JP6264009B2 - Program, information processing apparatus and information processing method - Google Patents

Description

  The present invention relates to a program, an information processing apparatus, and an information processing method for testing a process executed by software.

  The software test that performs the process of extracting the data stored in the database according to the extraction condition, for example, for each extraction condition, holding the extraction result when the extraction process is normally performed in advance, A technique is known in which the content of a normal extraction result is compared with the data content of the extraction result at the time of the test to determine whether or not the extraction process has been performed normally (for example, Patent Document 1, Patent Document) 2).

JP 2004-280231 A JP 2007-011512 A

  However, in the above-described technique, the validity of the test result is determined for each output data, so that the time required for processing increases as the data capacity of the extracted database increases.

  In one aspect, the present invention provides a program, an information processing apparatus, and an information processing method capable of performing a test result validity determination process in a short time.

And an aspect of the program is a program for executing processing for data group extracted by the extraction program for performing processing for extracting data from a database, and a second data group extracted by the first extraction condition from the first data group The number of data extracted under the second extraction condition from the data group combined with the first data group is acquired, the number of data to be extracted from the first data group under the second extraction condition, and the second The information processing apparatus is caused to execute processing for determining whether or not the number obtained by adding the number of data to be extracted from the data group according to the second extraction condition matches the number of the acquired data.

  According to one aspect, it is possible to perform a test result validity determination process in a short time.

It is a block diagram which shows the hardware group of information processing apparatus. It is a block diagram which shows the list of various data tables. It is explanatory drawing which shows an example of the data structure of a random table. It is explanatory drawing which shows an example of the data structure of a rewriting table. It is explanatory drawing which shows an example of the data structure of a work table. It is explanatory drawing which shows an example of the data structure of a number table. It is explanatory drawing which shows an example of the data structure of a combination table. It is explanatory drawing which shows an example of the data structure of an overwrite table. It is explanatory drawing which shows an example of the data structure of a master table. It is explanatory drawing which shows an example of the data structure of a correct answer table. It is explanatory drawing which shows an example of the master table which performed the test result determination process. It is a flowchart which shows the process sequence of CPU. It is a flowchart which shows an example of the procedure of a test data generation process. It is a flowchart which shows an example of the procedure of a test data generation process. It is a flowchart which shows an example of the procedure of a test data generation process. It is a flowchart which shows an example of the procedure of a test data generation process. It is a flowchart which shows an example of the procedure of a correct line number production | generation process. It is a flowchart which shows an example of the procedure of a correct line number production | generation process. It is a flowchart which shows an example of the procedure of a correct line number production | generation process. It is a flowchart which shows an example of the procedure of a correct line number production | generation process. It is a flowchart which shows an example of the procedure of a test result determination process. It is a flowchart which shows an example of the procedure of a test result determination process. 10 is a block diagram showing a list of various data tables according to Embodiment 2. FIG. It is explanatory drawing which shows an example of the data structure of an expansion | deployment table. 10 is a flowchart illustrating a processing procedure of a CPU according to the second embodiment. It is a flowchart which shows an example of the procedure of an expansion | deployment table production | generation process. It is explanatory drawing which shows an example of the fault location specific process which CPU performs. It is a flowchart which shows an example of the procedure of a fault location specific process. It is a flowchart which shows an example of the procedure of a fault location specific process. It is a flowchart which shows an example of the procedure of a fault location specific process. FIG. 10 is a block diagram illustrating a hardware group of an information processing device according to a third embodiment. FIG. 10 is a functional block diagram of an information processing device hardware group according to a third embodiment.

Embodiment 1
FIG. 1 is a block diagram illustrating a hardware group of the information processing apparatus 1. The information processing apparatus 1 is a computer that executes a program for confirming the validity of a test result performed on software, such as a personal computer or a server computer. An information processing apparatus 1 illustrated in FIG. 1 includes a CPU (Central Processing Unit) 11, a storage unit 12, an input unit 13, and an output unit 14.

  The CPU 11 is connected to each part of hardware via a bus. The CPU 11 includes, for example, one or a plurality of CPUs or a multi-core CPU. The CPU 11 controls each part of the hardware according to the control program 12P stored in the storage unit 12.

  The storage unit 12 includes a ROM (Read Only Memory) and a RAM (Random Access Memory). The ROM is a nonvolatile memory element such as an EEPROM (Electrically Erasable Programmable ROM) or a flash memory. The RAM is composed of a volatile memory element such as SRAM (Static Random Access Memory) or DRAM (Dynamic Random Access Memory). The storage unit 12 stores various data required when the CPU 11 performs processing, a program 12P executed by the CPU 11, an extraction program 13P that performs extraction processing, and a data table 12T. The data table 12T is composed of a plurality of tables storing data necessary for the information processing apparatus 1 to use for processing.

  The input unit 13 is an input device such as a mouse, a keyboard, or a touch panel, and outputs received operation information to the CPU 11. The output unit 14 outputs image data to be displayed on a display device (not shown).

  FIG. 2 is a block diagram showing a list of various data tables. The data table 12T includes a random table T1, a rewrite table T2, a work table T3, a number table T4, a combination table T5, an overwrite table T6, a master table T7, and a correct answer table T8.

  Next, the data table 12T used in the present embodiment will be described. FIG. 3 is an explanatory diagram showing an example of the data structure of the random table T1. The random table T1 is a table in which a random character string is generated in each column. The random table T1 includes one data item column, two data item columns, three data item columns, and the like. The CPU 11 reads various setting data including the number of rows (NUM_R), the number of columns (NUM_L), the minimum number of characters of items (MINI_L), the maximum number of characters of items (MAX_L), and the like stored in the storage unit 12 in advance. The CPU 11 generates a random table T1 by generating a random character string in each column of the random table T1 based on various setting data (see, for example, JP 2001-256076 A). In the random table T1 shown in FIG. 3, the number of rows is 8, the number of columns is 3, the minimum number of items is 1, and the maximum number of items is 10, but the number of rows or columns is, for example, 1 million rows or more. Alternatively, the table may be used.

  FIG. 4 is an explanatory diagram showing an example of the data structure of the rewrite table T2. The rewrite table T2 is a table that stores character strings to be extracted. The rewrite table T2 includes a data item column 1, a data item column 2, a data item column 3, and the like. The CPU 11 accepts input of rewrite data. The CPU 11 generates a rewrite table T2 from the input rewrite data. Note that the rewrite table T2 may be stored in the storage unit 12 in advance.

  FIG. 5 is an explanatory diagram showing an example of the data structure of the work table T3. The work table T3 is a table for generating an overwrite table T6 described later from the rewrite table T2. The work table T3 includes a data item column 1, a data item column 2, a data item column 3, and the like. The CPU 11 generates a data group in which each column of the generated table is randomly associated with the row number of each column of the rewrite table T2, and generates the work table T3 with the generated data group.

  In the work table T3 shown in FIG. 5, the number of rows is 5, the number of columns is 3, the minimum number of characters of the item is 1, and the maximum number of characters of the item is 10. However, the number of rows or columns is, for example, 100,000 rows or more. Alternatively, the table may be used.

  FIG. 6 is an explanatory diagram showing an example of the data structure of the number table T4. The number table T4 is a table that stores the number of times the row number of each column of the rewrite table T2 is stored in the work table T3. The number table T4 includes a data item column 1, a data item column 2, a data item column 3, and the like. The CPU 11 counts the number of times the row number of each column of the rewrite table T2 is stored in the work table T3. The CPU 11 stores the counted number for each element in the number table T4.

  Specifically, an example of processing in which the CPU 11 generates the number table T4 is as follows. When “1” is stored in the first row of the first column and the fourth row of the first column of the work table T3, the CPU 11 stores “2” in the first row of the first column of the number table T4. When “1” is stored in the first row of the second column of the work table T3, the CPU 11 stores “1” in the first row of the second column of the number table T4. When “1” is stored in the first row of the third column of the work table T3, the CPU 11 stores “1” in the first row of the third column of the number table T4. The CPU 11 performs the same processing for each row.

  FIG. 7 is an explanatory diagram showing an example of the data structure of the combination table T5. The combination table T5 is a table that stores data relating to line number combinations indicating combinations of line numbers associated with data groups. The combination table T5 includes a combination column, a combination number column, and the like. In the combination column, the row number combination is stored by combining the row numbers of the respective columns of the rewrite table T2. In the combination number column, the number of combinations indicating the number of times the same row number combination is stored in the work table T3 is stored.

  The CPU 11 refers to the rewriting table T2 and the work table T3, and generates a row number combination by combining the number of rows of the rewriting table T2 with the number of columns of the rewriting table T2. The CPU 11 counts the number of the same row number combinations. The CPU 11 stores the counted number of row number combinations in the combination table T5.

  Specifically, an example of processing in which the CPU 11 generates the combination table T5 is as follows. The CPU 11 refers to the rewriting table T2 and the work table T3. The CPU 11 stores all combinations from “1, 1, 1” to “4, 4, 4” in the combination table T5. The CPU 11 counts the line number combination “1, 1, 1” from the work table T3. The CPU 11 counts the row number combinations in which the row number combination “1, 1, 1” is stored in the first row of the work table T3, and stores “1” in the first row of the combination number sequence. The CPU 11 counts the line number combination “2, 1, 1” from the work table T3. The CPU 11 determines that the row number combination “2, 1, 1” is not stored in each row of the work table T3, and stores “0” in the second row of the combination number sequence. The CPU 11 then performs the same processing up to “4, 4, 4”.

  FIG. 8 is an explanatory diagram showing an example of the data structure of the overwrite table T6. The overwrite table T6 is a table for overwriting the random table T1. The overwrite table T6 includes a data item column 1, a data item column 2, a data item column 3, and the like. The CPU 11 generates the overwrite table T6 by assigning each element of the rewrite table T2 to the row number of each column of the rewrite table T2 associated with the work table T3.

  Specifically, an example of processing in which the CPU 11 generates the combination table T5 is as follows. When “1” is stored in the first row of the first column of the work table T3, the CPU 11 replaces “aaa” in the first row of the rewrite table T2 with the first row of the first column of the overwrite table T6. Remember in the eyes. When “1” is stored in the first row of the second column of the work table T3, the CPU 11 replaces the “first row” of the first row of the rewrite table T2 with the first row of the second column of the overwrite table T6. Remember in the eyes. When “1” is stored in the first row of the third column of the work table T3, the CPU 11 sets “Napoleon” of the first row of the third column of the rewrite table T2 to the first row of the third column of the overwrite table T6. Remember in the eyes. The CPU 11 performs the same processing for each row.

  FIG. 9 is an explanatory diagram showing an example of the data structure of the master table T7. The master table T7 is a table that stores a data group in which the overwrite table T6 is overwritten on the random table T1. The master table T7 includes a data item column 1, a data item column 2, a data item column 3, and the like. The CPU 11 generates the master table T7 by overwriting each row of the overwrite table T6 at random on the random table T1. Note that the CPU 11 may generate the master table T7 by overwriting the random table T1 with each row of the overwrite table T6 as it is.

  FIG. 10 is an explanatory diagram showing an example of the data structure of the correct answer table T8. The correct answer table T8 is a table storing data related to elements extracted by the extraction program 13P. The correct answer table T8 is stored in the storage unit 12 in advance. The correct answer table T8 includes a test number column, a type column, a search column, a correct column number column, a correct row number column, a combination column, an extracted number column, a test number total column, and the like.

  The test number column stores a test number indicating the order in which the CPU 11 performs the test. The type column stores extraction conditions such as a first extraction condition or a second extraction condition for search performed by the CPU 11 by the extraction program 13P. The first extraction condition is a search extraction condition associated with a test number. The second extraction condition is an extraction condition for a search performed next to the test number associated with the first extraction condition. The search extraction conditions are, for example, A1, A2, B, and the like. A1 is a condition that the character string included in the data group matches the character string to be extracted. A2 is a condition that a part of the character string included in the data group matches the character string to be extracted. B is a condition that the combination of character strings included in the data group matches the combination of character strings to be extracted.

  In the search string, a search character string indicating a character string searched by the CPU 11 by the extraction program 13P is stored. For example, “Aiue”, “aaa, Aiu, Napoleon”, etc. are stored in the search character string. In the correct column number column, the extraction column number of the extracted data group extracted from the data group according to the extraction condition is stored in advance. The extracted column number is a column number of the extracted data group extracted from the data group according to the extraction condition. In the correct answer row number column, the row numbers of the extracted data groups such as the first and second data groups are stored in advance. The first data group is a character string or a combination of character strings extracted from the data group according to the first extraction condition. The second data group is a character string or a combination of character strings extracted from the data group according to the second extraction condition. In the combination column, row number combinations extracted by the CPU 11 by the extraction program 13P are stored in advance. In the extraction number column, the number of extracted lines indicating the number of lines extracted by the CPU 11 by the extraction program 13P is stored in advance. The total number of test numbers is stored in advance in the total test number column.

  The CPU 11 determines the number of first estimation data groups to be extracted from the data group according to the second extraction condition and the number of second estimation data groups to be extracted from the first data group according to the second extraction condition. Estimate the number of added data groups. Specifically, the CPU 11 estimates the added data group by counting the number of coincidence between the row numbers of the first estimated data group and the second data group and the data group stored in advance in the storage unit 12. The CPU 11 stores the number of correct answers indicating the number of extracted data groups estimated based on the correct answer table T8, the work table T3, and the combination table T5 in SEIKAI (). SEIKAI () is an array that stores the number of correct rows, and a test number is stored in the array index. That is, the estimated number of the first data group and the second data group is stored in SEIKAI ().

  FIG. 11 is an explanatory diagram showing an example of the master table T7 subjected to the test result determination process. The test result determination process performed by the CPU 11 will be described below with reference to FIG.

  FIG. 11A is an explanatory diagram showing a master table T7 that has undergone a test result determination process with a test number of 1. As shown in FIG. 11A, the master table T7 is searched with the search character string “Aiue” using type A2. The CPU 11 extracts “Aiue” from the sixth and eighth rows of the master table T7. The CPU 11 stores the number of extracted lines in the number of extracted cases (1). The number of extracted cases () is an array for storing the number of extracted rows, and the test number is stored in the index of the array.

  The CPU 11 determines whether or not the number of extracted cases (1) and SEIKAI (1) match. CPU11 memorize | stores NG in determination (1) which shows whether the implemented test is correct, when extraction number (1) and SEIKAI (1) do not correspond. The argument of judgment () indicates the number of extractions. NG indicates that the test performed is not valid. CPU11 memorize | stores OK in determination (1), when the number of extraction cases (1) and SEIKAI (1) correspond. OK indicates that the test performed is valid. The CPU 11 stores the number of extractions (1) and SEIKAI (1) coincident and OK in the determination (1).

  The CPU 11 adds “ccc”, “Iueo”, and “Emerson” stored in the sixth row of the master table T7 to the ninth row of the master table T7. The CPU 11 adds “abaa”, “Kakikuaiue”, and “Ponte” stored in the eighth row of the master table T7 to the tenth row of the master table T7.

  FIG. 11B is an explanatory diagram showing a master table T7 that has undergone a test result determination process with a test number of 2. As shown in FIG. 11B, the CPU 11 searches the master table T7 for the search character string “Aiu” using type A1. The CPU 11 erroneously extracts “Kakikuaiue” from the eighth row of the master table T7. The CPU 11 stores the number of rows 1 in the number of extracted cases (2). The CPU 11 stores the number of extracted cases (2) and SEIKAI (2), and stores OK in the determination (2).

  The CPU 11 adds “abaa”, “Kakikuaiue”, and “Ponte” stored in the eighth row of the master table T7 to the eleventh row of the master table T7.

  FIG. 11C is an explanatory diagram showing the master table T7 on which the test result determination process with the test number 3 is performed. As shown in FIG. 11C, the CPU 11 searches the master table T7 for a search character string “aaa, Aiu, Napoleon” by using type B. The CPU 11 extracts “aaa”, “Aiu”, and “Napoleon” from the second row of the master table T7. The CPU 11 stores the extracted number of rows 2 in the number of extracted cases (3). The CPU 11 stores NG in the determination (3) because the number of extracted cases (3) does not match the SEIKAI (3). The CPU 11 adds “aaa”, “Aiu”, and “Napoleon” stored in the second row of the master table T7 to the twelfth row of the master table T7.

  FIG. 12 is a flowchart showing the processing procedure of the CPU 11. The CPU 11 sets various setting data such as a random table T1 and a work table T3 (step S1). Specifically, the CPU 11 sets setting data such as NUM_R, NUM_L, MINI_L, and MAX_L.

  The CPU 11 accepts input of rewrite data (step S2). The CPU 11 generates a rewrite table T2 from the input rewrite data (step S3). The CPU 11 performs test data generation processing (step S4). The CPU 11 performs a correct answer number generation process (step S5). The CPU 11 performs a test result determination process (step S6) and ends the process.

  13 to 16 are flowcharts showing an example of the procedure of the test data generation process. The CPU 11 reads various setting data (step S11). Specifically, the CPU 11 reads setting data such as NUM_R, NUM_L, MINI_L, and MAX_L. The CPU 11 generates a random table T1 by generating a random character string in each column of the random table T1 based on various setting data (step S12).

  The CPU 11 reads the rewrite table T2 (step S13). The rewrite data is stored in SOURCE (i, j) (step S14). SOURCE () is an array storing rewrite data. The loop variable i is used as an index of an array that stores row numbers. The loop variable j is used as an index of an array that stores column numbers.

  The CPU 11 stores the total number of row numbers for each column in the rewrite table T2 in N (j) (step S15). N (j) is an array storing the total number of row numbers for each column of rewrite data. The CPU 11 stores the numbers 1 to N (j) at random for every j columns of WORK (i, j) (step S16). WORK () is a data group, and is an array for storing the row numbers of rewrite data. The CPU 11 stores WORK (i, j) in the work table T3 (step S17).

  The CPU 11 refers to the work table T3 and counts the number of times the row number of each column of the rewrite table T2 is stored in the work table T3 (step S18). The CPU 11 stores the counted number in the number table T4 (step S19).

  The CPU 11 sets the loop variable i to 1 (step S20). The CPU 11 sets the loop variable j to 1 (step S21). The CPU 11 stores the value of WORK (i, j) in the variable L that stores the line number of the rewrite data (step S22). The CPU 11 stores SOURCE (L, j) in BASEDATA (i, j) (step S23). BASEDATA () is an array for storing overwrite data. That is, the CPU 11 stores the element stored in the j column of the L row of the rewrite table T2 in the j column of the i row of the overwrite table T6.

  The CPU 11 increments the loop variable j by 1 (step S24). The CPU 11 determines whether or not the loop variable j exceeds NUM_R (step S25). If the CPU 11 determines that the loop variable j has not exceeded NUM_R (step S25: NO), the CPU 11 returns to step S22 and continues the process. When the CPU 11 determines that the loop variable j exceeds NUM_R (step S25: YES), the CPU 11 increments the loop variable i by 1 (step S26). The CPU 11 determines whether or not the loop variable i exceeds NUM_D (step S27). When the CPU 11 determines that the loop variable i has not exceeded NUM_D (step S27: NO), the CPU 11 returns to step S21 and continues the process.

When the CPU 11 determines that the loop variable i exceeds NUM_D (step S27: YES), the CPU 11 refers to the work table T3 and counts the total number of combinations obtained by multiplying the number of rows of the rewrite table T2 by the number of columns of the rewrite table T2 ( Step S28). Specifically, the total number of combinations is counted by the following formula.
NUM = N (1) × N (2) × ...... × N (NUM_R)

  The CPU 11 stores the counted total number of combinations in the correct answer table T8 (step S29). The CPU 11 generates a line number combination based on the rewrite table T2 (step S30). Specifically, the CPU 11 generates a row number combination by combining the number of rows of the rewrite table T2 by the number of columns of the rewrite table T2. The CPU 11 stores the generated line number combination in the combination number L (i) and the combination table T5 (step S31). The combination number L () is an array that stores row number combinations. The CPU 11 counts the number of the same row number combinations stored in the combination number L (i) in the work table T3 (step S32). The CPU 11 stores the counted number of the same row number combinations in the variable SU and the combination table T5 (step S33). The variable SU is a variable for storing the number of the same row number combinations counted.

  The CPU 11 randomly extracts NUM_D line numbers from the work table T3 (step S34). The CPU 11 stores the extracted value in LINE_O (i) (step S35). LINE_O () is an array that stores randomly extracted row numbers.

  The CPU 11 sets the loop variable i to 1 (step S36). The CPU 11 stores the value of LINE_O (i) in the variable L (step S37). The variable L is a variable for storing randomly extracted line numbers. The CPU 11 sets the loop variable j to 1 (step S38). The CPU 11 stores BASEDATA (i, j) in DATA (L, j) (step S39). DATA () is an array stored in the master table T7. That is, the CPU 11 stores the element in the i row and j column of the overwrite table T6 in the L row and j column of the master table T7.

  The CPU 11 increments the loop variable j by 1 (step S40). The CPU 11 determines whether or not the loop variable j exceeds NUM_R (step S41). When the CPU 11 determines that the loop variable j does not exceed NUM_R (step S41: NO), the CPU 11 returns to step S39 and continues the process. When the CPU 11 determines that the loop variable j exceeds NUM_R (step S41: YES), the CPU 11 increments the loop variable i by 1 (step S42). The CPU 11 determines whether or not the loop variable i exceeds NUM_D (step S43). When the CPU 11 determines that the loop variable i does not exceed NUM_D (step S43: NO), the CPU 11 returns to step S37 and continues the process. If the CPU 11 determines that the loop variable i exceeds NUM_D (step S43: YES), the CPU 11 ends the test data generation process and shifts the process to the correct line number generation process.

  17 to 20 are flowcharts showing an example of the procedure of the correct answer line number generation process. The CPU 11 initializes HIT (a, i) to 0 (step S51). HIT () is an array for storing whether or not the element of the line number i is extracted from the rewrite table T2 in the loop variable a which is a variable indicating the test number. That is, HIT () stores whether or not the extracted data group of line number i is extracted from the data group according to the extraction condition associated with the loop variable a. For example, when HIT (a, i) is 1, it means that the element of the line number i is extracted from the master table T7 according to the extraction condition associated with the test number a. Alternatively, when HIT (a, i) is 0, it means that the element of row number i is not extracted from master table T7 due to the extraction condition associated with test number a.

  The CPU 11 reads the correct answer table T8 (step S52). The CPU 11 sets the loop variable a to 1 (step S53). The CPU 11 reads the combination table T5 (step S54).

  The CPU 11 determines whether or not the a-th row of the type column in the correct answer table T8 is A1 (step S55). If the CPU 11 determines that the a-th row of the type column is A1 (step S55: YES), the CPU 11 stores the a-th row of the correct row number column in the correct answer table T8 in the variable M (step S56). The variable M is a variable for storing the row number of the extracted data group stored in advance in the storage unit 12. The CPU 11 stores the a-th row of the correct column number sequence in the correct table T8 in the variable r (step S57). The variable r is a variable for storing the column number of the extracted data group stored in advance in the storage unit 12. The CPU 11 sets a loop variable i indicating the number of searches to 1 (step S58). The CPU 11 determines whether or not WORK (i, r) is a variable M (step S59). That is, the CPU 11 determines whether or not the row number of the extracted data group stored in advance in the storage unit 12 matches the row number of the data group.

  If the CPU 11 determines that WORK (i, r) is not the variable M (step S59: NO), the CPU 11 increments the loop variable i by 1 (step S60), returns to step S59, and continues the processing. When the CPU 11 determines that WORK (i, r) is the variable M (step S59: YES), it stores 1 in HIT (a, i) (step S61). The CPU 11 stores the number of combinations SU in HIT_SU (i) (step S62), and moves the process to step S80. HIT_SU () is an array for storing the number of the same row number combinations stored in the combination table T5.

  When the CPU 11 determines that the a-th row of the type column in the correct answer table T8 is not A1 (step S55: NO), the CPU 11 determines whether the a-th row of the type column in the correct answer table T8 is A2 (step S63). . The a-th row of the correct answer row number column in the correct answer table T8 is stored in LINE (j) (step S64). LINE () is an array for storing the row numbers to be extracted. The CPU 11 stores the a-th row of the correct answer column number column in the correct answer table T8 in the variable r (step S65). The CPU 11 sets the loop variable j to 1 (step S66).

  The CPU 11 sets the loop variable i to 1 (step S67). The CPU 11 determines whether WORK (i, r) is the same as LINE (j) (step S68). That is, the CPU 11 determines whether or not the row number stored in the r column of the i row of the rewrite data matches the row number extracted in the j column. If the CPU 11 determines that WORK (i, r) is not the same as LINE (j) (step S68: NO), the CPU 11 increments the loop variable i by 1 (step S69), returns to step S68, and continues the processing. When the CPU 11 determines that WORK (i, r) is the same as LINE (j) (step S68: YES), 1 is stored in HIT (a, i) (step S70). That is, HIT () stores whether or not the extracted data group of line number i is extracted from the data group according to the extraction condition associated with the loop variable a. The CPU 11 stores the number of combinations SU in HIT_SU (i) (step S71). That is, the CPU 11 stores the same row number combination of the counted row numbers i in HIT_SU (i) as the number of extracted data groups (first data group).

  The CPU 11 increments the loop variable j by 1 (step S72). The CPU 11 determines whether or not the loop variable j exceeds NUM_R (step S73). If the CPU 11 determines that the loop variable j has not exceeded NUM_R (step S73: NO), the CPU 11 returns to step S67 and continues the process. If the CPU 11 determines that the loop variable j exceeds NUM_R (step S73: YES), the process proceeds to step S80.

  When the CPU 11 determines that the a-th row of the type column in the correct answer table T8 is not A2 (step S63: NO), the CPU 11 stores the row number combination to be extracted in ROW (1, 2... NUM_R) (step S74). ROW () is an array for storing row number combinations, and column numbers are stored in the array index. For example, (1, 1, 1) and the like are stored in ROW (1, 2... NUM_R). The CPU 11 sets the loop variable i to 1 (step S75). The CPU 11 determines whether WORK (i, 1, 2... NUM_R) is the same as ROW (1, 2... NUM_R) (step S76). That is, the CPU 11 determines whether or not the line number combination stored in the i line of the rewrite data matches the extracted line number combination.

  When the CPU 11 determines that WORK (i, 1, 2... NUM_R) is not the same as ROW (1, 2... NUM_R) (step S76: NO), the CPU 11 increments the loop variable i by 1 (step S77). Returning to step S76, the processing is continued. When the CPU 11 determines that WORK (i, 1, 2... NUM_R) is ROW (1, 2... NUM_R) (step S76: YES), 1 is stored in HIT (a, i) (step S78). ). The CPU 11 stores the number of combinations SU in HIT_SU (i) (step S79), and moves the process to step S80.

  The CPU 11 increments the loop variable a by 1 (step S80). The CPU 11 determines whether or not the loop variable a has exceeded TEST_NUM indicating the total number of test numbers stored in the correct answer table T8 (step S81). If the CPU 11 determines that the loop variable a has not exceeded TEST_NUM (step S81: NO), the process proceeds to step S54. When the CPU 11 determines that the loop variable a exceeds TEST_NUM (step S81: YES), the CPU 11 sets the loop variable i to 1 (step S82). The CPU 11 sets the loop variable a to 1 (step S83).

  The CPU 11 sets the extraction number WL indicating the number of rows to be extracted from the rewrite table T2 to 0 (step S84). The number of extractions WL indicates the number of times that the CPU 11 has extracted the extraction data group (first data group) of row number i. The CPU 11 determines whether or not HIT (a, i) is 1 (step S85). If the CPU 11 determines that HIT (a, i) is 1 (step S85: YES), the CPU 11 increments the number of extractions WL by 1 (step S86), and moves the process to step S87. That is, the CPU 11 determines whether or not HIT (a, i) is 1, and when it is determined that HIT (a, i) is 1, the CPU 11 stores the number of extractions WL in the storage unit 12 by increasing it. The number of row numbers of the data group that matches the row number of the extracted data group (first data group) is counted. When the CPU 11 determines that HIT (a, i) is not 1 (step S85: NO), the CPU 11 increases the loop variable a by 1 (step S87). HIT_SUM (a) × number of extractions WL is stored in HIT_SUM (a, i) (step S88). HIT_SUM () is an array that stores the number of extracted data groups extracted from the data group. That is, the CPU 11 multiplies the number of extraction data groups (first data group) by the same combination of row numbers, thereby calculating the number of row numbers of the counted data groups and the first data group stored in the storage unit 12. Count the sum of the line number and the number of line numbers that matched. The CPU 11 determines whether or not the loop variable a exceeds TEST_NUM (step S89).

  If the CPU 11 determines that the loop variable a has not exceeded TEST_NUM (step S89: NO), the process proceeds to step S85. If the CPU 11 determines that the loop variable a exceeds TEST_NUM (step S89: YES), the CPU 11 increments the loop variable i by 1 (step S90). The CPU 11 determines whether i exceeds the total number of combinations (step S91). If the CPU 11 determines that i has not exceeded NUM_D (step S91: NO), the process proceeds to step S83. When the CPU 11 determines that i exceeds the total number of combinations (step S91: YES), it sets the loop variable a to 1 (step S92).

  The CPU 11 sets the loop variable i to 1 (step S93). The CPU 11 sets the correct line number WK indicating the number of extracted lines estimated for each test number from the master table T7 to 0 (step S94). The CPU 11 adds HIT_SUM (a, i) to the correct answer line number WK (step S95). That is, the CPU 11 counts the sum of each estimated extraction data group. The CPU 11 increments the loop variable i by 1 (step S96). The CPU 11 determines whether or not the loop variable i has exceeded the total number of combinations (step S97). If the CPU 11 determines that the loop variable i has not exceeded the total number of combinations (step S97: NO), the process proceeds to step S95. If the CPU 11 determines that the loop variable i has exceeded the total number of combinations (step S97: YES), the CPU 11 stores the correct line number WK in SEIKAI (a) (step S98).

  The CPU 11 increments the loop variable a by 1 (step S99). The CPU 11 determines whether or not the loop variable a exceeds TEST_NUM (step S100). If the CPU 11 determines that the loop variable a does not exceed TEST_NUM (step S100: NO), the process proceeds to step S93. When the CPU 11 determines that the loop variable a exceeds TEST_NUM (step S100: YES), the CPU 11 ends the correct line number generation process and shifts the process to the test result determination process.

  21 to 22 are flowcharts showing an example of the procedure of the test result determination process. The CPU 11 sets the loop variable a to 1 (step S111). The CPU 11 reads the correct answer table T8 and extracts (acquires) the line number and the number of lines based on the test item (a) by the extraction program 13P (step S112). The test item () is an array storing extraction conditions associated with the test number a. That is, the CPU 11 extracts the first data group from the data group of the master table T7 by the extraction program 13P according to the first extraction condition associated with the test number a.

  The CPU 11 stores the extracted number of rows in the number of extracted cases (a) (step S113). The CPU 11 determines whether or not the number of extracted cases (a) and SEIKAI (a) are the same (step S114). That is, the CPU 11 determines whether or not they are the same by comparing the number of extracted rows that compares the number of extracted data groups with the sum of the estimated number of data groups and the number of correct rows. When the CPU 11 determines that the number of extracted cases (a) and SEIKAI (a) are not the same (step S114: NO), it stores NG in the determination (a) (step S115). The CPU 11 stores the loop variable a in the test number K (step S116) and ends the process.

  If the CPU 11 determines that the number of extracted cases (a) and SEIKAI (a) are the same (step S114: YES), it stores OK in the determination (a) (step S117). The extracted row number element is added to the last row of the master table T7 (step S118). The CPU 11 reads the correct answer table T8 and extracts the line number and the number of lines based on the test item (a + 1) (step S119). That is, the CPU 11 extracts the second data group from the data group of the master table T7 according to the second extraction condition associated with the test number a + 1.

  The CPU 11 stores the extracted number of rows in the number of extracted cases (a + 1) (step S120). The CPU 11 determines whether or not the number of extracted cases (a + 1) is the same as SEIKAI (a + 1) (step S121). That is, the CPU 11 determines whether or not the extracted number of the second data group matches the added data group obtained by adding the estimated number of the first estimated data group and the second estimated data group. When the CPU 11 determines that the number of extracted cases (a + 1) and SEIKAI (a + 1) are not the same (step S121: NO), the CPU 11 stores NG in the determination (a + 1) (step S122). The CPU 11 stores the loop variable a + 1 in the test number K + 1 (step S123) and ends the process.

  If the CPU 11 determines that the number of extractions (a + 1) and SEIKAI (a + 1) are the same (S121: YES), it stores OK in the determination (a + 1) (step S124). The CPU 11 increments the loop variable a by 1 (step S125). The CPU 11 determines whether or not the loop variable a exceeds TEST_NUM (step S126). If the CPU 11 determines that the loop variable a has not exceeded TEST_NUM (step S126: NO), the process proceeds to step S118. If the CPU 11 determines that the loop variable a exceeds TEST_NUM (step S126: YES), the CPU 11 ends the test result determination process and ends the process.

  In the present embodiment, by determining whether or not the number of lines extracted from the work table T3 by the CPU 11 is the same as the number of correct answer lines, the test result validity determination process can be performed in a short time.

  In the present embodiment, the CPU 11 determines whether or not WORK (i, r) is a variable M. With this, the process of determining the validity of the test result is performed depending on whether or not the character strings match. it can.

  In this embodiment, the CPU 11 determines whether WORK (i, r) is the same as LINE (j). As a result, it is possible to perform a test result validity determination process based on whether or not a part of the character string matches.

  In this embodiment, the CPU 11 determines whether or not WORK (i, (1, 2... NUM_R)) is the same as ROW (1, 2... NUM_R). As a result, it is possible to determine whether the test result is valid depending on whether the character string combinations match.

Embodiment 2
Hereinafter, a second embodiment of the present invention will be described in detail with reference to the drawings showing the embodiment. FIG. 23 is a block diagram showing a list of various data tables according to the second embodiment. In the following, the configuration and operation other than those specifically described are the same as those of the first embodiment, and the description is omitted for the sake of brevity. The data table 12T further includes a development table T9.

  FIG. 24 is an explanatory diagram showing an example of the data structure of the expansion table T9. The expansion table T9 is a table that stores combinations of elements in each row in the combination table T5. The expansion table T9 includes a data item column 1, a data item column 2, a data item column 3, and the like. CPU11 produces | generates the expansion | deployment data which show the combination of the element of each line based on the rewriting table T2 and the combination table T5. The CPU 11 generates the expansion table T9 by storing the generated expansion data in the expansion table T9.

  Specifically, an example of processing in which the CPU 11 generates the expansion table T9 is as follows. When 1 is stored in the first row of the first column of the combination table T5, the CPU 11 stores “aaa” in the first row of the first column of the rewrite table T2, so that one column of the expansion table T9. “Aaa” is stored in the first line of the eye. When 1 is stored in the first row of the second column of the combination table T5, the CPU 11 stores “Ai” in the first row of the second column of the rewrite table T2, so that the second column of the expansion table T9. “Aiu” is stored in the first line of the eye. When 1 is stored in the first row of the third column of the combination table T5, the CPU 11 stores “Napoleon” in the first row of the third column of the rewrite table T2, so that the third column of the expansion table T9. “Napoleon” is stored in the first line of the eye. The CPU 11 performs the same processing for each row.

  FIG. 25 is a flowchart illustrating an example of a processing procedure of the CPU 11 according to the second embodiment. Processing other than step S7 and step S8 is the same as the processing procedure of the CPU 11 according to the above-described first embodiment, and thus the description is omitted for the sake of brevity.

  After completing the process in step S6, the CPU 11 performs a development table generation process (step S7). The CPU 11 performs a failure location identification process (step S8) and ends the process.

  FIG. 26 is a flowchart illustrating an example of the procedure of the development table generation process. The CPU 11 reads the combination table T5 (step S131). The CPU 11 reads the rewrite table T2 (step S132). Based on the rewrite table T2 and the combination table T5, the CPU 11 generates expanded data indicating the combination of elements in each row (step S133). Specifically, the CPU 11 generates expanded data by storing each element corresponding to the row number of each column of the rewrite table T2 in the row number of each column of the combination table T5. The CPU 11 stores the generated expansion data in the expansion table T9 (step S134).

  FIG. 27 is an explanatory diagram showing an example of the failure location specifying process performed by the CPU. FIG. 27A1 is an explanatory diagram listing elements of correct line numbers for which the line numbers extracted by the CPU 11 in test number 3 are estimated.

  The CPU 11 determines whether or not HIT (a, i) is 1 in order from the test number immediately preceding the test number K. HIT_DATA () is an array that stores combinations of elements with correct line numbers. When the CPU 11 determines that HIT (a, i) is 1, the CPU 11 stores i rows of the decompressed data in HIT_DATA (i). That is, when the CPU 11 determines that HIT (a, i) is 1, the CPU 11 stores i rows of decompressed data in HIT_DATA (i).

  The CPU 11 determines whether or not there is an element that matches HIT_DATA (i) in OUT_DATA (a, (1, 2... OUT_NUM (a)). OUT_NUM () is an array for storing the correct line number. (A, (1, 2... OUT_NUM (a)) is an array that stores combinations of extracted row elements. The CPU 11 determines that an element that matches HIT_DATA (i) is OUT_DATA (a, (1, 2... OUT_NUM ( When it is determined not to be in a)), various information is output.

  Specific processing of the CPU 11 is shown below. The CPU 11 does not match the combination “aa, Aiu, Napoleon” of the correct line element in the test number 3 shown in FIG. It is determined that The CPU 11 outputs the combination “aaa, Aiu, Napoleon” and the test number 2 to the output unit 14, which is the correct line number 2, the extracted line number 8, and the correct line.

  28 to 30 are flowcharts showing an example of the procedure of the fault location specifying process. The CPU 11 sets the loop variable a to the number obtained by subtracting 1 from the test number K (step S141). The CPU 11 sets the loop variable i to 1 (step S142). The CPU 11 sets SUM to 0 (step S143). SUM is a variable indicating the number of correct answers.

  The CPU 11 determines whether or not HIT (a, i) is 1 (step S144). If the CPU 11 determines that HIT (a, i) is not 1 (step S144: NO), the process proceeds to step S147. When the CPU 11 determines that HIT (a, i) is 1 (step S144: YES), the CPU 11 stores i row of the expansion table T9 in HIT_DATA (i) (step S145). That is, the CPU 11 stores the i row of the expansion table T9 as a combination of extracted row elements. The CPU 11 increases SUM by SUM + HIT_SUM (a, i) (step S146). The CPU 11 increments the loop variable i by 1 (step S147).

  The CPU 11 determines whether or not the loop variable i exceeds NUM_D (step S148). If the CPU 11 determines that the loop variable i has not exceeded NUM_D (step S148: NO), the process proceeds to step S144. If the CPU 11 determines that the loop variable i exceeds NUM_D (step S148: YES), it generates OUT_DATA (a, (1, 2,... OUT_NUM (a))) based on OUT_NUM (a) and the expanded data ( Step S149). OUT_DATA () is an array for storing the extracted row elements. Specifically, the CPU 11 generates OUT_DATA (a, (1, 2... OUT_NUM (a))) by storing the elements of the expansion table T9 in OUT_NUM (a).

  The CPU 11 sets 1 to the loop variable CL (step S150). The CPU 11 determines whether there is an element in OUT_DATA (a, (1, 2,... OUT_NUM (a)) that matches HIT_DATA (CL) (step S151), that is, the CPU 11 extracts the extracted data group (first data). The CPU 11 determines whether or not the number of the extracted data groups matches the comparison with the comparison, and the CPU 11 determines whether the element that matches HIT_DATA (CL) is OUT_DATA (a, (1, 2,..., OUT_NUM). If it is determined that (a)) is present (step S151: YES), the process proceeds to step S154.

  When the CPU 11 determines that there is no element that matches HIT_DATA (CL) in OUT_DATA (a, (1, 2... OUT_NUM (a)) (step S151: NO), HIT_DATA (CL), HIT_SUM (a, CL), OUT_DATA (a, (1, 2... OUT_NUM (a))) and the loop variable a is output to the output unit 14 (step S152), that is, the CPU 11 performs line number, correct line number, extracted line number, and incorrect extraction. The performed test number is output to the output unit 14. The CPU 11 turns on FLAG (step S153).

  The CPU 11 increases CL by 1 (step S154). The CPU 11 determines whether i exceeds NUM_D (step S155). If the CPU 11 determines that i does not exceed NUM_D (step S155: NO), the process proceeds to step S151. If the CPU 11 determines that i exceeds NUM_D (step S155: YES), it determines whether or not FLAG is ON (step S156). When the CPU 11 determines that the FLAG is ON (step S156: YES), the CPU 11 ends the fault location specifying process and ends the process.

  If the CPU 11 determines that FLAG is not ON (step S156: NO), the CPU 11 decreases the loop variable a by 1 (step S157). The CPU 11 determines whether or not the loop variable a has exceeded the test number k (step S158). If the CPU 11 determines that the loop variable a has not exceeded the test number k (step S158: NO), the process proceeds to step S142. When the CPU 11 determines that the loop variable a has exceeded the test number k (step S158: YES), the CPU 11 ends the failure location specifying process and ends the process.

  In the present embodiment, it is possible to extract test numbers that have been erroneously extracted in a short time.

  In the present embodiment, it is possible to confirm detailed information of a test in which the user has made an erroneous extraction in a short time.

Embodiment 3
Embodiment 3 of the present invention will be described below in detail with reference to the drawings showing the embodiment. FIG. 31 is a block diagram illustrating a hardware group of the information processing apparatus 1 according to the third embodiment. In the following, the configuration and operation other than those specifically described are the same as those of the first embodiment, and the description is omitted for the sake of brevity.

  A program for operating the information processing apparatus 1 is stored in a reading unit 15 such as a disk drive in a portable recording medium 16A such as a CD-ROM, a DVD (Digital Versatile Disc) disk, a memory card, or a USB (Universal Serial Bus) memory. May be read and stored in the storage unit 12. Further, a semiconductor memory 16B such as a flash memory storing the program may be mounted in the information processing apparatus 1. The communication unit 17 is, for example, a wireless LAN card or a mobile phone communication module, and is connected to another server computer via the communication network N. The program can be downloaded from another server computer (not shown) connected by the communication unit 17 via the communication network N such as the Internet. The contents will be described below.

  The information processing apparatus 1 shown in FIG. 31 reads a program for executing the above-described various software processes from the portable recording medium 16A or the semiconductor memory 16B, or another server computer (not shown) via the communication network N. Download from. The program is installed as a program 12P, loaded into the storage unit 12, and executed. This functions as the information processing apparatus 1 described above.

  FIG. 32 is a block diagram illustrating a hardware group of the information processing apparatus 1 according to the third embodiment. When the CPU 11 executes the program 12P, the information processing apparatus 1 operates as follows. The obtaining unit 11a obtains the number of the first data group extracted under the first extraction condition by the extraction program 13P from the data group and the number of the second data group extracted under the second extraction condition from the data group by the extraction program 13P. The estimation unit 11b includes the number of first estimation data groups to be extracted from the data group according to the second extraction condition and the number of second estimation data groups to be extracted from the first data group according to the second extraction condition. And the number of added data groups is estimated. The data determination unit 11c determines whether or not the estimated number of added data groups matches the acquired number of second data groups.

With respect to the embodiments including the above first and second embodiments, the following additional notes are disclosed.
(Appendix 1)
A program that executes processing on a data group extracted by an extraction program that performs extraction processing,
Obtaining the number of first data group extracted under the first extraction condition by the extraction program from the data group and the number of second data group extracted under the second extraction condition by the extraction program from the data group;
The number of first estimation data groups to be extracted from the data group by the second extraction condition and the number of second estimation data groups to be extracted from the first data group by the second extraction condition are added Estimate the number of additional data groups,
A program that causes an information processing apparatus to execute a process of determining whether or not the estimated number of added data groups matches the acquired number of second data groups.
(Appendix 2)
The number of the added data groups is estimated by counting the number of line numbers of the first estimated data group and the second estimated data group stored in advance in the storage unit and the row numbers of the data group. The program according to 1.
(Appendix 3)
The first extraction condition or the second extraction condition is a condition that a character string included in the data group matches a character string to be extracted,
The program according to Supplementary Note 1 or Supplementary Note 2, wherein the first data group or the second data group is a matched character string in the first extraction condition or the second extraction condition.
(Appendix 4)
The program according to any one of appendix 1 to appendix 3, wherein the first extraction condition or the second extraction condition is that a part of a character string included in the data group matches a character string to be extracted.
(Appendix 5)
The first extraction condition or the second extraction condition is that the combination of character strings included in the data group matches the combination of character strings to be extracted,
The program according to any one of Supplementary Note 1 to Supplementary Note 4, wherein the first data group or the second data group is a combination of character strings that match in the first extraction condition or the second extraction condition.
(Appendix 6)
The program according to any one of appendix 1 to appendix 5, which compares the elements of the first data group and the elements of the first estimated data group.
(Appendix 7)
If the elements of the first data group and the elements of the first estimated data group do not match, the line number of the first data group and the line number of the first estimated data group are output. The program according to any one of 1 to appendix 6.
(Appendix 8)
An information processing apparatus that executes processing on a data group extracted by an extraction program that performs extraction processing,
An acquisition unit that acquires a first data group extracted from the data group by the extraction program using the first extraction condition and a second data group extracted from the data group by the extraction program using the second extraction condition;
The number of first estimation data groups to be extracted from the data group by the second extraction condition and the number of second estimation data groups to be extracted from the first data group by the second extraction condition are added An estimation unit for estimating the number of added data groups;
An information processing apparatus comprising: a data determination unit that determines whether or not the estimated number of added data groups matches the acquired number of second data groups.
(Appendix 9)
An information processing method using an information processing apparatus that executes processing on a data group extracted by an extraction program that performs extraction processing,
Obtaining the number of first data group extracted under the first extraction condition by the extraction program from the data group and the number of second data group extracted under the second extraction condition by the extraction program from the data group;
The number of first estimation data groups to be extracted from the data group by the second extraction condition and the number of second estimation data groups to be extracted from the first data group by the second extraction condition are added Estimate the number of additional data groups,
An information processing method for determining whether or not the estimated number of added data groups matches the acquired number of second data groups.

  The embodiment disclosed this time is to be considered as illustrative in all points and not restrictive. The scope of the present invention is defined by the terms of the claims, rather than the meanings described above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

11 CPU
12 storage unit 12P control program 13P extraction program 13 input unit 14 output unit T1 random table T2 rewrite table T3 work table T4 count table T5 combination table T6 overwrite table T7 master table T8 correct answer table 12T data table

Claims (5)

A program for executing processing for data group extracted by the extraction program for performing processing for extracting data from a database,
Obtaining the number of data extracted under the second extraction condition from the data group combining the second data group extracted from the first data group under the first extraction condition and the first data group;
The number obtained by adding the number of data to be extracted from the first data group by the second extraction condition and the number of data to be extracted from the second data group by the second extraction condition, and the acquired A program that causes an information processing apparatus to execute processing for determining whether or not the number of data matches. The first extraction condition or the second extraction condition is a condition that a character string included in the data group matches a character string to be extracted,
The program of claim 1, wherein the second data Gunmata is the extracted data group in the second extraction conditions to the data group including a character string that matches in the first extraction condition and the second extraction condition. The program according to claim 1, wherein the first extraction condition or the second extraction condition is that a part of a character string included in the data group matches a character string to be extracted. An information processing apparatus for executing processing for data group extracted by the extraction program for performing processing for extracting data from a database,
An acquisition unit for acquiring the number of data extracted under the second extraction condition from a data group obtained by combining the second data group extracted from the first data group under the first extraction condition and the first data group;
Estimating the number of added data by adding the number of data to be extracted from the first data group under the second extraction condition and the number of data to be extracted from the second data group according to the second extraction condition An estimator to
An information processing apparatus comprising: a data determination unit that determines whether or not the estimated number of addition data matches the number of data acquired by the acquisition unit. An information processing method using an information processing apparatus for executing processing for data group extracted by the extraction program for performing processing for extracting data from a database,
Obtaining the number of data extracted under the second extraction condition from the data group combining the second data group extracted from the first data group under the first extraction condition and the first data group;
Estimating the number of added data by adding the number of data to be extracted from the first data group under the second extraction condition and the number of data to be extracted from the second data group according to the second extraction condition And
An information processing method for determining whether or not the estimated number of added data matches the acquired number of data.

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