A Practical Introduction to Data Structures and Algorithm Analysis

Sec. 5.6 Huffman Coding Trees 195// Build a Huffman tree from list huffliststatic HuffTree buildTree(List hufflist) {HuffTree tmp1, tmp2, tmp3;LettFreq tmpnode;for(hufflist.moveToPos(1); hufflist.length() > 1;hufflist.moveToPos(1)) {// While at least two items lefthufflist.moveToStart();tmp1 = hufflist.remove();tmp2 = hufflist.remove();tmpnode = new LettFreq(tmp1.weight() + tmp2.weight());tmp3 = new HuffTree(tmpnode, tmp1, tmp2);}// return to the list in sorted orderfor (hufflist.moveToStart();hufflist.currPos() < hufflist.length();hufflist.next())if (tmp3.weight() = hufflist.length())hufflist.append(tmp3); // This is heaviest value}hufflist.moveToStart(); // This is only tree on listreturn hufflist.remove(); // Return the treeFigure 5.29 Implementation for the Huffman tree construction function.buildHuff takes as input fl, the min-heap of partial Huffman trees, whichinitially are single leaf nodes as shown in Step 1 of Figure 5.25. The body offunction buildTree consists mainly of a for loop. On each iteration of thefor loop, the first two partial trees are taken off the heap and placed in variablestemp1 and temp2. A tree is created (temp3) such that the left and right subtreesare temp1 and temp2, respectively. Finally, temp3 is returned to fl.VUl 1l 2XFigure 5.30 An impossible Huffman tree, showing the situation where the twonodes with least weight, l 1 and l 2 , are not the deepest nodes in the tree. Trianglesrepresent subtrees.