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<title>Solutions to the L-99: Nintey-Nine Lisp Problems</title>
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<h1 align="center">Solutions to Nintey-Nine Lisp Problems</h1>

<p>Here are solutions to the
<a href="http://www.ic.unicamp.br/~meidanis/courses/mc336/2006s2/funcional/L-99_Ninety-Nine_Lisp_Problems.html">
L-99: Nintey-Nine Lisp Problems</a>, (which themselves are derived from
<a href="http://www.scribd.com/doc/18339544/99-prolog-problems">a list of prolog problems</a>).</p>

<h2>Working with lists</h2>
<ul>
<li><a href="p01.lisp">p01.lisp</a> P01 (*) Find the last box of a list.</li>
<li><a href="p02.lisp">p02.lisp</a> P02 (*) Find the last but one box of a list.</li>
<li><a href="p03.lisp">p03.lisp</a> P03 (*) Find the K'th element of a list.</li>
<li><a href="p04.lisp">p04.lisp</a> P04 (*) Find the number of elements of a list.</li>
<li><a href="p05.lisp">p05.lisp</a> P05 (*) Reverse a list.</li>
<li><a href="p06.lisp">p06.lisp</a> P06 (*) Find out whether a list is a palindrome.</li>
<li><a href="p07.lisp">p07.lisp</a> P07 (**) Flatten a nested list structure.</li>
<li><a href="p08.lisp">p08.lisp</a> P08 (**) Eliminate consecutive duplicates of list elements.</li>
<li><a href="p09.lisp">p09.lisp</a> P09 (**) Pack consecutive duplicates of list elements into sublists.</li>
<li><a href="p10.lisp">p10.lisp</a> P10 (*) Run-length encoding of a list.</li>
<li><a href="p11.lisp">p11.lisp</a> P11 (*) Modified run-length encoding.</li>
<li><a href="p12.lisp">p12.lisp</a> P12 (**) Decode a run-length encoded list.</li>
<li><a href="p13.lisp">p13.lisp</a> P13 (**) Run-length encoding of a list (direct solution).</li>
<li><a href="p14.lisp">p14.lisp</a> P14 (*) Duplicate the elements of a list.</li>
<li><a href="p15.lisp">p15.lisp</a> P15 (**) Replicate the elements of a list a given number of times.</li>
<li><a href="p16.lisp">p16.lisp</a> P16 (**) Drop every N'th element from a list.</li>
<li><a href="p17.lisp">p17.lisp</a> P17 (*) Split a list into two parts; the length of the first part is given.</li>
<li><a href="p18.lisp">p18.lisp</a> P18 (**) Extract a slice from a list.</li>
<li><a href="p19.lisp">p19.lisp</a> P19 (**) Rotate a list N places to the left.</li>
<li><a href="p20.lisp">p20.lisp</a> P20 (*) Remove the K'th element from a list.</li>
<li><a href="p21.lisp">p21.lisp</a> P21 (*) Insert an element at a given position into a list.</li>
<li><a href="p22.lisp">p22.lisp</a> P22 (*) Create a list containing all integers within a given range.</li>
<li><a href="p23.lisp">p23.lisp</a> P23 (**) Extract a given number of randomly selected elements from a list.</li>
<li><a href="p24.lisp">p24.lisp</a> P24 (*) Lotto: Draw N different random numbers from the set 1..M.</li>
<li><a href="p25.lisp">p25.lisp</a> P25 (*) Generate a random permutation of the elements of a list.</li>
<li><a href="p26.lisp">p26.lisp</a> P26 (**) Generate the combinations of K distinct objects chosen from the N elements of a list</li>
<li><a href="p27.lisp">p27.lisp</a> P27 (**) Group the elements of a set into disjoint subsets.</li>
<li><a href="p28.lisp">p28.lisp</a> P28 (**) Sorting a list of lists according to length of sublists</li>
</ul>
<h2>Arithmetic</h2>
<ul>
<li><a href="p31.lisp">p31.lisp</a> P31 (**) Determine whether a given integer number is prime.</li>
<li><a href="p32.lisp">p32.lisp</a> P32 (**) Determine the greatest common divisor of two positive integer numbers.</li>
<li><a href="p33.lisp">p33.lisp</a> P33 (*) Determine whether two positive integer numbers are coprime.</li>
<li><a href="p34.lisp">p34.lisp</a> P34 (**) Calculate Euler's totient function phi(m).</li>
<li><a href="p35.lisp">p35.lisp</a> P35 (**) Determine the prime factors of a given positive integer.</li>
<li><a href="p36.lisp">p36.lisp</a> P36 (**) Determine the prime factors of a given positive integer (2).</li>
<li><a href="p37.lisp">p37.lisp</a> P37 (**) Calculate Euler's totient function phi(m) (improved).</li>
<li><a href="p38.lisp">p38.lisp</a> P38 (*) Compare the two methods of calculating Euler's totient function.</li>
<li><a href="p39.lisp">p39.lisp</a> P39 (*) A list of prime numbers.</li>
<li><a href="p40.lisp">p40.lisp</a> P40 (**) Goldbach's conjecture.</li>
<li><a href="p41.lisp">p41.lisp</a> P41 (**) A list of Goldbach compositions.</li>
</ul>
<h2>Logic and Codes</h2>
<ul>
<li><a href="p46.lisp">p46.lisp</a> P46 (**) Truth tables for logical expressions.</li>
<li><a href="p47.lisp">p47.lisp</a> P47 (*) Truth tables for logical expressions (2).</li>
<li><a href="p48.lisp">p48.lisp</a> P48 (**) Truth tables for logical expressions (3).</li>
<li><a href="p49.lisp">p49.lisp</a> P49 (**) Gray code.</li>
<li><a href="p50.lisp">p50.lisp</a> P50 (***) Huffman code.</li>
</ul>
<h2>Binary Trees</h2>
<ul>
<li><a href="p54a.lisp">p54a.lisp</a> P54A (*) Check whether a given term represents a binary tree</li>
<li><a href="p55.lisp">p55.lisp</a> P55 (**) Construct completely balanced binary trees</li>
<li><a href="p56.lisp">p56.lisp</a> P56 (**) Symmetric binary trees</li>
<li><a href="p57.lisp">p57.lisp</a> P57 (**) Binary search trees (dictionaries)</li>
<li><a href="p58.lisp">p58.lisp</a> P58 (**) Generate-and-test paradigm</li>
<li><a href="p59.lisp">p59.lisp</a> P59 (**) Construct height-balanced binary trees</li>
<li><a href="p60.lisp">p60.lisp</a> P60 (**) Construct height-balanced binary trees with a given number of nodes</li>
<li><a href="p61.lisp">p61.lisp</a> P61 (*) Count the leaves of a binary tree</li>
<li><a href="p61a.lisp">p61a.lisp</a> P61A (*) Collect the leaves of a binary tree in a list</li>
<li><a href="p62.lisp">p62.lisp</a> P62 (*) Collect the internal nodes of a binary tree in a list</li>
<li><a href="p62b.lisp">p62b.lisp</a> P62B (*) Collect the nodes at a given level in a list</li>
<li><a href="p63.lisp">p63.lisp</a> P63 (**) Construct a complete binary tree</li>
<li><a href="p64.lisp">p64.lisp</a> P64 (**) Layout a binary tree (1)</li>
<li><a href="p65.lisp">p65.lisp</a> P65 (**) Layout a binary tree (2)</li>
<li><a href="p66.lisp">p66.lisp</a> P66 (***) Layout a binary tree (3)</li>
<li><a href="p67.lisp">p67.lisp</a> P67 (**) A string representation of binary trees</li>
<li><a href="p68.lisp">p68.lisp</a> P68 (**) Preorder and inorder sequences of binary trees</li>
<li><a href="p69.lisp">p69.lisp</a> P69 (**) Dotstring representation of binary trees</li>
</ul>
<h2>Multiway Trees</h2>
<ul>
<li><a href="p70b.lisp">p70b.lisp</a> P70B (*) Check whether a given term represents a multiway tree</li>
<li><a href="p70c.lisp">p70c.lisp</a> P70C (*) Count the nodes of a multiway tree</li>
<li><a href="p70.lisp">p70.lisp</a> P70 (**) Tree construction from a node string</li>
<li><a href="p71.lisp">p71.lisp</a> P71 (*) Determine the internal path length of a tree</li>
<li><a href="p72.lisp">p72.lisp</a> P72 (*) Construct the bottom-up order sequence of the tree nodes</li>
<li><a href="p73.lisp">p73.lisp</a> P73 (**) Lisp-like tree representation</li>
</ul>
<h2>Graphs</h2>
<ul>
<li><a href="p80.lisp">p80.lisp</a> P80 (***) Conversions</li>
<li><a href="p81.lisp">p81.lisp</a> P81 (**) Path from one node to another one</li>
<li><a href="p82.lisp">p82.lisp</a> P82 (*) Cycle from a given node</li>
<li><a href="p83.lisp">p83.lisp</a> P83 (**) Construct all spanning trees</li>
<li><a href="p84.lisp">p84.lisp</a> P84 (**) Construct the minimal spanning tree</li>
<li><a href="p85.lisp">p85.lisp</a> P85 (**) Graph isomorphism</li>
<li><a href="p86.lisp">p86.lisp</a> P86 (**) Node degree and graph coloration</li>
<li><a href="p87.lisp">p87.lisp</a> P87 (**) Depth-first order graph traversal (alternative solution)</li>
<li><a href="p88.lisp">p88.lisp</a> P88 (**) Connected components (alternative solution)</li>
<li><a href="p89.lisp">p89.lisp</a> P89 (**) Bipartite graphs</li>
</ul>
<h2>Miscellaneous Problems</h2>
<ul>
<li><a href="p90.lisp">p90.lisp</a> P90 (**) Eight queens problem</li>
<li><a href="p91.lisp">p91.lisp</a> P91 (**) Knight's tour</li>
<li><a href="p92.lisp">p92.lisp</a> P92 (***) Von Koch's conjecture</li>
<li><a href="p93.lisp">p93.lisp</a> P93 (***) An arithmetic puzzle</li>
<li><a href="p94.lisp">p94.lisp</a> P94 (***) Generate K-regular simple graphs with N nodes</li>
<li><a href="p95.lisp">p95.lisp</a> P95 (**) English number words</li>
<li><a href="p96.lisp">p96.lisp</a> P96 (**) Syntax checker (alternative solution with difference lists)</li>
<li><a href="p97.lisp">p97.lisp</a> P97 (**) Sudoku</li>
<li><a href="p98.lisp">p98.lisp</a> P98 (***) Nonograms</li>
<li><a href="p99.lisp">p99.lisp</a> P99 (***) Crossword puzzle</li>
</ul>

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grep -n 'TO BE DONE' *.lisp
p38.lisp:11:;; TO BE DONE.

P59 (**) Construct height-balanced binary trees
In a height-balanced binary tree, the following property holds for every node: The height of its left subtree and the height of its right subtree are almost equal, which means their difference is not greater than one.

Write a predicate hbal-tree/2 to construct height-balanced binary trees for a given height. The predicate should generate all solutions via backtracking. Put the letter 'x' as information into all nodes of the tree.
Example:
* hbal-tree(3,T).
T = t(x, t(x, t(x, nil, nil), t(x, nil, nil)), t(x, t(x, nil, nil), t(x, nil, nil))) ;
T = t(x, t(x, t(x, nil, nil), t(x, nil, nil)), t(x, t(x, nil, nil), nil)) ;
etc......No

P60 (**) Construct height-balanced binary trees with a given number of nodes
Consider a height-balanced binary tree of height H. What is the maximum number of nodes it can contain?
Clearly, MaxN = 2**H - 1. However, what is the minimum number MinN? This question is more difficult. Try to find a recursive statement and turn it into a predicate minNodes/2 defined as follwos:

% minNodes(H,N) :- N is the minimum number of nodes in a height-balanced binary tree of height H.
(integer,integer), (+,?)

On the other hand, we might ask: what is the maximum height H a height-balanced binary tree with N nodes can have?

% maxHeight(N,H) :- H is the maximum height of a height-balanced binary tree with N nodes
(integer,integer), (+,?)

Now, we can attack the main problem: construct all the height-balanced binary trees with a given nuber of nodes.

% hbal-tree-nodes(N,T) :- T is a height-balanced binary tree with N nodes.

Find out how many height-balanced trees exist for N = 15.

P66 (***) Layout a binary tree (3)
[p66]
Yet another layout strategy is shown in the illustration opposite. The method yields a very compact layout while maintaining a certain symmetry in every node. Find out the rules and write the corresponding Prolog predicate. Hint:
Consider the horizontal distance between a node and its successor nodes. How tight can you pack together two subtrees to construct the combined binary tree?

Use the same conventions as in problem P64 and P65 and test your predicate in an appropriate way. Note: This is a difficult problem. Don't give up too early!

Which layout do you like most?

P67 (**) A string representation of binary trees
[p67]

Somebody represents binary trees as strings of the following type (see example opposite):

a(b(d,e),c(,f(g,)))

a) Write a Prolog predicate which generates this string representation, if the tree is given as usual (as nil or t(X,L,R) term). Then write a predicate which does this inverse; i.e. given the string representation, construct the
tree in the usual form. Finally, combine the two predicates in a single predicate tree-string/2 which can be used in both directions.

b) Write the same predicate tree-string/2 using difference lists and a single predicate tree-dlist/2 which does the conversion between a tree and a difference list in both directions.

For simplicity, suppose the information in the nodes is a single letter and there are no spaces in the string.

P68 (**) Preorder and inorder sequences of binary trees
We consider binary trees with nodes that are identified by single lower-case letters, as in the example of problem P67.

a) Write predicates preorder/2 and inorder/2 that construct the preorder and inorder sequence of a given binary tree, respectively. The results should be atoms, e.g. 'abdecfg' for the preorder sequence of the example in problem
P67.

b) Can you use preorder/2 from problem part a) in the reverse direction; i.e. given a preorder sequence, construct a corresponding tree? If not, make the necessary arrangements.

c) If both the preorder sequence and the inorder sequence of the nodes of a binary tree are given, then the tree is determined unambiguously. Write a predicate pre-in-tree/3 that does the job.

d) Solve problems a) to c) using difference lists. Cool! Use the predefined predicate time/1 to compare the solutions.

What happens if the same character appears in more than one node. Try for instance pre-in-tree(aba,baa,T).

P69 (**) Dotstring representation of binary trees
We consider again binary trees with nodes that are identified by single lower-case letters, as in the example of problem P67. Such a tree can be represented by the preorder sequence of its nodes in which dots (.) are inserted where
an empty subtree (nil) is encountered during the tree traversal. For example, the tree shown in problem P67 is represented as 'abd..e..c.fg...'. First, try to establish a syntax (BNF or syntax diagrams) and then write a predicate
tree-dotstring/2 which does the conversion in both directions. Use difference lists.

Multiway Trees

A multiway tree is composed of a root element and a (possibly empty) set of successors which are multiway trees themselves. A multiway tree is never empty. The set of successor trees is sometimes called a forest.

[p70]

In Prolog we represent a multiway tree by a term t(X,F), where X denotes the root node and F denotes the forest of successor trees (a Prolog list). The example tree depicted opposite is therefore represented by the following Prolog
term:

T = t(a,[t(f,[t(g,[])]),t(c,[]),t(b,[t(d,[]),t(e,[])])])

P70B (*) Check whether a given term represents a multiway tree
Write a predicate istree/1 which succeeds if and only if its argument is a Prolog term representing a multiway tree.
Example:
* istree(t(a,[t(f,[t(g,[])]),t(c,[]),t(b,[t(d,[]),t(e,[])])])).
Yes

P70C (*) Count the nodes of a multiway tree
Write a predicate nnodes/1 which counts the nodes of a given multiway tree.
Example:
* nnodes(t(a,[t(f,[])]),N).
N = 2

Write another version of the predicate that allows for a flow pattern (o,i).

P70 (**) Tree construction from a node string
[p70]
We suppose that the nodes of a multiway tree contain single characters. In the depth-first order sequence of its nodes, a special character ^ has been inserted whenever, during the tree traversal, the move is a backtrack to the
previous level.

By this rule, the tree in the figure opposite is represented as: afg^^c^bd^e^^^

Define the syntax of the string and write a predicate tree(String,Tree) to construct the Tree when the String is given. Work with atoms (instead of strings). Make your predicate work in both directions.

P71 (*) Determine the internal path length of a tree
We define the internal path length of a multiway tree as the total sum of the path lengths from the root to all nodes of the tree. By this definition, the tree in the figure of problem P70 has an internal path length of 9. Write a
predicate ipl(Tree,IPL) for the flow pattern (+,-).

P72 (*) Construct the bottom-up order sequence of the tree nodes
Write a predicate bottom-up(Tree,Seq) which constructs the bottom-up sequence of the nodes of the multiway tree Tree. Seq should be a Prolog list. What happens if you run your predicate backwords?

P73 (**) Lisp-like tree representation
There is a particular notation for multiway trees in Lisp. Lisp is a prominent functional programming language, which is used primarily for artificial intelligence problems. As such it is one of the main competitors of Prolog. In
Lisp almost everything is a list, just as in Prolog everything is a term.

The following pictures show how multiway tree structures are represented in Lisp.
[p73]
Note that in the "lispy" notation a node with successors (children) in the tree is always the first element in a list, followed by its children. The "lispy" representation of a multiway tree is a sequence of atoms and parentheses '
(' and ')', which we shall collectively call "tokens". We can represent this sequence of tokens as a Prolog list; e.g. the lispy expression (a (b c)) could be represented as the Prolog list ['(', a, '(', b, c, ')', ')']. Write a
predicate tree-ltl(T,LTL) which constructs the "lispy token list" LTL if the tree is given as term T in the usual Prolog notation.

Example:
* tree-ltl(t(a,[t(b,[]),t(c,[])]),LTL).
LTL = ['(', a, '(', b, c, ')', ')']

As a second, even more interesting exercise try to rewrite tree-ltl/2 in a way that the inverse conversion is also possible: Given the list LTL, construct the Prolog tree T. Use difference lists.

Graphs

A graph is defined as a set of nodes and a set of edges, where each edge is a pair of nodes.

There are several ways to represent graphs in Prolog. One method is to represent each edge separately as one clause (fact). In this form, the graph depicted below is represented as the following predicate:
[graph1]

edge(h,g).
edge(k,f).
edge(f,b).
...

We call this edge-clause form. Obviously, isolated nodes cannot be represented. Another method is to represent the whole graph as one data object. According to the definition of the graph as a pair of two sets (nodes and edges), we may
use the following Prolog term to represent the example graph:

graph([b,c,d,f,g,h,k],[e(b,c),e(b,f),e(c,f),e(f,k),e(g,h)])

We call this graph-term form. Note, that the lists are kept sorted, they are really sets, without duplicated elements. Each edge appears only once in the edge list; i.e. an edge from a node x to another node y is represented as e(x,y),
the term e(y,x) is not present. The graph-term form is our default representation. In SWI-Prolog there are predefined predicates to work with sets.

A third representation method is to associate with each node the set of nodes that are adjacent to that node. We call this the adjacency-list form. In our example:

[n(b,[c,f]), n(c,[b,f]), n(d,[]), n(f,[b,c,k]), ...]

The representations we introduced so far are Prolog terms and therefore well suited for automated processing, but their syntax is not very user-friendly. Typing the terms by hand is cumbersome and error-prone. We can define a more
compact and "human-friendly" notation as follows: A graph is represented by a list of atoms and terms of the type X-Y (i.e. functor '-' and arity 2). The atoms stand for isolated nodes, the X-Y terms describe edges. If an X appears as
an endpoint of an edge, it is automatically defined as a node. Our example could be written as:

[b-c, f-c, g-h, d, f-b, k-f, h-g]

We call this the human-friendly form. As the example shows, the list does not have to be sorted and may even contain the same edge multiple times. Notice the isolated node d. (Actually, isolated nodes do not even have to be atoms in
the Prolog sense, they can be compound terms, as in d(3.75,blue) instead of d in the example).

[graph2]
When the edges are directed we call them arcs. These are represented by ordered pairs. Such a graph is called directed graph. To represent a directed graph, the forms discussed above are slightly modified. The example graph opposite is
represented as follows:

Arc-clause form
arc(s,u).
arc(u,r).
...

Graph-term form
digraph([r,s,t,u,v],[a(s,r),a(s,u),a(u,r),a(u,s),a(v,u)])

[n(r,[]),n(s,[r,u]),n(t,[]),n(u,[r]),n(v,[u])]
Note that the adjacency-list does not have the information on whether it is a graph or a digraph.

Human-friendly form
[s > r, t, u > r, s > u, u > s, v > u]

Finally, graphs and digraphs may have additional information attached to nodes and edges (arcs). For the nodes, this is no problem, as we can easily replace the single character identifiers with arbitrary compound terms, such as city
('London',4711). On the other hand, for edges we have to extend our notation. Graphs with additional information attached to edges are called labelled graphs.

[graph3]

Arc-clause form
arc(m,q,7).
arc(p,q,9).
arc(p,m,5).

Graph-term form
digraph([k,m,p,q],[a(m,p,7),a(p,m,5),a(p,q,9)])

[n(k,[]),n(m,[q/7]),n(p,[m/5,q/9]),n(q,[])]
Notice how the edge information has been packed into a term with functor '/' and arity 2, together with the corresponding node.

Human-friendly form
[p>q/9, m>q/7, k, p>m/5]

The notation for labelled graphs can also be used for so-called multi-graphs, where more than one edge (or arc) are allowed between two given nodes.

P80 (***) Conversions
Write predicates to convert between the different graph representations. With these predicates, all representations are equivalent; i.e. for the following problems you can always pick freely the most convenient form. The reason
this problem is rated (***) is not because it's particularly difficult, but because it's a lot of work to deal with all the special cases.

P81 (**) Path from one node to another one
Write a predicate path(G,A,B,P) to find an acyclic path P from node A to node b in the graph G. The predicate should return all paths via backtracking.

P82 (*) Cycle from a given node
Write a predicate cycle(G,A,P) to find a closed path (cycle) P starting at a given node A in the graph G. The predicate should return all cycles via backtracking.

[p83]

P83 (**) Construct all spanning trees
Write a predicate s-tree(Graph,Tree) to construct (by backtracking) all spanning trees of a given graph. With this predicate, find out how many spanning trees there are for the graph depicted to the left. The data of this example
graph can be found in the file p83.dat. When you have a correct solution for the s-tree/2 predicate, use it to define two other useful predicates: is-tree(Graph) and is-connected(Graph). Both are five-minutes tasks!

[p84]

P84 (**) Construct the minimal spanning tree
Write a predicate ms-tree(Graph,Tree,Sum) to construct the minimal spanning tree of a given labelled graph. Hint: Use the algorithm of Prim. A small modification of the solution of P83 does the trick. The data of the example graph
to the right can be found in the file p84.dat.

P85 (**) Graph isomorphism
Two graphs G1(N1,E1) and G2(N2,E2) are isomorphic if there is a bijection f: N1 -> N2 such that for any nodes X,Y of N1, X and Y are adjacent if and only if f(X) and f(Y) are adjacent.

Write a predicate that determines whether two graphs are isomorphic. Hint: Use an open-ended list to represent the function f.

P86 (**) Node degree and graph coloration
a) Write a predicate degree(Graph,Node,Deg) that determines the degree of a given node.

b) Write a predicate that generates a list of all nodes of a graph sorted according to decreasing degree.

c) Use Welch-Powell's algorithm to paint the nodes of a graph in such a way that adjacent nodes have different colors.

P87 (**) Depth-first order graph traversal (alternative solution)
Write a predicate that generates a depth-first order graph traversal sequence. The starting point should be specified, and the output should be a list of nodes that are reachable from this starting point (in depth-first order).

P88 (**) Connected components (alternative solution)
Write a predicate that splits a graph into its connected components.

P89 (**) Bipartite graphs
Write a predicate that finds out whether a given graph is bipartite.

Miscellaneous Problems

P90 (**) Eight queens problem
This is a classical problem in computer science. The objective is to place eight queens on a chessboard so that no two queens are attacking each other; i.e., no two queens are in the same row, the same column, or on the same
diagonal.

Hint: Represent the positions of the queens as a list of numbers 1..N. Example: [4,2,7,3,6,8,5,1] means that the queen in the first column is in row 4, the queen in the second column is in row 2, etc. Use the generate-and-test

P91 (**) Knight's tour
Another famous problem is this one: How can a knight jump on an NxN chessboard in such a way that it visits every square exactly once?

Hints: Represent the squares by pairs of their coordinates of the form X/Y, where both X and Y are integers between 1 and N. (Note that '/' is just a convenient functor, not division!) Define the relation jump(N,X/Y,U/V) to express
the fact that a knight can jump from X/Y to U/V on a NxN chessboard. And finally, represent the solution of our problem as a list of N*N knight positions (the knight's tour).

P92 (***) Von Koch's conjecture
Several years ago I met a mathematician who was intrigued by a problem for which he didn't know a solution. His name was Von Koch, and I don't know whether the problem has been solved since.

[p92a]   [p92b]

Anyway the puzzle goes like this: Given a tree with N nodes (and hence N-1 edges). Find a way to enumerate the nodes from 1 to N and, accordingly, the edges from 1 to N-1 in such a way, that for each edge K the difference of its
node numbers equals to K. The conjecture is that this is always possible.

For small trees the problem is easy to solve by hand. However, for larger trees, and 14 is already very large, it is extremely difficult to find a solution. And remember, we don't know for sure whether there is always a solution!

Write a predicate that calculates a numbering scheme for a given tree. What is the solution for the larger tree pictured above?

P93 (***) An arithmetic puzzle
Given a list of integer numbers, find a correct way of inserting arithmetic signs (operators) such that the result is a correct equation. Example: With the list of numbers [2,3,5,7,11] we can form the equations 2-3+5+7 = 11 or 2 =
(3*5+7)/11 (and ten others!).

P94 (***) Generate K-regular simple graphs with N nodes
In a K-regular graph all nodes have a degree of K; i.e. the number of edges incident in each node is K. How many (non-isomorphic!) 3-regular graphs with 6 nodes are there? See also a table of results and a Java applet that can
represent graphs geometrically.

P95 (**) English number words
On financial documents, like cheques, numbers must sometimes be written in full words. Example: 175 must be written as one-seven-five. Write a predicate full-words/1 to print (non-negative) integer numbers in full words.

P96 (**) Syntax checker (alternative solution with difference lists)
[p96]
In a certain programming language (Ada) identifiers are defined by the syntax diagram (railroad chart) opposite. Transform the syntax diagram into a system of syntax diagrams which do not contain loops; i.e. which are purely
recursive. Using these modified diagrams, write a predicate identifier/1 that can check whether or not a given string is a legal identifier.

% identifier(Str) :- Str is a legal identifier
P97 (**) Sudoku
Sudoku puzzles go like this:

Problem statement                 Solution

.  .  4 | 8  .  . | .  1  7      9  3  4 | 8  2  5 | 6  1  7
|         |                      |         |
6  7  . | 9  .  . | .  .  .      6  7  2 | 9  1  4 | 8  5  3
|         |                      |         |
5  .  8 | .  3  . | .  .  4      5  1  8 | 6  3  7 | 9  2  4
--------+---------+--------      --------+---------+--------
3  .  . | 7  4  . | 1  .  .      3  2  5 | 7  4  8 | 1  6  9
|         |                      |         |
.  6  9 | .  .  . | 7  8  .      4  6  9 | 1  5  3 | 7  8  2
|         |                      |         |
.  .  1 | .  6  9 | .  .  5      7  8  1 | 2  6  9 | 4  3  5
--------+---------+--------      --------+---------+--------
1  .  . | .  8  . | 3  .  6      1  9  7 | 5  8  2 | 3  4  6
|         |                      |         |
.  .  . | .  .  6 | .  9  1      8  5  3 | 4  7  6 | 2  9  1
|         |                      |         |
2  4  . | .  .  1 | 5  .  .      2  4  6 | 3  9  1 | 5  7  8

Every spot in the puzzle belongs to a (horizontal) row and a (vertical) column, as well as to one single 3x3 square (which we call "square" for short). At the beginning, some of the spots carry a single-digit number between 1 and
9. The problem is to fill the missing spots with digits in such a way that every number between 1 and 9 appears exactly once in each row, in each column, and in each square.
P98 (***) Nonograms
Around 1994, a certain kind of puzzles was very popular in England. The "Sunday Telegraph" newspaper wrote: "Nonograms are puzzles from Japan and are currently published each week only in The Sunday Telegraph. Simply use your logic
and skill to complete the grid and reveal a picture or diagram." As a Prolog programmer, you are in a better situation: you can have your computer do the work! Just write a little program ;-).

The puzzle goes like this: Essentially, each row and column of a rectangular bitmap is annotated with the respective lengths of its distinct strings of occupied cells. The person who solves the puzzle must complete the bitmap given
only these lengths.

Problem statement:          Solution:

|_|_|_|_|_|_|_|_| 3         |_|X|X|X|_|_|_|_| 3
|_|_|_|_|_|_|_|_| 2 1       |X|X|_|X|_|_|_|_| 2 1
|_|_|_|_|_|_|_|_| 3 2       |_|X|X|X|_|_|X|X| 3 2
|_|_|_|_|_|_|_|_| 2 2       |_|_|X|X|_|_|X|X| 2 2
|_|_|_|_|_|_|_|_| 6         |_|_|X|X|X|X|X|X| 6
|_|_|_|_|_|_|_|_| 1 5       |X|_|X|X|X|X|X|_| 1 5
|_|_|_|_|_|_|_|_| 6         |X|X|X|X|X|X|_|_| 6
|_|_|_|_|_|_|_|_| 1         |_|_|_|_|X|_|_|_| 1
|_|_|_|_|_|_|_|_| 2         |_|_|_|X|X|_|_|_| 2
1 3 1 7 5 3 4 3             1 3 1 7 5 3 4 3
2 1 5 1                     2 1 5 1

For the example above, the problem can be stated as the two lists [[3],[2,1],[3,2],[2,2],[6],[1,5],[6],[1],[2]] and [[1,2],[3,1],[1,5],[7,1],[5],[3],[4],[3]] which give the "solid" lengths of the rows and columns, top-to-bottom and
left-to-right, respectively. Published puzzles are larger than this example, e.g. 25 x 20, and apparently always have unique solutions.

P99 (***) Crossword puzzle
Given an empty (or almost empty) framework of a crossword puzzle and a set of words. The problem is to place the words into the framework.

[p99]
The particular crossword puzzle is specified in a text file which first lists the words (one word per line) in an arbitrary order. Then, after an empty line, the crossword framework is defined. In this framework specification, an
empty character location is represented by a dot (.). In order to make the solution easier, character locations can also contain predefined character values. The puzzle opposite is defined in the file p99a.dat, other examples are
p99b.dat and p99d.dat. There is also an example of a puzzle (p99c.dat) which does not have a solution.

Words are strings (character lists) of at least two characters. A horizontal or vertical sequence of character places in the crossword puzzle framework is called a site. Our problem is to find a compatible way of placing words onto
sites.

Hints: (1) The problem is not easy. You will need some time to thoroughly understand it. So, don't give up too early! And remember that the objective is a clean solution, not just a quick-and-dirty hack!
(2) Reading the data file is a tricky problem for which a solution is provided in the file p99-readfile.lisp. Use the predicate read_lines/2.
(3) For efficiency reasons it is important, at least for larger puzzles, to sort the words and the sites in a particular order. For this part of the problem, the solution of P28 may be very helpful.

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