2. Open the database. 3. Create a table.
4. Create an insert interface for datasets. 5. Create a query interface for datasets.
6. Close the database.
2.10. File Saving and Loading
Based on Steele and To 2011, In addition to the Android- specific data storage methods mentioned previously, the standard
java.io.File Java package is available, too. This provides for flat
file manipulation, such as FileInputStream, FileOutputStream, InputStream and OutputStream.
2.11. Indexing
Indexing is collects, parses, and stores
data to facilitate fast
and accurate information retrieval. Index design incorporates interdisciplinary concepts from linguistics, cognitive psychology,
mathematics, informatics
, physics, and computer science. An alternate name for the process in the context of search engines
designed to find web pages on the Internet is Web indexing.
2.12. Regular Expression
Based on Goyvaerts and Levithan 2009, Regular expression is a specific kind of text pattern that you can use with
many modern applications and programming languages. You can use them to verify whether input fits into the text pattern, to find
text that matches the pattern within a larger body of text, to replace text matching the pattern with other text or rearranged bits of the
matched text, to split a block of text into a list of subtexts, and to shoot yourself in the foot.
Based on Watt 2005, Regular expressions are patterns of characters that match, or fail to match, sequences of characters in
text.
2.12.1. Basic Regular Expression Skills
The skills presented in this chapter aren’t the kind of real-world problems that usually customers ask you to
solve. Rather, they’re technical problems encounter while creating and editing regular expressions to solve real-world
problems, for example, explains how to match literal text with a regular expression. This isn’t a goal on its own,
because usually programmers don’t need a regex when programmers want to do is to search for literal text. But
when creating a regular expression, programmers likely
need it to match certain text literally, and programmers need to know which characters to escape.
2.12.2. Matching Single Characters
Based on Watt 2005, The simplest regular expression involves matching a single character. If you
want to match a single, specified alphabetic character or numeric digit, you simply use a pattern that consists of that
character or digit. So, for example, to match the uppercase letter L, the pattern matches any occurrence of the
uppercase L.[13] Here is an example:
Text:
sales1.xls sales2.xls
sales3.xls apac1.xls
europe2.xls na1.xls
na2.xls sa1.xls
Regex:
sales.
Result:
sales1.xls sales2.xls
sales3.xls The alogarithm that will use such as below:
variable = expression IF condition
variable = expression SWITCHcondition
DO action; ELSE
DO next action;
2.12.3. Matching Optional Character
Based on Watt 2005, Matching literal characters is straightforward, particularly when you are aiming to match
exactly one literal character for each corresponding literal character that you include in a
regular expression pattern.[13] Here is example:
Text:
apac1.xls europe2.xls
na1.xls sa1.xls
ca1.xls
Regex:
[ns]a.\.xls
Result:
na1.xls na2.xls
sa1.xls
2.12.4. Matching Multiple Optional Characters
Based on Watt 2005, With the techniques that you have seen so far, you aren’t able to express ideas such as
“match something only if it is not preceded by something else.” That sort of approach might help achieve higher
specificity at the expense of increased complexity.[13] Here is example:
Text:
sales3.xls sam.xls
na1.xls na2.xls
sa1.xls ca1.xls
Regex:
[ns]a[0123456789]\.xls
Result:
na1.xls na2.xls
sa1.xls
2.13. PHP
