Overview.Modern computing and the internet have made accessible a vast amount of information. The ability to efficiently search through this information is fundamental to computation. This chapter describes classical searching algorithms that have proven to be effective in numerous applications for decades. We use the term symbol table to describe an abstract mechanism where we save information (a value) that we can later search for and retrieve by specifying a key.
- 3.1 Elementary Symbol Tables includes unordered and ordered implementations, using arrays or linked lists.
- 3.2 Binary Search Trees describes binary search trees.
- 3.3 Balanced Search Trees describes red-black BSTs, a data structure that guarantees logarithmic performance per symbol table operation.
- 3.4 Hash Tables describes two classic hashing algorithms: separate chaining and linear probing.
- 3.5 Applications introduces the set data type and includes numerous applications of symbol tables and sets.
Java programs in this chapter.Below is a list of Java programs in this chapter. Click on the program name to access the Java code; click on the reference number for a brief description; read the textbook for a full discussion.
REF PROGRAM DESCRIPTION / JAVADOC - FrequencyCounter.java frequency counter 3.1 SequentialSearchST.java sequential search 3.2 BinarySearchST.java binary search 3.3 BST.java binary search tree 3.4 RedBlackBST.java red-black tree 3.5 SeparateChainingHashST.java separate chaining hash table 3.6 LinearProbingHashST.java linear probing hash table - ST.java ordered symbol table - SET.java ordered set - DeDup.java remove duplicates - AllowFilter.java allowlist filter - BlockFilter.java blocklist filter - LookupCSV.java dictionary lookup - LookupIndex.java index and inverted index - FileIndex.java file indexing - SparseVector.java sparse vector