Algorithms and Data Structures

N.Wirth. Algorithms and Data Structures. Oberon version 147
(*input phase*)
Texts.Scan(S);
WHILE S.class = Texts.Int DO
x := S.i; Texts.Scan(S); y := S.i; p := find(x); q := find(y);
NEW(t); t.id := q; t.next := p.trail;
p.trail := t; INC(q.count); Texts.Scan(S)
END;
(*search for leaders without predecessors*)
p := head; head := NIL;
WHILE p # tail DO
q := p; p := q.next;
IF q.count = 0 THEN (*insert q in new chain*)
q.next := head; head := q
END
END;
(*output phase*) q := head;
WHILE q # NIL DO
Texts.WriteLn(W); Texts.WriteInt(W, q.key, 8); DEC(n);
t := q.trail; q := q.next;
WHILE t # NIL DO
p := t.id; DEC(p.count);
IF p.count = 0 THEN (*insert p in leader list*)
p.next := q; q := p
END;
t := t.next
END
END;
IF n # 0 THEN
Texts.WriteString(W, "This set is not partially ordered")
END;
Texts.WriteLn(W)
END TopSort.
4.4 Tree Structures
4.4.1 Basic Concepts and Definitions
We have seen that sequences and lists may conveniently be defined in the following way: A sequence
(list) with base type T is either
1. The empty sequence (list).
2. The concatenation (chain) of a T and a sequence with base type T.
Hereby recursion is used as an aid in defining a structuring principle, namely, sequencing or iteration.
Sequences and iterations are so common that they are usually considered as fundamental patterns of
structure and behaviour. But it should be kept in mind that they can be defined in terms of recursion,
whereas the reverse is not true, for recursion may be effectively and elegantly used to define much more
sophisticated structures. Trees are a well-known example. Let a tree structure be defined as follows: A
tree structure with base type T is either
1. The empty structure.