We will be able to use the next define to boost our application: whereas there's enter get a observe look for note if be aware is within the desk upload 1 to its count number else upload note to the desk set its count number to one endif endwhile print desk it is a ordinary “search and insert” state of affairs. We look for the following observe one of the phrases kept to this point. If the quest succeeds, the single factor to do is increment its count number. If the hunt fails, the notice is installed the desk and its count number set to one. a big layout selection this is the way to seek the desk, which, in flip, is determined by the place and the way a brand new notice is inserted within the desk. the subsequent are probabilities: 1. a brand new be aware is inserted within the subsequent loose place within the desk. this suggests sequential seek needs to be used to appear for an incoming be aware because the phrases wouldn't be in any specific order. this technique has the benefits of simplicity and straightforward insertion, yet looking out takes longer as extra phrases are installed the desk. 2. a brand new be aware is inserted within the desk in this kind of means that the phrases are regularly in alphabetical order. this can entail relocating phrases that experience already been saved in order that the hot be aware might be slotted within the correct position. in spite of the fact that, because the desk is so as, a binary seek can be utilized to look for an incoming note. For (2), looking is quicker, yet insertion is slower than in (1). given that, quite often, looking out is completed extra often than placing, (2) can be top-rated. one other good thing about (2) is that, on the finish, the phrases will already be in alphabetical order and no sorting may be required. If (1) is used, the phrases might want to be looked after to acquire the alphabetical order. we are going to write our software utilizing the procedure in (2). the entire software is proven as software P1. 7. software P1. 7 import java. io. *; import java. util. *; public category WordFrequency { ultimate static int MaxWords = 50; public static void main(String[] args) throws IOException { String[] wordList = new String[MaxWords]; int[] frequency = new int[MaxWords]; FileReader in = new FileReader("passage. txt"); PrintWriter out = new PrintWriter(new FileWriter("output. txt")); for (int h = zero; h < MaxWords; h++) { frequency[h] = zero; wordList[h] = ""; } 20 CHAPTER 1 N SORTING, looking out, AND MERGING int numWords = zero; String notice = getWord(in). toLowerCase(); whereas (! observe. equals("")) { int loc = binarySearch(word, wordList, zero, numWords-1); if (word. compareTo(wordList[loc]) == zero) ++frequency[loc]; //word came upon else //this is a brand new notice if (numWords < MaxWords) { //if desk isn't really complete addToList(word, wordList, frequency, loc, numWords-1); ++numWords; } else out. printf("'%s' now not extra to table\n", word); observe = getWord(in). toLowerCase(); } printResults(out, wordList, frequency, numWords); in. close(); out. close(); } // finish major public static int binarySearch(String key, String[] record, int lo, int hi){ //search for key from list[lo] to list[hi] //if stumbled on, go back its situation; //if now not chanced on, go back the site within which it may be inserted //the calling application will money the positioning to figure out if came upon whereas (lo <= hello) { int mid = (lo + hello) / 2; int cmp = key.