Abstract:
A database analysis apparatus pays its attention to table columns more than two constituting a table among plural tables that a database holds, and analyzes automatically a dependence and a limitation condition that exist between the table columns from a tendency of appearance at the same time of data which each table column maintains, which comprises a data category calculation means to calculate a method of categorizing a data group from association rules generated from the data group of two or more table columns and an association rules reconstruction means to generate association rules of the best granularity by reconstructing the association rules based on the result of the above categorizing.
Abstract:
A test case is generated by receiving software specification, generating a test case including a test input value for particular software from the software specification, as well as an expected output value expected to be obtained as an output value when the software is executed by inputting the test input value, and checking whether a value that can be output in the software specification is included in the expected output value. As a result of the check, if it is determined that the output value that can be output in the software specification is not included in the expected output value, a test case including the value that can be output in the software specification as well as a corresponding test input value is generated and added to the test case that has been generated.
Abstract:
A database analyzer includes a data sorting unit sorting a data group acquired from an analysis target database based on data values in a table column and storing it as analysis target data in a storage unit; a data pattern creation processing unit creating a group for each data value based on differences between the data values and storing a data pattern in the storage unit; a data pattern judgment processing unit for judging validity of the data pattern; and a data pattern transformation processing unit for reconstructing the data pattern with respect to constituent elements of each group included in the data pattern by transforming each group in accordance with a specified conversion rule for converting the constituent elements, which are conceptually similar to each other, into the same constituent element, and storing it in the storage unit if a negative result is obtained for the validity judgment.