i))))
-}
-
-
-// the backtracking needed in depth-first search 
-// can be painfully slow
-
-for (i <- 1 to 8) {
-  println(i + " " + "%.5f".format(time_needed(2, tmatches2(EVIL2, "a" * i))))
-}
-
-
-
-// while my thompson->enfa->subset->partial-function-chain
-// is probably not the most effcient way to obtain a fast DFA 
-// (the test below should be much faster with a more direct 
-// construction), in general the DFAs can be slow because of 
-// the state explosion in the subset construction
-
-for (i <- 1 to 13) {
-  println(i + ": " + "%.5f".format(time_needed(2, tmatches_dfa(EVIL1(i), "a" * i))))
-}
-
-for (i <- 1 to 100 by 5) {
-  println(i + " " + "%.5f".format(time_needed(2, tmatches_dfa(EVIL2, "a" * i))))
-}