JP2001243090A - System and method for automatically generating test item and machine readable recording medium with program recorded - Google Patents

Abstract

PROBLEM TO BE SOLVED: To adjust the number of test items to a practicable range for test item candidates obtained by combining information on design related with software to be tested. SOLUTION: A set value deciding means 105 decides a set value being a value to be used for the practice of test for each data defined by design data based on design data inputted from a design data inputting means 101 and a set value deciding instruction inputted from a set value deciding instruction inputting means 103. Then, a combination deciding means 109 decides the combination of the set value of each data defined by the design data based on the set value of each data defined by the design data decided by the set value deciding means 105 and a combination deciding instruction inputted from a combination deciding instruction inputting means 107. A test item generating means 111 generates a test item based on the combination decided by the combination deciding means 109.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an automatic test item generation technology for automatically generating software test items, and more particularly, to a test item automatic generation technology capable of appropriately selecting from a myriad of test item candidates. About.

[0002]

2. Description of the Related Art In software development, a test (test) operation for executing a source program and confirming an operation is indispensable. In order to perform such a test operation, it is necessary to set the content of the operation check to be performed as a test item.

[0003] Japanese Patent Application Laid-Open No. 9-330248 discloses a conventional technique in which test items can be efficiently generated by automating the generation of test items even if the program becomes complicated. The test item generation method described in this publication is intended for a GUI control program, and FIG.
As shown in FIG. 1, the system includes an event registration process 10, a screen layout creation process 11, a judgment condition setting process 12, a test item creation process 13, and a test program creation process 14 stored in the main storage device 1. ing.

[0004] The conventional test item automatic generation system having such a configuration operates as follows. That is, design information (referred to as design information) on the GUI control program is sequentially input by the event input 20, the component pasting 21, and the determination condition input 22, and the event registration process 10 is executed.
By the screen layout creation processing 11 and the judgment condition setting processing 12, the event table 30, the screen file
31. Convert to the judgment condition file 32. Subsequently, from these files, a test item file 33 is automatically generated by a test item generation process 13, and a test program file 34 is automatically generated by a test program generation process 14.

[0005] In this method, test items are automatically generated by the above operation. Even if the GUI control program is complicated and the types of GUI parts and events are increased, the design information is efficiently and without fail. And test item automatic generation.

[0006]

In the conventional system shown in FIG.
In a situation where the combination of GUI components and events in a GUI control program is enormous, when creating test items by combining these pieces of design information by hand, the problem that leakage occurs and that it takes time to create them is taken up as an issue. The problem is solved by automatically generating combinations.

However, in this method, a huge number of combinations obtained as a result of combining a large amount of design information are directly generated as test items, so that the time required for performing the test is enormous, making it difficult to perform the test. Become,
The problem arises. Note that this problem is not specific to GUI control programs, but applies to general software testing.The problem also exists when the conventional method of FIG. 19 is applied to other types of software testing. It becomes.

Japanese Patent Application Laid-Open No. H11-175370 also discloses a technique for automatically generating test items. However, this technique does not include a means for limiting the number of test items to be generated. The same problem as the technique described in Japanese Patent No. 330248 occurs.

[0009]

SUMMARY OF THE INVENTION An object of the present invention is to reduce the number of test items by preparing appropriate selection means for test item candidates obtained by combining design information on software to be tested. The purpose of the present invention is to enable adjustment to be made within a practicable range.

[0010]

In order to achieve the above object, a test item automatic generation system according to the present invention provides design data for inputting design data indicating definitions of a plurality of data that can be input by software to be tested. Setting means for inputting a setting value determination instruction for specifying a value used for test execution or a condition for specifying a value used for test execution for each of the data defined by the design data Determination instruction input means, based on the design data input from the design data input means and the set value determination instruction input from the set value determination instruction input means, to each of the data defined in the design data On the other hand, it is defined by setting value determining means for determining a setting value which is a value to be used for test execution, and is defined by the design data. Combination determination instruction input means for inputting a combination determination instruction for instructing a method of combining data set values, and a set value of each data defined by the design data determined by the set value determination means and the combination determination instruction Combination determining means for determining a combination of set values of each data defined in the design data based on a combination determination instruction input from the input means; and a test item based on the combination determined by the combination determining means. And a test item generating means for generating a test item.

[0011] According to this configuration, the test items are set only for the combinations according to the combination method designated by the combination determination instruction input means, among the combinations of the set values of the data defined by the design data. Since it is generated, the number of test items can be adjusted to a range in which the test can be performed.

Further, the test item automatic generation system of the present invention uses the design data input from the design data input means and the combination determining means in order to efficiently execute a test in accordance with the generated test items. An execution result prediction unit that predicts an execution result for each combination determined by the combination determination unit based on the determined combination; and the test item generation unit includes the generated test item and the execution result. It has a configuration for associating with the execution result for each combination predicted by the result prediction means.

According to this configuration, at the time of test execution, it is possible to compare the actual test result with the predicted execution result, so that the test can be performed more efficiently.

[0014]

Embodiments of the present invention will now be described in detail with reference to the drawings.

Referring to FIG. 1, an automatic test item generation system 1 according to a first embodiment of the present invention includes a design data input means 101, a design data storage means 102, and a set value determination instruction input means 103. , Set value determination instruction storage means 104
Setting value determining means 105, setting value storing means 106, combination determining instruction input means 107, combination determining instruction storing means 108, combination determining means 109, combination storing means 110, test item generating means 111, , Test item storage means 112.

Each of these means operates as follows.

The user uses the design data input means 101 to input design data of the software to be tested (indicating the definitions of a plurality of commands and other data that can be input to the software to be tested). so,
Using the setting value determination instruction input means 103, input a setting value determination instruction indicating a value used for test execution or a condition for specifying a value used for test execution for each data defined by the design data Then, using the combination determination instruction input means 107, a combination determination instruction for instructing a method of combining the set values is input. These input results are stored in the design data storage means 102, the set value determination instruction storage means 104, and the combination determination instruction storage means 108, respectively.

The set value determination means 105 refers to the design data and the set value determination instruction stored in the design data storage means 102 and the set value determination instruction storage means 104, respectively, and sets a set value which is a value to be used for performing a test. Make a decision. The determined set value is stored in the set value storage means 106.

The combination determination means 109 refers to the combination determination instruction and the set value stored in the combination determination instruction storage means 108 and the set value storage means 106, respectively, to determine the combination of the set values. The determined combination is
It is stored in the combination storage means 110.

The test item generating means 111 generates test items by referring to the combinations stored in the combination storing means 110. The generated test items are stored in the test item storage unit 112.

The recording medium K1 is a disk, a semiconductor memory, or another recording medium, and stores a program for causing a computer to function as an automatic test item generation system. This program is read by the computer, and by controlling the operation of the computer, the design data input means 101, the set value determination instruction input means 103, the set value determination means 105, the combination determination instruction input means 107, the combination determination The means 109 realizes the test item generating means 111.

Next, the operation of this embodiment will be described with reference to specific examples.

First, the operation of the design data and design data input means 101 stored in the design data storage means 102 will be described with reference to FIGS.

FIG. 2 shows an example of the design data stored in the design data storage means 102. In the case where software such as a UNIX shell having a command function by text input is to be tested. belongs to. One or more options can be specified for a text-input command, and depending on the type of option, the parameters of the option can be further specified. FIG.
The design data shown in (1) includes an option number, an option name, and a parameter definition for each option given to a command to be input to the software to be tested, and these are stored in the design data storage means 102 in a table format. Here, the parameter definition further includes a parameter presence / absence, and a parameter value range. If the option can specify a parameter, and if so, what range can be specified as its value. Describes information.

FIG. 3 is a flowchart showing a processing example of the design data input means 101. Referring to FIG. 3, the design data input unit 101 first receives the number of command options input by the user (S301). Next, "1" is set to a counter for performing processing for the number of options (S302). It is determined whether or not the value of the counter is equal to or less than the number of options (S303). If Yes, the count value (option number) of the counter is presented to the user, and the option name, parameter presence / absence, and parameter value of the option number The user is prompted to enter a range (S304 to S306). The option name, parameter presence / absence, and parameter value range input by the user are stored in the design data storage unit 102.
(S307). Subsequently, the value of the counter is increased by 1 (S308),
Return to S303. On the other hand, if the determination in S303 is No,
The process ends. Through these processes, the design data as shown in FIG. 2 is stored in the design data storage means 102.

Next, with reference to FIG. 4 and FIG. 5, the operation of the set value determination instruction stored in the set value determination instruction storage means 104 and the operation of the set value determination instruction input means 103 will be described.

FIG. 4 is a diagram showing an example of the set value determination instruction stored in the set value determination instruction storage means 104. FIG.
The setting value determination instruction content shown in (1) includes an option name for designating an option, a value to be set for the option at the time of test execution, and a set of conditions for specifying the value to be set. For example, for option A, two types are specified, one for specifying an option as a value (ON) and one for omitting (OFF) without specifying it. For option B, a fixed value XXX is specified as a value There are two types when omitting without specifying. For Option C, the minimum value (MIN) specified in the parameter value range as the value, and the value obtained by adding 1 to the maximum value (MAX) as well, omitting without specifying If you
(OFF) are specified.

FIG. 5 is a flow chart showing a processing example of the set value determination instruction input means 103. Referring to FIG.
The setting value determination instruction input means 103 first determines whether or not the user has instructed the end of the setting (S501). If the determination result is No, the user is prompted to input an option name and input a setting value determination instruction (such as ON / OFF in FIG. 4) corresponding to the option by displaying an input prompting screen or the like. Prompt (S502, S503). After that, it is checked whether the input from the user is meaningful (S504). If the check result is OK (S505: Yes), the option name input by the user and the setting value determination instruction content are set It is stored in the decision instruction storage means 104 (S506), and the process returns to S501. On the other hand, if it is not OK in S505, the process returns to S503 again. The check in S504 is performed based on, for example, the corresponding optional parameter value range stored in the design data storage unit 102. For example, if a character string that does not relate to an integer value (MIN, MAX, etc., relates to an integer value) is entered for an option whose parameter value range is “integer value between 0 and 20,” an error will occur. judge. If it is determined in S501 that the setting end has been specified, the process ends. As a result, the setting value determination instruction storage means 104 is stored in FIG.
Are stored.

Next, referring to FIGS. 6 and 7, the set value stored in the set value storage means 106 and the set value determination means 10 will be described.
Operation 5 will be described.

FIG. 6 shows the setting values stored in the set value storage means 106 when the contents of the design data storage means 102 and the set value determination instruction storage means 104 are those shown in FIGS. 2 and 4, respectively. FIG. Referring to FIG. 6, option A includes a set value determination instruction “ON / OFF” in FIG.
Are set to "<specified>" and "<omitted>". Here, “<specified>” and “<omitted>” are special parameter values indicating parameter specification and parameter omission. In addition, option B includes FIG.
Set value "X" corresponding to the set value determination instruction "XXX" / OFF
XX "" and "<omitted>" are provided in option C in accordance with the set value determination instruction "MIN / MAX + 1 / OFF" in FIG.
0 ",""21"","<omitted>"are set. Note that the setting values "" 0 "" and "" 21 "" in option C
Is determined not only in the setting value determination instructions “MIN” and “MAX + 1” in FIG. 4 but also in S706 described later using the parameter definition “integer value of 0 to 20” in FIG.

FIG. 7 is a flowchart showing a processing example of the set value determining means 105. Referring to FIG. 7, the setting value determination unit 105 first sets the option number indicating the option to be processed to “1” (S701). Next, by determining whether or not the option number is larger than the number of options, it is determined whether or not all the options have been processed (S702). If the judgment result is No,
The option name and parameter definition corresponding to the option number are respectively extracted from the design data stored in the design data storage means 102 (S703, S704). Further, the contents of the set value determination instruction corresponding to the option name are extracted from the contents stored in the set value determination instruction storage means 104 (S705). Subsequently, the set value determination instruction content of the set value determination instruction is converted into a specific value from the extracted information (S706), and the result is stored in the set value storage means 106 (S707). Next, set the option number to 1.
Increase (S708), and return to S702. Ye in the judgment of S702
If s, the process ends. By the above operation, the set value as shown in FIG. 6 is stored in the set value storage means 106.

Next, with reference to FIGS. 8 and 9, a description will be given of the combination determination instruction stored in the combination determination instruction storage means 108 and the operation of the combination determination instruction input means 107.

FIG. 8 is a diagram showing an example of a combination determination instruction. The combination determination instruction shown in FIG. 8 specifies how to combine the set values for each option. Here, the properties to be satisfied by the selected combination are represented by three logical expressions. For example, the first logical expression indicates that when the set value of the option C is larger than the maximum value, the options A and B are not omitted. In the third logical expression, whether the option A is specified or the value of the option C is “0”
Either of the two must be satisfied. The combination determination instruction is determined in consideration of the characteristics of the software, the importance of each part, the development stage, and the like, and is not limited to the example of FIG. For example, when a certain option is changed or a new option is added, a combination determination instruction that omits other options may be used.

FIG. 9 shows a combination determination instruction input means 107.
9 is a flowchart illustrating an example of the processing of FIG. Referring to FIG. 9, first, the combination determination instruction input unit 107 checks whether or not the user has instructed to end the setting (S90).
1). If the end of the setting has not been instructed (No in S901), the user is prompted to input a combination determination instruction by displaying an input prompting screen or the like (S902). In response to this, when the user inputs a combination determination instruction represented by a logical expression as shown in FIG. 8, the syntax is checked (S903), and if the check result is not OK (S904 is No) Then, the process returns to S902. If the check result is OK (S904: Yes), the input result is stored in the combination determination instruction storage means 108 (S905), and the process returns to S901. If it is determined in S901 that the end of the setting has been instructed (S901: Yes), the process ends. By the above operation, the combination determination instruction as shown in FIG. 8 is stored in the combination determination instruction storage means 108.

Next, with reference to FIGS. 10 and 11, the combinations stored in the combination storage means 110 and the operation of the combination determination means 109 will be described.

FIG. 10 shows a case where the set value and combination determination instruction shown in FIGS. 6 and 8 are stored in the set value storage means 106 and the combination determination instruction storage means 108, respectively. FIG. 3 is a diagram showing combinations stored in storage means 110. FIG.
As shown in the figure, the combination storage means 110 stores all combinations (2
Of the 12 combinations (× 2 × 3 = 12 combinations), only five combinations that satisfy all the combination determination instructions in FIG. 8 are stored. For example, option A is specified and option B
Is "XXX" and the option C is "21", which satisfies all three logical expressions in FIG. 8 and is stored in the combination storage means 110 as shown in FIG. On the other hand, the combination in which all options are omitted is the second combination in FIG.
Since the second logical expression is not satisfied, the combination storage means 11
Not stored in 0.

FIG. 11 is a flowchart showing a processing example of the combination determining means 109. In the processing of FIG. 11, combinations are sequentially generated for each set value stored in the set value storage means 106, and the combination to be generated is referred to by referring to the combination determination instruction stored in the combination determination instruction storage means 108. Is determined whether or not the combination determination instruction is satisfied, and the operation of storing only the combination determination instruction in the combination storage means 110 is performed. Instead of generating combinations for all options,
The efficiency of execution is improved by checking whether or not the partial combination satisfies the combination determination instruction as needed.

Referring to FIG. 11, the combination determining means 10
9 first retrieves a combination determination instruction from the combination determination instruction storage means 108 (S1101), and then retrieves a set value from the set value storage means 106 (S1102). Subsequently, a one-dimensional array N for temporarily storing combinations to be sequentially generated
Is secured and initialized (S1103). This array N has the same number of elements as the number of options, and the first, second,... Elements correspond to the first, second,. Therefore, the setting value storage means 106
If the extracted set values are those shown in FIG. 6, the array N indicates that the first, second, and third elements are the first, second, and third options A, B, respectively. ,
It becomes a one-dimensional array corresponding to C.

After that, the combination determining means 109 outputs a variable M
Is set to “1” (S1104), and the option number M =
Variable N [M] = N representing the number of the set value corresponding to 1
"1" is set to "0" (S1105). Next, the combination means 109 increments the variable N [1] by 1 and sets N [1] = 1 (S1106). That is, “1” indicating the first set value is set in the first element of the array N.

Thereafter, it is checked whether or not the currently selected contents (the first set value <designation> of the first option A) satisfy the restrictions of the combination determination instruction contents (S1111). If the check result is OK (S1112
Is Yes), N [2] = 1, and “1” indicating the first set value is set in the second element of the array N (S1115, S11)
16, S1106). On the other hand, if the check result is not OK (S1112 is No), N [1] = 2 and the first
Set the second element to "2" indicating the second setting value
(S1106). In this example, since S1112 is Yes,
N [2] = 1 (S1115, S1116, S1106).

Thereafter, the combination determining means 109 determines the current selection contents (the first set value <designation> of the first option A and the first set value "XXX" of the second option B). (S1111). In this case, the check result is O
K (Yes in S1112), the combination determination means 109
Is set to N [3] = 1 (S1115, S1116, S1106), and the current selection contents (the first set value <specified> of the first option A and the first set value of the second option B) It is checked whether or not the combination of the third set value “XXX” and the first set value “0” of the third option C) satisfies the constraint (S1111). In this example, the check result is OK (Yes in S1112), and it is determined in S1113 that M is equal to or larger than the number of options.
Combination storage means for selecting contents indicated by array N
It is stored in 110 (S1114). That is, options A, B,
<Specification>, "XXX", "0" as a combination of C setting values
Is stored in the combination storage means 110.

Thereafter, the combination determining means 109
[3] is incremented by 1 to set the first set value of the first and second options and the second set value of the third option.
Select combinations with all the setting values after the
The same processing as described above is performed on the selected combination (S1106, S1107, S1111 to S1116). When the above-described processing is performed on a combination of the first set values of the first and second options and all the set values of the third option (Yes in S1107), N [3 = 0] and M = 3-1 = 2 (S1108, S1109).

Thereafter, N [2] is increased by 1 to "2".
(S1106), the first set value of the first option, the second set value of the second option, and the third
The same processing as the above-described processing is performed for all combinations of the setting values of the second option. Hereinafter, N [2] indicating the number of the setting value of the second option is incremented by one, and the same processing as that described above is performed. And the second
When the processing for all the setting values of the second option is completed (S1107: Yes), N [2] = 0, and M = 2-1
= 1 (S1108, S1109).

Thereafter, N [1] is increased by 1 to "2".
(S1106) The processing described above for the combination of the second set value of the first option, all the set values of the second option, and all the set values of the third option The same processing is performed. Thereafter, N [1] indicating the number of the setting value of the first option is incremented by one, and the same processing as the above-described processing is performed. When the above-described processing is performed on all the setting values of the first option (S1110: Yes), all the combinations have been selected, and the combination determining unit 109 ends the processing.

Next, the operation of the test item stored in the test item storage means 112 and the operation of the test item generation means 111 will be described with reference to FIGS.

FIG. 12 shows a case where the contents of the combination storage means 110 are as shown in FIG.
FIG. 5 is a diagram showing an example of test items stored in the test item. As shown in the figure, the test items are represented in a CSV format (a table format in which data is separated by commas) in a table heading portion and a portion representing each combination.

FIG. 13 is a flowchart showing a processing example of the test item generating means 111. Referring to the figure, the test item generation means 111 first sets the item number to be processed to 1
(S1301), the table heading part is stored in the test item storage means 112 (S1302). Subsequently, it is checked whether or not all combinations have been retrieved from the combination storage means 110 (S
1303), if No, retrieve the next combination (S130
Four) . The item number is stored (S1305) and the combination is stored (S1306) in the test item storage means 112, respectively, and the item number is increased by 1 (S1307), and the process returns to S1303. By the above procedure, test items as shown in FIG. 12 are stored in the test item storage means 112.

Next, a second embodiment of the present invention will be described in detail with reference to the drawings.

FIG. 14 is a block diagram showing a configuration example of a test item automatic generation system 2 according to the second embodiment of the present invention. The automatic test item generation system 2 of the present embodiment is different from the first embodiment in that an execution result predicting unit 201 is added, and a combination storage unit 110, a test item generation unit 111, a test item storage unit 112, and a combination storage instead of the recording medium K1 are provided. It differs from the automatic test item generation system 1 shown in FIG. 1 in that it comprises means 110a, test item generation means 111a, test item storage means 112a, and recording medium K2.

The execution result predicting means 201 includes the design data stored in the design data storing means 102 and the combination storing means.
It has a function of referring to the combinations stored in 110a, predicting an execution result for each combination, and adding the obtained result prediction to the combination. The test item generation unit 111a includes, in addition to the functions of the test item generation unit 111 shown in FIG.
It has the function of storing it in 112a.

The recording medium K2 is a disk, a semiconductor memory, or another recording medium, in which a program for causing a computer to function as an automatic test item generation system is recorded. This program is read by the computer, and by controlling the operation of the computer, the design data input means 101, the set value determination instruction input means 103, the set value determination means 105, the combination determination instruction input means 107, the combination Deciding means 109,
A test item generation unit 111a and an execution result prediction unit 201 are realized.

Next, the operation of this embodiment will be described using a specific example.

First, the operation of the execution result predicting means 201 will be described with reference to FIGS.

FIG. 15 shows an example of a combination obtained by adding the result prediction information to the combination determined by the combination determining means 109. In FIG. 15, as the execution result prediction, whether the option of the command is normal or error in comparison with the parameter definition is added. For example, in the second combination, the parameter of option C has exceeded the maximum value of 20, so an error has occurred, and the other has no violation and is normal.

FIG. 16 is a flowchart showing a processing example of the execution result predicting means 201. Referring to the figure, the execution result prediction means 201 extracts design data from the design data storage means 102 (S1601), and sets a variable N representing a combination number to 1 (S1602). Thereafter, it is determined whether N exceeds the total number of combinations (S1603). If No, the Nth combination is taken out from the combination storage means 110a (S160).
Four) . Based on the design data, it is determined whether the set value of the combination satisfies the parameter existence or non-existence and the parameter value range (S1605, S1606). Add to the combination stored in storage means 110a
(S1607, S1608). After that, N is increased by 1 (S1609),
Return to S1603. If Yes in S1603, the process ends.

Next, the operation of the test item generating means 111a will be described with reference to FIGS.

FIG. 17 shows an example of a test item to which the result prediction is added, which is stored in the test item storage means 112a.
One item is added in the table format, and the result prediction content is described therein.

FIG. 18 is a flowchart showing a processing example of the test item generating means 111a. As shown in the figure, the test item generation means 111a of the present embodiment stores the result prediction in the test item storage means 112a in addition to the processing performed by the test item generation means 111 shown in FIG. 1 (S1801). ). As a result, the figure with the result prediction added
The test item as shown in FIG.
Is stored in

Next, the effect of the present embodiment will be described. In the present embodiment, the prediction of the execution result is added to the combination and added to the test item, so that the content can be compared with the actual execution result at the time of the test, thereby making the test more efficient. It can be implemented effectively.

[0060]

The first effect is that, in the automatic generation of test items, the number of test items to be generated can be adjusted to an executable range. The reason is that the provision of the set value determination instruction input means and the combination determination instruction input means enables the designation of the set value and the combination thereof, and the selection from all the combinations can be performed accordingly. is there.

The second effect is that the selection of the combinations as described above reflects the characteristics of the software, the importance of each part, the status of the development stage, and the like, thereby simply generating a fixed test item automatically. It is possible to generate more optimal test items according to the situation as compared with. The reason is that the provision of the setting value determination instruction input means and the combination determination instruction input means enables the specification of the setting value and the combination thereof to be changed as necessary.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration example of a first embodiment of the present invention.

FIG. 2 is a diagram showing an example of design data stored in a design data storage means 102.

FIG. 3 is a flowchart showing a processing example of a design data input unit 101;

FIG. 4 is a diagram showing an example of a set value determination instruction stored in a set value determination instruction storage means 104.

FIG. 5 is a flowchart showing a processing example of a setting value determination instruction input means 103;

FIG. 6 is a diagram showing an example of a set value stored in a set value storage means 106;

FIG. 7 is a flowchart illustrating a processing example of a setting value determining unit 105;

FIG. 8 is a diagram showing an example of a combination determination instruction stored in a combination determination instruction storage means 108;

FIG. 9 is a flowchart illustrating a processing example of a combination determination instruction input unit 107;

FIG. 10 is a diagram showing an example of combinations stored in a combination storage means 110.

FIG. 11 is a flowchart showing a processing example of a combination determining means 109;

FIG. 12 is a diagram showing an example of test items stored in a test item storage means 112.

FIG. 13 is a flowchart showing a processing example of the test item generation means 111;

FIG. 14 is a block diagram illustrating a configuration example of a second embodiment of the present invention.

FIG. 15 is a diagram showing an example of a combination to which a result prediction is added, which is stored in the combination storage means 110a.

FIG. 16 is a flowchart showing a processing example of an execution result prediction means 201;

FIG. 17 is a diagram showing an example of a test item to which a result prediction is added, which is stored in the test item storage means 112a.

FIG. 18 is a flowchart illustrating a processing example of a test item generation unit 111a.

FIG. 19 is a block diagram of a conventional example.

[Explanation of symbols]

 1, 2 ... test item automatic generation system 101 ... design data input means 102 ... design data storage means 103 ... set value determination instruction input means 104 ... set value determination instruction storage means 105 ... set value determination means 106 ... set value storage means 107 ... combination determination instruction input means 108 ... combination determination instruction storage means 109 ... combination determination means 110, 110a ... combination storage means 111, 111a ... test item generation means 112, 112a ... test item storage means 201 ... execution result prediction means K1, K2 ... recording medium

Claims (6)

[Claims] 1. A design data input means for inputting design data indicating a definition of each of a plurality of data that can be input by software to be tested, and executing a test on each data defined by the design data. Setting value determination instruction input means for inputting a setting value determination instruction for specifying a value to be used for a value or a value to be used for test execution; design data and the set value input from the design data input means Setting value determining means for determining, for each of the data defined in the design data, a setting value that is a value to be used for performing a test, based on the setting value determining instruction input from the determining instruction input means; A combination for inputting a combination determination instruction for instructing a combination method of set values of respective data defined by the design data. A combination determination instruction input means, and the design data based on a set value of each data defined by the design data determined by the set value determination means and a combination determination instruction input from the combination determination instruction input means. And a test item generating means for generating a test item based on the combination determined by the combination determining means. Test item automatic generation system. 2. An execution result for predicting an execution result for each combination determined by the combination determining means based on the design data input from the design data inputting means and the combination determined by the combination determining means. 2. The test according to claim 1, further comprising a prediction unit, wherein the test item generation unit associates the generated test item with an execution result of each combination predicted by the execution result prediction unit. Automatic item generation system. 3. Design data indicating a definition of each of a plurality of data that can be input by software to be tested is input, and for each data defined by the design data, a value used for test execution or A set value determination instruction for specifying a condition for specifying a value to be used for performing a test is input, and is defined in the design data based on the input design data and the input set value determination instruction. Determining a set value that is a value to be used for test execution for each piece of data, and inputting a combination determination instruction instructing a combination method of set values of each data defined by the design data; The design data based on the set value of each data defined in the design data and the input combination determination instruction. In defined to determine the combination of set values of the data it is, test item automatically generating method characterized by generating a test item based on the combination which is the determined. 4. An execution result is predicted for each of the determined combinations based on the input design data and the determined combinations, and the execution is performed for the generated test items and each of the predicted combinations. 4. The automatic test item generation method according to claim 3, wherein the test item is associated with a result. 5. A design data input process for inputting design data indicating a definition of each of a plurality of data that can be input by software to be tested into a computer, and for each data defined by the design data. Setting value determination instruction input processing for inputting a setting value determination instruction for specifying a value to be used for test execution or a value for test execution, and design data input by the design data input processing. A set value for determining a set value that is a value used for test execution for each of the data defined in the design data based on the set value determination instruction input in the set value determination instruction input process A determination process, and a combination determination instructing a combination method of setting values of respective data defined by the design data. A combination determination instruction input process of inputting an instruction; and a set value of each data defined in the design data determined by the set value determination process and a combination determination instruction input by the combination determination instruction input process. In order to execute a combination determination process for determining a combination of set values of each data defined in the design data, and a test item generation process for generating a test item based on the combination determined in the combination determination process. A machine-readable recording medium that records the program. 6. A prediction of an execution result for each combination determined in the combination determination process based on the design data input in the design data input process and the combination determined in the combination determination process. 6. A program according to claim 5, wherein a program for performing an execution result prediction process for performing the following, and associating the generated test item with an execution result for each combination predicted by the execution result prediction process are recorded. Machine-readable recording medium on which is recorded.