JP5076700B2 - Database verification method and apparatus - Google Patents

Description

  The present invention relates to a technique for verifying whether the contents of data stored in a database are consistent in business.

  Conventionally, in a business application test or operational environment, there are two methods for verifying whether business data consistency is achieved for DB data stored in a database (DB), for example, as follows. It was.

  (A) For example, there is a method in which the user verifies whether DB data is consistent in business using SQL or the like for each column or between tables. However, in this method, the SQL sentence for verification must be described one by one, which takes man-hours and the description itself may be difficult depending on the contents. In particular, in a large scale DB, it is extremely difficult for a user to describe and execute an SQL statement for each design constraint condition item.

(B) On the other hand, there is a method of acquiring related data between items using relation information between databases. As a method similar to such a method, for example, there is a technique described in Japanese Patent Application Laid-Open No. 2007-4447. Specifically, referring to the table definition table that stores the table name and one or more item names of the table in association with each other based on the input item name, the item name 1 The first table extraction step for extracting the first table name having the first table name and the table link table storing the two tables related by having a common item in association with each other, A related table extracting step of extracting a related table associated with the related table and extracting all the related tables when there is another related table associated with the related table; , Obtain data values of all items associated with the first table in the data values input in association with the item name of 1 above, From one or more related tables extracted by continuous table extractor, a data acquisition step of acquiring all the data values that are associated to the input data value via the common item is executed. However, since there are no constraints, business consistency cannot be verified.
JP 2007-4447 A

  When testing an application program, a database may be required. However, correct data cannot be obtained unless business-consistent data is stored in the database. However, as described above, it is very time consuming to verify whether or not business-consistent data is stored in the database.

  Therefore, an object of the present invention is to provide a technique for automatically verifying whether the contents of data stored in a database are consistent in business.

  The database verification method according to the present invention includes a constraint information storage unit that stores constraint information about constraint conditions for data items stored in a database including a database to be verified, an analysis template for constraint information, and the analysis template. A template storage unit that stores the corresponding verification SQL template, parameter acquisition SQL template, and verification statement template is accessible and executed by a computer having a processing unit. The database verification method matches the constraint information stored in the constraint information storage unit with the analysis template stored in the template storage unit, and identifies an analysis template that matches the constraint information. And the step of identifying the value of the variable in the identified analysis template from the constraint information, the parameter acquisition SQL template corresponding to the identified analysis template, and the value of the identified variable Generating a parameter acquisition SQL statement by combining with the corresponding one, executing the parameter acquisition SQL statement on the database and acquiring the search result as a parameter, and the identified analysis template SQL template for verification corresponding to A search result obtained by executing, for the database, a verification SQL statement in which the corresponding one of the values of the variables and any of the acquired parameters is combined, and acquiring the search result as a second search result Determining whether the acquisition step and the acquired second search result satisfy a verification sentence in which a verification sentence template corresponding to the identified analysis template and a verification SQL sentence are combined; And a log generation step of generating a log including parameters combined with the verification SQL sentence that has resulted in the second search result.

  According to such a configuration, it is possible to automatically perform verification processing on a database by effectively using constraint information in machine-readable design information.

  In addition, in the log generation step described above, a verification sentence template corresponding to a specific variable value among the specified analysis template and the specified variable value may be used. If various templates corresponding to the constraint information are prepared, the number of databases that can be automatically verified can be increased.

  A program for causing a computer to execute this method can be created, and this program is stored in a storage medium or storage device such as a flexible disk, a CD-ROM, a magneto-optical disk, a semiconductor memory, or a hard disk. . Moreover, it may be distributed as a digital signal via a network or the like. The intermediate processing result is temporarily stored in a storage device such as a main memory.

  According to the present invention, it is possible to automatically verify whether the contents of data stored in a database are consistent in business.

  A functional block diagram of a database verification apparatus according to an embodiment of the present invention is shown in FIG. The database verification apparatus 100 according to the present embodiment includes a constraint information storage unit 1 that stores constraint information included in design information, a template storage unit 3 that stores various templates described below, a constraint information storage unit 1, A constraint information reading unit 5 that performs processing using the data stored in the template storage unit 3, a variable data storage unit 7 that stores variable data that is a processing result of the constraint information reading unit 5, a variable data storage unit 7 and A verification statement generation unit 9 that uses the data stored in the template storage unit 3 and performs processing according to the processing result of the constraint information reading unit 5, and a verification statement data storage that stores the processing result of the verification statement generation unit 9 Section 13, using data stored in variable data storage section 7 and template storage section 3, and depending on the processing result of constraint information reading section 5 A parameter detection unit 11 that performs a search on the DB 200 including the verification target database, a parameter storage unit 15 that stores a parameter that is a search result of the parameter detection unit 11, a verification sentence data storage unit 13, A verification execution unit 17 that performs processing using data stored in the parameter storage unit 15 and performs a search on the DB 200, and an evaluation log storage unit that stores an evaluation log that is a processing result of the verification execution unit 17 19 and an output unit 21 for outputting data stored in the evaluation log storage unit 19.

  Next, FIG. 2 shows an example of data stored in the constraint information storage unit 1. In this embodiment, among the three columns, the leftmost column is the database name to be verified (table name), the second column from the left is the name of the verification target column, and the rightmost column is the check contents Is to be registered. In the example of FIG. 2, the verification target database is “order DB”, the verification target column is “product code”, and the check content is “product DB. Exists in product code”. In some cases, the constraint information describes a constraint condition between tables (referred to as “relevant check”), and may describe a constraint condition for one column (referred to as “unary check”). In some cases, a constraint between columns in a table is described (referred to as single association check). The constraint information is described in a format that can be processed by the constraint information reading unit 5. Note that the constraint information is included in the design information and effectively utilizes the design information.

  An example of data stored in the template storage unit 3 is shown in FIGS. FIG. 3 shows an example of a grammar pattern (a template for analyzing constraint information, also referred to as an analysis template) for matching with constraint information. In this embodiment, three grammatical patterns (1) to (3) are shown. In (1), the verification target table is “AA”, the verification target column is “BB”, and the check content is “YY”. (2) is a pattern in which the verification target table is “AA”, the verification target column is “BB”, and the check content is “not present in YY.ZZ” ( 3) The verification target table is “EE”, the verification target column is “II”, and the check content is “CC.DD = EE.FF && CC.GG [H] EE.II” ([H] is <,>, =, ≦, ≧, ≠). “AA”, “BB”, “CC”, “DD”, “EE”, “FF”, “GG”, and “II” are variables, and any value (data) may be used for matching.

  (1) is a pattern for matching against a restriction such as “Product code of order DB exists in product DB. Product code”, and (2) is “Customer of new customer DB”. Is a pattern for matching against a restriction such as “Customer DB does not exist in customer DB. User ID”, and (3) is “When DB1.slip number = DB3.order slip number, “DB1. Order date is after DB3. Purchase date” or “Advertisement DB. Customer ID = Purchase history DB. When customer ID”, the advertisement DB. Recommended product is purchase history DB. This is a pattern for matching against constraints such as “is different”.

  FIG. 4 shows an example of a pseudo SQL sentence template stored in the template storage unit 3. (1) to (3) in FIG. 4 show the correspondence with (1) to (3) in FIG. The pseudo SQL statement template is a template of an SQL statement in a search for verification that is finally executed on the DB 200. (1) is for Select YY. ZZ where AA. BB = [X], and [X] indicates a part for substituting a value to be extracted later as a parameter. The same applies to (2). (3) Select EE. FF from EE where EE. FF = [X] and CC. GG [H] EE. II, and [X] indicates a part for substituting a value to be extracted later as a parameter. [H] is the same as described above. Of course, “AA”, “BB”, “CC”, “DD”, “EE”, “FF”, “GG”, and “II” are variables, and the variable values specified when matching is performed according to the grammatical pattern are substituted. .

  FIG. 5 shows an example of a column value (parameter) acquisition template stored in the template storage unit 3. (1) to (3) in FIG. 5 show the correspondence with (1) to (3) in FIG. The column value acquisition template is an SQL statement template for acquiring a parameter (a value assigned to [X] of the pseudo SQL statement template) from the DB 200. (1) is for Select AA. It is BB and (2) is the same. (3) is for Select CC. DD. Of course, “AA”, “BB”, “CC”, and “DD” are variables, and the variable values specified when matching is performed according to the grammatical pattern are substituted.

  FIG. 6 shows an example of a verification sentence template stored in the template storage unit 3. (1) to (3) in FIG. 6 show the correspondence with (1) to (3) in FIG. Also, [H] is the same as described above, and the value specified when matching is performed according to the grammatical pattern. (1) is assert (empty) which means that a log is output when it is empty (empty), and (2) is that a log is output when it is not empty (not empty). Assert (not empty). (3) depends on [H], and except for ≠ is assert (empty) which means that a log is output when it is empty, and if it is ≠, a log is output when it is not empty This means assert (not empty).

  In order to make the following explanation easy to understand, it is assumed that data as shown in FIGS. 7 and 8 is stored in the DB 200. That is, as shown in FIG. 7, the order DB is registered with a slip number, a product code, a quantity, and an order date. Further, as shown in FIG. 8, a product code and a product name are registered in the product DB.

  Hereinafter, processing contents of the database verification apparatus 100 will be described with reference to FIGS. 9 to 12. The constraint information reading unit 5 reads the constraint information to be processed from the constraint information storage unit 1 (step S1). For example, the constraint information on the first line in FIG. 2 is read. Then, the constraint information reading unit 5 performs pattern matching between the constraint information and each grammar pattern stored in the template storage unit 3 (for example, the grammar pattern shown in each row of FIG. 3). The grammatical pattern to be specified is specified (step S3). In the case of the constraint information on the first line in FIG. 2, the grammatical pattern on the first line (1) in FIG. 3 matches, so (1) is specified.

  The constraint information reading unit 5 extracts the value of each variable in the corresponding grammatical pattern and stores it in the variable data storage unit 7 (step S5). In the grammatical pattern of (1), there are variables “AA”, “BB”, “YY”, and “ZZ”. When matched with the constraint information on the first line in FIG. 2, as shown in FIG. Furthermore, “AA” = “order DB”, “BB” = “product code”, “YY” = “product DB”, and “ZZ” = “product code”. These variables and their values are stored in the variable data storage unit 7. The constraint information reading unit 5 outputs the ID of the corresponding grammar pattern ((1) in the above example) to the verification sentence generation unit 9 and the parameter detection unit 11.

  Then, using the ID of the grammar pattern received from the constraint information reading unit 5, the verification statement generation unit 9 reads a pseudo SQL sentence template corresponding to the corresponding grammar pattern from the template storage unit 3 (step S7). In the example of FIG. 4, the pseudo SQL sentence template “Select YY.ZZ where AA.BB = [X]” in (1) is read. Then, a pseudo SQL statement is generated by assigning a value to the variable of the pseudo SQL statement template, and stored in, for example, the verification statement data storage unit 13 (step S9). A pseudo SQL sentence as shown in FIG. 10B is generated. That is, “Select product DB. Product code where order DB. Product code = [X]” is generated and stored in the verification statement data storage unit 13. Since [X] is not fixed at this stage, it is a “pseudo” SQL sentence.

  Further, the verification statement generation unit 9 reads a verification statement template corresponding to the corresponding grammar pattern from the template storage unit 3, generates a verification statement by combining the verification statement template and the pseudo SQL statement, and generates a verification statement data storage unit. 13 (step S11). In the example of FIG. 6, (1) assert (empty) is extracted and combined with the pseudo SQL statement generated in step S9, and the verification statement “Select product DB. Product code where” shown in FIG. Order DB.Product code = [X]-> assert (empty) "is generated. Then, the processing shifts to the processing in FIG.

  Shifting to the description of the processing in FIG. 11, the parameter detection unit 11 uses the ID of the grammar pattern received from the constraint information reading unit 5 to convert the column value acquisition template corresponding to the corresponding grammar pattern to the template storage unit 3. (Step S13). In the example of FIG. 5, (1) “Select AA.BB” is read. Then, the value of the variable stored in the variable data storage unit 7 is substituted into the variable of the column value acquisition template to generate an SQL statement for parameter acquisition, for example, stored in a storage device such as a main memory ( Step S15). As shown in FIG. 12A, an SQL statement for parameter acquisition of “Select order DB. Commodity code” is generated. Thereafter, an SQL statement for parameter acquisition is executed on the DB 200, a parameter as a search result is acquired and stored in the parameter storage unit 15 (step S17). In the case of the order DB as shown in FIG. 7, the values “ZZ1” and “ZZ2” of the product code column are extracted as parameters and stored in the parameter storage unit 15 as shown in FIG.

  Next, the verification execution unit 17 selects one unprocessed parameter stored in the parameter storage unit 15 (step S19), and the pseudo SQL statement part of the verification statement stored in the verification statement data storage unit 13 The selected parameter is substituted into the variable [X], a verification SQL statement is generated, and stored in a storage device such as a main memory (step S21). For example, when “ZZ1” is selected, a verification SQL statement “Select product DB. Product code where order DB. Product code =“ ZZ1 ”” is generated as shown in FIG. Then, the generated SQL statement for verification is executed on the DB 200, and the search result is acquired (step S23). When a search is executed by executing the SQL statement as described above for the product DB as shown in FIG. 8, since the corresponding record exists, “Product DB.ZZ1” is displayed as shown in FIG. Obtained as a search result.

  The verification execution unit 17 determines whether the search result matches the content of the assert in the verification sentence (step S25). As shown in FIG. 10C, since the verification statement in this example is “assert (empty)”, it is determined that there is a match in the case of empty. In the case of the search result as shown in FIG. 12D, it cannot be said that there is a match. When it cannot be said that it matched in step S25, it transfers to step S29. On the other hand, if the search result is empty, it matches the content of the assert, so an evaluation log is generated and stored in the evaluation log storage unit 19 (step S27).

  Then, the verification execution unit 17 determines whether or not an unprocessed parameter exists in the parameter storage unit 15 (step S29). If an unprocessed parameter exists, the verification execution unit 17 returns to step S19.

  Here, since “ZZ2” remains, in step S21, as shown in FIG. 12E, a verification SQL statement “Select product DB. Product code where order DB. Product code =“ ZZ2 ”” is generated. Is done. Then, if a search is performed by executing such an SQL statement on the product DB as shown in FIG. 8, there is no corresponding record, so the search “empty” as shown in FIG. Results are obtained. If it does so, in step S25, since it will match the content of the assertion of an evaluation sentence, an evaluation log will be generated. As shown in FIG. 13, the evaluation log is “NG: order DB. Product code =“ ZZ2 ””. That is, it is data for specifying a record in the verification target database that includes the parameter “ZZ2” for which the evaluation log is to be generated and is not consistent in business.

  When it is determined that there is no unprocessed parameter after performing such processing, the output unit 21 outputs the evaluation log stored in the evaluation log storage unit 19 from a display device, a printing device, or the like. (Step S31). In this way, the user can specify which part of the verification target database is not consistent in business when performing the test, and can take corrective action such as correction.

  By performing the above processing, it is possible to automatically verify the database for business consistency, and to prevent problems from occurring during system testing. Become.

  Next, a second specific example will be described with reference to FIGS. For example, it is assumed that data as illustrated in FIG. 14 is stored in the constraint information storage unit 1. That is, the verification target database is “DB3”, the verification target column is “purchase date”, and the check contents are “DB1. Slip number = DB3. Order slip number && DB1. Order date ≦ DB3. Purchase date”. Yes. This is constraint information indicating that the order date of DB1 must be before the purchase date of DB3 for orders with the same slip number in DB1 and DB3. Further, it is assumed that data as shown in FIG. 15 is stored in DB1. That is, the slip number, product code, quantity, and order date are registered. Similarly, data as shown in FIG. 16 is stored in DB3. That is, the product code, purchase date, quantity, and order slip number are registered.

  According to the processing flow of FIGS. 9 and 11, first, matching with the grammar pattern of FIG. 3, (3) is specified as the corresponding grammar pattern. Here, as shown in FIG. 17A, “CC” = “DB1”, “DD” = “slip number”, “EE” = “DB3”, “FF” = “order slip number”, “GG” "=" Order Date "and" II "=" Purchase Date "are specified. [H] is “≦”.

  Then, as shown in FIG. 4 and FIG. 6 (3) to FIG. 17 (b), the verification sentence is “Select DB3. Order slip number from DB3 where DB3. Order slip number = [X] and DB1. Date ≦ DB3.Purchase date → assert (empty) ”.

  In addition, the SQL statement for parameter acquisition is “Select DB1. Slip number” as shown in FIG. 5 (3) to FIG. 17 (c). When this SQL statement is executed on DB1 (FIG. 15), “A1234” and “B1234” are acquired as search results as shown in FIG.

  Then, the SQL statement for verification is “Select DB3. Order slip number from DB3 where DB3. Order slip number =“ A1234 ”and DB1. Order date ≦ DB3. Purchase date” as shown in FIG. When this is executed for the DB 200, “empty” is obtained as shown in FIG. This is because the purchase date of the slip number “A1234” is before the order date, so that there is no record that matches the verification SQL statement. Therefore, an evaluation log such as “NG: X =“ A1234 ”” is generated as shown in FIG.

  Next, as shown in FIG. 17 (i), a verification SQL statement “Select DB3. Order slip number from DB3 where DB3. Order slip number =“ B1234 ”and DB1. Order date ≦ DB3. Purchase date”. Is generated and executed on the DB 200, “B1234” is obtained as shown in FIG. Since it is not empty, an evaluation log is not generated.

  Thus, it can be seen that a record that is inconsistent in business is registered for the slip number “A1234”.

  Although the embodiment of the present invention has been described above, the present invention is not limited to this. For example, the functional block diagram shown in FIG. 1 may not be the same as the actual program module configuration. In addition, since steps S7 to S11 and steps S13 to S17 are independent processes, they may be executed in parallel or the order of execution may be changed.

  The database verification device 100 is, for example, a computer device. In the computer device, as shown in FIG. 18, a memory 2501 (storage unit), a CPU 2503 (processing unit), a hard disk drive (HDD) 2505, and a display device are included. A display control unit 2507 connected to 2509, a drive device 2513 for the removable disk 2511, an input device 2515, and a communication control unit 2517 for connecting to a network are connected by a bus 2519. Application programs including an operating system (OS) and a Web browser are stored in the HDD 2505, and are read from the HDD 2505 to the memory 2501 when executed by the CPU 2503. If necessary, the CPU 2503 controls the display control unit 2507, the communication control unit 2517, and the drive device 2513 to perform necessary operations. Further, data in the middle of processing is stored in the memory 2501 and stored in the HDD 2505 if necessary. Such a computer realizes various functions as described above by organically cooperating hardware such as the CPU 2503 and the memory 2501 described above with the OS and necessary application programs.

(Appendix 1)
A constraint information storage unit that stores constraint information on constraint conditions for data items stored in a database including a database to be verified, an analysis template for the constraint information, a verification SQL template corresponding to the analysis template, and parameters To a computer accessible to a template storage unit for storing an acquisition SQL template and a verification statement template,
The constraint information stored in the constraint information storage unit is matched with the analysis template stored in the template storage unit to identify an analysis template that matches the constraint information, and from the constraint information Identifying the value of the variable in the identified analytical template;
A parameter acquisition SQL statement is generated by combining the parameter acquisition SQL template corresponding to the specified analysis template and the corresponding value of the specified variable, and the parameter acquisition SQL statement To the database to obtain the search result as a parameter;
A verification SQL statement in which the verification SQL template corresponding to the specified analysis template, the corresponding one of the specified values of the variable, and any one of the acquired parameters is combined is stored in the database. And a search result acquisition step for acquiring the search result as a second search result,
It is determined whether the acquired second search result satisfies a verification statement in which the verification statement template corresponding to the specified analysis template and the verification SQL statement are combined, and is satisfied. A log generation step for generating a log including the parameters combined with the verification SQL statement that resulted in the second search result;
Database verification program to execute.

(Appendix 2)
In the log generation step,
The database verification program according to claim 1, wherein a verification sentence template corresponding to a value of a specific variable among the specified template for analysis and the value of the specified variable is used.

(Appendix 3)
A constraint information storage unit that stores constraint information on constraint conditions for data items stored in a database including a database to be verified, an analysis template for the constraint information, a verification SQL template corresponding to the analysis template, and parameters A database verification method that is accessible to a template storage unit that stores an acquisition SQL template and a verification statement template, and that is executed by a computer having a processing unit,
The constraint information stored in the constraint information storage unit is matched with the analysis template stored in the template storage unit to identify an analysis template that matches the constraint information, and from the constraint information Identifying the value of the variable in the identified analytical template;
A parameter acquisition SQL statement is generated by combining the parameter acquisition SQL template corresponding to the specified analysis template and the corresponding value of the specified variable, and the parameter acquisition SQL statement To the database to obtain the search result as a parameter;
A verification SQL statement in which the verification SQL template corresponding to the specified analysis template, the corresponding one of the specified values of the variable, and any one of the acquired parameters is combined is stored in the database. And a search result acquisition step for acquiring the search result as a second search result,
It is determined whether the acquired second search result satisfies a verification statement in which the verification statement template corresponding to the specified analysis template and the verification SQL statement are combined, and is satisfied. A log generation step for generating a log including the parameters combined with the verification SQL statement that resulted in the second search result;
Database validation method including:

(Appendix 4)
A constraint information storage unit that stores constraint information about constraint conditions for data items stored in the database including the database to be verified;
A template storage unit for storing an analysis template of the constraint information, a verification SQL template corresponding to the analysis template, a parameter acquisition SQL template, and a verification statement template;
The constraint information stored in the constraint information storage unit is matched with the analysis template stored in the template storage unit to identify an analysis template that matches the constraint information, and from the constraint information Means for specifying the value of the variable in the specified analysis template;
A parameter acquisition SQL statement is generated by combining the parameter acquisition SQL template corresponding to the specified analysis template and the corresponding value of the specified variable, and the parameter acquisition SQL statement Means for executing the search on the database and acquiring the search result as a parameter;
A verification SQL statement in which the verification SQL template corresponding to the specified analysis template, a corresponding value among the specified values of the variable, and any one of the acquired parameters is combined with the database And a search result acquisition means for acquiring the search result as a second search result,
It is determined whether the acquired second search result satisfies a verification statement in which the verification statement template corresponding to the specified analysis template and the verification SQL statement are combined, and is satisfied. Log generating means for generating a log including the parameter combined with the verification SQL statement that has resulted in the second search result,
A database verification apparatus.

It is a figure which shows the system outline | summary which concerns on embodiment of this invention. It is a figure which shows an example of the data stored in a constraint information storage part. It is a figure which shows an example of the data (grammar pattern) stored in a template storage part. It is a figure which shows an example of the data (pseudo SQL sentence template) stored in a template storage part. It is a figure which shows an example of the data (SQL statement template for column value acquisition) stored in a template storage part. It is a figure which shows an example of the data (verification sentence template) stored in a template storage part. It is a figure which shows an example of the data stored in order DB. It is a figure which shows an example of the data stored in goods DB. It is a figure which shows the processing flow in embodiment of this invention. (A) thru | or (c) are figures which show the intermediate result in a processing flow. It is a figure which shows the processing flow in embodiment of this invention. (A) thru | or (f) is a figure which shows the intermediate result in a processing flow. It is a figure which shows an example of the data stored in an evaluation log storage part. It is a figure which shows an example of the data stored in a constraint information storage part. It is a figure which shows an example of the data stored in DB1. It is a figure which shows an example of the data stored in DB3. (A) thru | or (j) is a figure which shows the intermediate result of the process in a 2nd specific example. It is a functional block diagram of a computer.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Constraint information storage part 3 Template storage part 5 Constraint information reading part 7 Variable data storage part 9 Verification sentence generation part 11 Parameter detection part 13 Verification sentence data storage part 15 Parameter storage part 17 Verification execution part 19 Evaluation log storage part 21 Output part 100 Database verification device 200 DB

Claims (4)

A constraint information storage unit that stores constraint information on constraint conditions for data items stored in a database including a database to be verified, an analysis template for the constraint information, a verification SQL template corresponding to the analysis template, and parameters To a computer accessible to a template storage unit for storing an acquisition SQL template and a verification statement template,
The constraint information stored in the constraint information storage unit is matched with the analysis template stored in the template storage unit to identify an analysis template that matches the constraint information, and from the constraint information Identifying the value of the variable in the identified analytical template;
A parameter acquisition SQL statement is generated by combining the parameter acquisition SQL template corresponding to the specified analysis template and the corresponding value of the specified variable, and the parameter acquisition SQL statement To the database to obtain the search result as a parameter;
A verification SQL statement in which the verification SQL template corresponding to the specified analysis template, the corresponding one of the specified values of the variable, and any one of the acquired parameters is combined is stored in the database. And a search result acquisition step for acquiring the search result as a second search result,
It is determined whether the acquired second search result satisfies a verification statement in which the verification statement template corresponding to the specified analysis template and the verification SQL statement are combined, and is satisfied. A log generation step for generating a log including the parameters combined with the verification SQL statement that resulted in the second search result;
Database verification program to execute. In the log generation step,
The database verification program according to claim 1, wherein a verification sentence template corresponding to a value of a specific variable among the specified template for analysis and the value of the specified variable is used. A constraint information storage unit that stores constraint information on constraint conditions for data items stored in a database including a database to be verified, an analysis template for the constraint information, a verification SQL template corresponding to the analysis template, and parameters A database verification method that is accessible to a template storage unit that stores an acquisition SQL template and a verification statement template, and that is executed by a computer having a processing unit,
The constraint information stored in the constraint information storage unit is matched with the analysis template stored in the template storage unit to identify an analysis template that matches the constraint information, and from the constraint information Identifying the value of the variable in the identified analytical template;
A parameter acquisition SQL statement is generated by combining the parameter acquisition SQL template corresponding to the specified analysis template and the corresponding value of the specified variable, and the parameter acquisition SQL statement To the database to obtain the search result as a parameter;
A verification SQL statement in which the verification SQL template corresponding to the specified analysis template, the corresponding one of the specified values of the variable, and any one of the acquired parameters is combined is stored in the database. And a search result acquisition step for acquiring the search result as a second search result,
It is determined whether the acquired second search result satisfies a verification statement in which the verification statement template corresponding to the specified analysis template and the verification SQL statement are combined, and is satisfied. A log generation step for generating a log including the parameters combined with the verification SQL statement that resulted in the second search result;
Database validation method including: A constraint information storage unit that stores constraint information about constraint conditions for data items stored in the database including the database to be verified;
A template storage unit for storing an analysis template of the constraint information, a verification SQL template corresponding to the analysis template, a parameter acquisition SQL template, and a verification statement template;
The constraint information stored in the constraint information storage unit is matched with the analysis template stored in the template storage unit to identify an analysis template that matches the constraint information, and from the constraint information Means for specifying the value of the variable in the specified analysis template;
A parameter acquisition SQL statement is generated by combining the parameter acquisition SQL template corresponding to the specified analysis template and the corresponding value of the specified variable, and the parameter acquisition SQL statement Means for executing the search on the database and acquiring the search result as a parameter;
A verification SQL statement in which the verification SQL template corresponding to the specified analysis template, the corresponding one of the specified values of the variable, and any one of the acquired parameters is combined is stored in the database. And a search result acquisition means for acquiring the search result as a second search result,
It is determined whether the acquired second search result satisfies a verification statement in which the verification statement template corresponding to the specified analysis template and the verification SQL statement are combined, and is satisfied. Log generating means for generating a log including the parameter combined with the verification SQL statement that has resulted in the second search result,
A database verification apparatus.

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