JP6954806B2 - Defect detection device and defect detection method - Google Patents

Description

The present invention relates to a defect detection device and a defect detection method.

Patent Document 1 states, "In order to detect similar bugs latent in a plurality of programs sharing data, firstly, the relationship between the program and the latent bug is clarified, and secondly, the program and the latent bug are latent. Clarify the relationship between bugs and data items. "," In a bug detection system that detects potential bugs in multiple programs that share data, a storage means that stores the relationship between each program and the data referenced by them, and It consists of an input means for inputting the relationship between the type of bug and the data in which the bug occurred, and an output means for outputting the relationship between the program and the bug based on the contents of the input content and the storage means. " ing.

Japanese Unexamined Patent Publication No. 11-85563

Software is generally composed of programs and functions that realize multiple functions, and these functions operate while passing data via input / output to a database or file. When creating the source code that realizes each function, the defect is removed by performing debugging (Debug) that detects and corrects the defect (bug) contained in the source code.

Here, in the above-mentioned Patent Document 1, when a defect is detected in the function of referencing or updating a certain data (variable), it is highly possible that the same defect is included by specifying the function of referencing or updating the same data. The function is specified.

However, in Patent Document 1, since the specific value of the data is not considered, for example, the function of referencing or updating another data (variable) having the same value cannot be specified. In addition, it takes time to identify the corrected part because it is not possible to know under what conditions the defect will occur only by identifying the functions and data (variables) related to the defect.

The present invention has been made in view of such a background, and an object of the present invention is to provide a defect detection device and a defect detection method capable of efficiently detecting software defects.

One of the present inventions for solving the above problems is a defect detection device, which includes one or more software specifications including information indicating conditions for input variables and information indicating values of output variables. is information describing the rules, and rule specification, a problem characteristic to be detected, including information representing a pattern of syntactic rule specification, an information storage unit for storing the defect pattern list, and the It is provided with a defect detection unit that collates the rule specification with the defect pattern list and generates a defect occurrence condition list that is information obtained by extracting the rule satisfying the pattern from the rule specification.

In addition, the problems disclosed in the present application and the solutions thereof are described in the column of forms for carrying out the invention.
And the drawings reveal.

According to the present invention, it is possible to efficiently detect software defects.

It is a figure which shows the hardware configuration example of the defect detection apparatus. It is a figure which shows the function which the defect detection apparatus has, and the information which the defect detection apparatus stores. It is a figure which shows the example of the rule specification described in the IF-THEN format. It is a figure which shows the example of the defect pattern list. It is a figure which shows the example of the defect detection result described in the IF-THEN format. It is a flowchart explaining the process of defect detection. It is a figure which shows the example of the rule specification described in the decision table format. It is a figure which shows the example of the defect detection result described in the decision table format.

Hereinafter, embodiments will be described with reference to the drawings. In the following description, the same or similar configurations may be designated by the same reference numerals and duplicate description may be omitted.

[First Embodiment]
FIG. 1 shows the hardware configuration of the defect detection device 100 shown as the first embodiment, and FIG. 2 shows the functions included in the defect detection device 100 and the data stored in the defect detection device 100, respectively.

The defect detection device 100 is an information processing device (computer) used for developing and maintaining software (for example, those related to business such as finance, insurance, manufacturing, distribution, communication, education, medical treatment, etc.). The defect detection device 10 may be realized by using virtual information processing resources such as a cloud server provided by a cloud system.

Software is legal regulations, business rules, standards, etc. regarding products and services. The specifications are determined and designed according to business rules, system rules, check rules, etc. (hereinafter, these are collectively referred to as rules). The above rule is, for example, a description in a natural sentence such as "If ... If ..." or a description according to a predetermined rule that can be interpreted by a computer such as "IF A = 1 AND B = 2 THEN R = 1". It is expressed in various forms such as a description in a decision table that defines the correspondence between conditions and results in a tabular format. Hereinafter, a software specification described as a set of rules is referred to as a rule specification. Rule specifications can be automatically generated from source code by, for example, source code analysis techniques such as symbol execution.

The defect detection device 100 detects defects included in the rule specifications. The defect detection device 100 includes a defect pattern list (defect pattern list 260 described later) including information representing the rule specifications and the characteristics of the defect to be detected by the syntax (syntax) and semantics (semantics) patterns of the rule specifications. ), The rule of the rule specification is collated with the defect pattern list, and the defect detection result (described later) including the information (occurrence condition list) that extracts the rule satisfying the pattern (condition) of the defect pattern list from the rule specification. The defect detection result 270) is generated.

The defect detection results generated by the defect detection device 100 include a defect summary (described later, defect summary 510) indicating the presence or absence of a defect, and a list of detected defects (described later, a list of conditions for occurrence of detected defects 520). Is included.

As shown in FIG. 1, the defect detection device 100 includes a processor 110, a main storage device 120, an auxiliary storage device 130, an input device 140, an output device 150, and a communication device 160. These are communicably connected to each other via a communication means such as a bus (not shown).

The processor 110 is configured by using, for example, a CPU (Central Processing Unit) or an MPU (Micro Processing Unit). When the processor 110 reads and executes the program stored in the main storage device 120, various functions of the defect detection device 100 are realized.

The main storage device 120 is a device that stores programs and data, and is, for example, a ROM (Read Only Memory), a RAM (Random Access Memory), a non-volatile semiconductor memory (NVRAM (Non Volatile RAM)), and the like.

The auxiliary storage device 130 includes, for example, a hard disk drive, an SSD (Solid State Drive), an optical storage device (CD (Compact Disc), DVD (Digital Versatile Disc), etc.),
A storage system, an IC card, a reading / writing device for a recording medium such as an SD memory card or an optical recording medium, a storage area of a cloud server, and the like. Programs and data stored in the auxiliary storage device 130 are read into the main storage device 120 at any time.

The input device 140 is, for example, a keyboard, a mouse, a touch panel, a card reader, a voice input device, or the like. The output device 150 is a user interface that provides the user with various information such as processing progress and processing results. For example, a screen display device (liquid crystal monitor, LCD (Liquid)).
Crystal Display), graphic cards, etc.), audio output devices (speakers, etc.), printing devices, etc. In addition, for example, the defect detection device 100 may be configured to input or output information from another device via the communication device 160.

The communication device 160 is a wired or wireless communication interface that realizes communication with other devices via a communication means such as LAN or the Internet. For example, a NIC (Network Interface Card), a wireless communication module, or the like. USB (Universal Serial Interface) module, serial communication module, etc.

As shown in FIG. 2, the defect detection device 100 includes the functions of the rule specification generation unit 210, the defect detection unit 220, and the information storage unit 230. Further, the defect detection device 100 stores the source code 240, the rule specification 250, the defect pattern list 260, and the defect detection result 270 in the auxiliary storage device 130.

The rule specification generation unit 210 generates the rule specification 250 from the source code 240 by a source code analysis technique such as symbol execution.

The defect detection unit 220 detects a defect of the rule specification 250 based on a predetermined defect pattern list 260.

The information storage unit 230 stores the result of the defect detection unit 220 detecting the defect of the rule specification 250 as the defect detection result 270 in the auxiliary storage device 130. Details of the processing performed by the defect detection unit 220 will be described later.

FIG. 3 is an example of the rule specification 250 generated by the rule specification generation unit 210 and stored by the information storage unit 230. The rule specification 250 is composed of one or more rule groups grouped by a function identified by an identifier (hereinafter referred to as a function ID). In the following description, each function is described as function 1, function 2, .... Each rule group contains one or more rules described in IF-THEN format. Each rule is identified by an identifier (hereinafter referred to as a rule ID). Hereinafter, the above rule group is also referred to as a rule set.

The rule specification 250 shown in the figure includes three rule sets: a rule set 310 for function 1, a rule set 320 for function 2, and a rule set 330 for function 3. Of these, the rule set 310 includes four rules having rule IDs 1 to 4. Further, the rule set 320 includes three rules of rule IDs 1 to 3. Further, the rule set 330 includes two rules having rule IDs 1 and 2. In the following description, each rule is described as rule 1, rule 2, ....

Each rule includes a condition part and a result part. In the IF-THEN format description, the condition part and the result part correspond to the IF clause and the THEN clause, respectively. For example, in the case of rule 1 of the rule set 310 illustrated in FIG. 3, the condition part is “p = 1 and q> r” and the result part is “x = 1”.

In the following description, for each rule set, the variable described in the condition part of the rule included in the rule set is referred to as an input variable, and the variable described in the result part is referred to as an output variable. For example, in the rule set 310 illustrated in FIG. 3, the input variables are p, q, r and the output variables are x.

When the specific value of the input variable is defined in each rule set, it is uniquely determined whether the condition part of each rule is satisfied (whether the logical expression of the condition part is true). When the condition part of the rule is satisfied, the value of the output variable is determined so that the result part of the rule is true. For example, in the rule set 310 illustrated in FIG. 3, when the specific values of the input variables p, q, and r are 1, 2, and 3, respectively, the condition part of the rule 2 is satisfied, and the specific output variable x is specified. Value is set to 2.

For example, in the rule specification 250, when two functions pass data via input / output to a database, a file, or the like, the output variable of one rule set is included in the input variable of the other rule set. For example, in the rule specification 250 illustrated in FIG. 3, the output variable x of the rule set 310 of the function 1 is included in the input variable of the rule set 320 of the function 2. This means that function 1 writes the value of the variable x to a database or file, and function 2 reads the value of the variable x from the same database or file and refers to it. In the following, among multiple functions that read and write the same variable, the function that has the variable as the output variable of the rule set is referred to as the "output side function", and the function that has the variable as the input variable of the rule set is referred to as the "input side function". ..

For the two functions, when the output variable of one rule set and the input variable of the other rule set are different, the information on the correspondence between the input variable and the output variable is prepared separately and input / output to the database, file, etc. It may indicate that the data is being passed via. For example, in the rule specification 250 illustrated in FIG. 3, the output variable n of the rule set 330 of the function 3 and the input variable z of the rule set 320 of the function 2 correspond to each other (pointing to the same value on the database or file). It may be expressed that there is data transfer between these functions by another information such as).

FIG. 4 is an example of the defect pattern list 260 stored in the information storage unit 230. The defect pattern list 260 includes information indicating a defect pattern that describes the features of each defect detected by the defect detection device 100. The defect pattern list 260 is created by the user, for example.

The defect pattern list 260 shown in the figure includes a defect pattern 410 of defect A (division by zero) and a defect pattern 420 of defect B (argument invalidity of function f). Each defect pattern is composed of one or more determination conditions having each item of type and conditional expression. Either "syntax" or "meaning" is set for the type. In the conditional expression, a pattern is set in which the defect detection device 100 determines that the rule specification 250 includes a defect. When "syntax" is set for the type, a pattern on the syntax of the rule specification 250 (without considering the specific value set in the variable) is set in the conditional expression. When "meaning" is set for the type, a pattern on the semantics of the rule specification 250 (considering the specific value set in the variable) is set in the conditional expression.

For example, the defect pattern 410 of defect A illustrated in FIG. 4 includes two determination conditions. The first judgment condition is a syntactic pattern, and the conditional expression is "appears in an argument (output variable, / 2)". The second determination condition is a semantic pattern, and the conditional expression is "output variable = 0".

The "output variable" described in the conditional expression is a placeholder in which the output variable during the defect determination is stored. In addition, "appearing in argument (expression, function, N)" described in the conditional expression is a function indicating that the expression is syntactically included in the Nth argument passed to the function, and a positive integer is set in N. NS. That is, the conditional expression "appears in the argument (output variable, / 2)" indicates that the output variable is syntactically included in the second argument (divisor) of the function "/" (division). In this example, the placeholder "output variable" and the function "appear in the argument" are used, but it is possible not to use these or to define and use other placeholders and functions. ..

FIG. 5 is an example of the defect detection result 270 generated by the defect detection device 100 based on the rule specification 250 illustrated in FIG. 3 and the defect pattern list 260 illustrated in FIG. The defect detection result 270 includes a defect summary 510 and a list of conditions for generating the detected defects 520. Each line of the defect summary 510 shown in FIG. 5 indicates whether or not each output variable of the rule set in the rule specification 250 includes a defect related to that variable. By referring to the defect summary 510, the user can easily grasp the presence or absence of a defect for each output variable.

The defect summary 510 includes an output variable and the presence / absence of each defect in the defect pattern list 260. One of the output variables of the rule set in the rule specification 250 is set as the output variable. The presence or absence of a defect is set for each defect set in the defect pattern list 260. The defect summary 510 illustrated in FIG. 5 shows that the defect A and the defect B in the defect pattern list 260 are included in the output variable x. Further, regarding the output variables m and n, it is shown that the defect A and the defect B in the defect pattern list 260 are not included. In this example, "●" indicates that there is a defect and "-" indicates that there is no defect, but characters and symbols other than these may be used.

The detected defect occurrence condition list 520 has an output variable indicated to include a defect in the defect summary 510 and a defect occurrence condition for each defect. The detected defect occurrence condition list 520 illustrated in FIG. 5 includes the occurrence condition 530 of the defect A related to the output variable x and the occurrence condition 540 of the defect B related to the output variable x.

Each defect occurrence condition includes a rule that satisfies the defect pattern defined in the defect pattern list 260 among the rules included in the rule specification 250. For example, when the condition part of the rule 4 of the rule set 310 of the function 1 illustrated in FIG. 3 is satisfied, the specific value of the output variable x becomes 0, and the rule 1 or the rule 2 of the rule set 320 of the function 2 becomes 0. Then, the output variable x appears in the divisor of the condition part. That is, with respect to the output variable x, the defect pattern 410 of the defect A illustrated in FIG. 4 is satisfied, and as shown in FIG. 5, the occurrence condition 530 of the defect A regarding the output variable x is the rule 4 of the rule set 310 and the rule. Includes Rule 1 and Rule 2 of Set 320.

The occurrence condition 530 of the defect A related to the output variable x and the occurrence condition 540 of the defect B related to the output variable x shown in FIG. 5 both include rules for a plurality of functions, but are defects that depend on only a single function. In some cases, it is possible to set the condition for occurrence of the defect to be only the rule of the function. For example, the occurrence condition 540 of the defect B relating to the output variable x illustrated in FIG. 5 includes all the rules of the rule set 330 of the function 3 in the rule specification 250 illustrated in FIG. This means that the occurrence condition of the defect B does not depend on the function 3 but depends only on the function 1, and the occurrence condition 540 of the defect B may be only the rule 4 of the rule set 310 of the function 1. ..

In the detected defect occurrence condition list 520, in addition to the defect occurrence condition, an example of specific values of the input variable / output variable that satisfies the defect occurrence condition may be output. For example, regarding the occurrence condition 540 of the defect B related to the output variable x shown in FIG. 5, "p = 2, q = 0, r = 0" as an example of specific values of the input variable and the output variable satisfying the occurrence condition of the defect. , X = 0, n = 1 ”may be output.

FIG. 6 is a flowchart illustrating a process (hereinafter, referred to as a defect detection process S600) performed by the defect detection device 100 when detecting a defect. Hereinafter, the defect detection process S600 will be described with reference to the figure. The defect detection unit 220 starts the defect detection process S600, for example, triggered by an instruction from the user. Further, the defect detection unit 220 automatically executes the defect detection process S600 by batch processing or the like at a scheduled timing, for example. In the following, the letter "S" attached before the code means a processing step.

First, the defect detection device 100 reads the rule specification 250 stored in the information storage unit 230 (S601) and also reads the defect pattern list 260 stored in the information storage unit 230 (S602).

Subsequently, the defect detection device 100 generates a rule pair based on the rule specification 250 read in S601. Here, a rule pair is a rule pair that selects one rule from each of the output side function rule set and the input side function rule set for two functions that transfer data via input / output to a database or file. It is a combination of In the following, the rules selected from the rule set of the output side function will be referred to as "output side rules", and the rules selected from the rule set of the input side functions will be referred to as "input side rules". For example, in the rule specification 250 shown in FIG. 3, the function 1 and the function 2 and the function 1 and the function 3 are a set of an output side function and an input side function that pass the value of the variable x, respectively. Therefore, in the case of this example, the defect detection device 100 has a total of 20 rule pairs, 4 × 3 = 12 from the set of function 1 and function 2, and 4 × 2 = 8 from the set of function 1 and function 3. Generate.

In S603, instead of generating the rule pair directly from the rule specification 250, the defect detection device 100 generates all the pairs of the output side function and the input side function based on the rule specification 250, and then the rule pair is generated from each function pair. May be generated.

Returning to FIG. 6, in S604, the defect detection device 100 executes the processes of S605 to S609 for all the rule pairs generated in S603.

In S605, the defect detection device 100 executes the processes S606 to S609 for all the defects in the defect pattern list 260 read in S602.

In S606, the defect detection device 100 determines whether or not the rule pair currently being processed satisfies the determination condition having the "syntax" as the type in the defect pattern of the defect currently being processed. When the defect detection device 100 has a placeholder "output variable" in the conditional expression of the determination condition, the defect detection device 100 stores the output variable of the output side rule in the rule pair currently being processed in the placeholder and makes a determination. Whether or not the rule pair satisfies the syntactic pattern can be determined by, for example, pattern matching. If the rule pair satisfies all the determination conditions having the "syntax" as the type (S606: YES), the process proceeds to S607, and if not satisfied (S606: NO), the process returns to the loop of S605.

Subsequently, the defect detection device 100 determines whether or not the rule pair currently being processed satisfies the determination condition having "meaning" as the type in the defect pattern of the defect currently being processed (S607). In the case of the rule specification described in the IF-THEN format, whether or not the rule pair satisfies the semantic pattern can be determined by using, for example, an SMT solver (Satisfiability Modulo Theories solver). If the rule pair satisfies all the determination conditions having "meaning" as the type (S607: YES), the process proceeds to S608, and if not (S607: NO), the process returns to the loop of S605.

In this example, the syntactic pattern is determined in S606 and then the semantic pattern is determined in S607, but the order of these processes may be reversed. If it takes time to determine the syntactic pattern, reduce the number of rule pairs that determine the syntactic pattern by first performing the semantic pattern determination process to shorten the defect detection processing time. Can be done.

In S608, the defect detection device 100 records in the defect summary 510 in the defect detection result 270 that the output variable of the output side rule in the rule pair currently being processed includes the defect currently being processed. For example, the defect detection device 100 records “●” in the defect column of the output variable line in the defect summary 510 illustrated in FIG.

In S609, the defect detection device 100 configures the rule pair currently being processed in the detected defect occurrence condition list 520 as the output variable recorded in S608 as containing the defect and the occurrence condition related to the defect. Add two rules. If the same rule is included in the already detected defect occurrence condition list 520, the rule does not have to be added to the detected defect occurrence condition list 520.

As described above, the defect detection device 100 is a software having a function of sharing data via input / output to a database, a file, or the like, based on a rule specification and a defect pattern list, and is a specific value of data. Since defects are detected in consideration of (semantic pattern), software defects can be detected efficiently and reliably. Further, since the defect detection device 100 outputs the occurrence condition of the defect in a clear form as the occurrence condition list 520, the time required for the user to identify the correction part at the time of debugging can be shortened. As described above, according to the defect detection device 100, it is possible to efficiently detect defects in software that operates while passing data. Therefore, the user can efficiently perform work such as identifying a correction part of the software and removing a defect.

[Second Embodiment]
In the first embodiment, the rules included in the rule specification 250 and the defect detection result 270 are described in the IF-THE format, but the defect detection device 100 of the second embodiment describes the rule specification 250 and the defect detection result. The rules contained in each of the 270 are described in a decision table format. The hardware configuration and the basic software configuration of the defect detection device 100 of the second embodiment are the same as those of the defect detection device 100 of the first embodiment. Hereinafter, a configuration different from that of the first embodiment will be mainly described.

FIG. 7 is an example of the rule specification 250 described in the decision table format, which is generated by the rule specification generation unit 210 of the defect detection device 100 of the second embodiment and stored by the information storage unit 230. As shown in the figure, the rule specification 250 includes a rule set 710 of function 1, a rule set 720 of function 2, and a rule set 730 of function 3.

As shown in the figure, each rule set is composed of one or more rule rows including each column of rule ID, condition part, and result part. A column label is attached to each column, a conditional expression is set in the column label of the condition part, and a result variable is set in the column label of the result part. For example, in the case of the rule set 710 in the figure, the condition part of two columns and the result part of one column are included, and p and q> r are added to the label of each column of the condition part, respectively. Is set to x.

The conditional expression set in the column label, the value of the result variable, or the range of values is set in the conditional part and the result part of each rule. In all columns of the conditional part of a rule, when the specific value of the conditional expression is the value set in the rule or the range of values, the conditional part of the rule is satisfied. For example, in rule 1 of the rule set 710 illustrated in FIG. 7, the conditional part is satisfied when the value of the conditional expression p is 1 and the value of the conditional expression q> r is True (true), and the value of the result variable x. Means that is 1. Further, in rule 2 of the rule set 720, the conditional part is satisfied when the value of the conditional expression z is in the range of z> 10 and the value of the conditional expression y / x is other than 2, and the value of the result variable m becomes 2. Means that.

FIG. 8 is an example of the defect detection result 270 generated by the defect detection unit 220 of the defect detection device 100 of the second embodiment based on the rule specification 250 illustrated in FIG. 7 and the defect pattern list 260 illustrated in FIG. be. The defect detection result 270 shown in FIG. 5 corresponds to a decision table format in which each rule of the defect occurrence condition is described in the occurrence condition list 520 in the defect detection result 270 shown in FIG.

The defect detection device 100 of the second embodiment executes the defect detection process S600 in the same manner as the defect detection device 100 of the first embodiment. The defect detection process S600 executed by the defect detection device 100 of the second embodiment is different from the defect detection process S600 in the same manner as the defect detection device 100 of the first embodiment in the following points.

First, in S606, the defect detection device 100 determines whether or not the rule pair currently being processed satisfies the determination condition having the "syntax" as the type in the defect (defect pattern) currently being processed. Whether or not the rule pair satisfies the syntactic pattern is determined by converting the rules included in the rule pair from the decision table format to the IF-THE format and then performing pattern matching in the same manner as in the first embodiment. can do. Further, the conversion from the rule decision table format to the IF-THEN format can be performed, for example, as follows. That is, first, the conditional expression or result variable set in the column label is concatenated with the value set in the corresponding row of the rule by an equal sign (=), or concatenated with the range of values. Then, all the columns of the condition part are connected by a logical product (and) and arranged in the form of "IF condition part THEN result part". Parentheses may be added as appropriate if necessary. For example, when the rule 1 of the rule set 710 illustrated in FIG. 7 is converted into the IF-THE format, it becomes "IF p = 1 and (q> r) = True THEn x = 1".

Further, in S607, the defect detection device 100 determines whether or not the rule pair currently being processed satisfies the determination condition having "meaning" as the type in the defect pattern of the defect currently being processed. Whether or not the rule pair satisfies the semantic pattern can be determined after converting the rule from the decision table format to the IF-THEN format in the same manner as in S606.

In S606 and S607, instead of converting the rule from the decision table format to the IF-THEN format, the rule format may be converted to the IF-THEN format in advance by S601 or the like. Further, the syntactic pattern may be determined in the decision table format without converting to the IF-THEN format in S606.

By making the above changes, the defect detection device 100 outputs the defect occurrence conditions in the decision table format, so that the readability of the defect occurrence conditions is higher than in the IF-THEN format, and the correction location during debugging can be specified. The time required for this can be further reduced.

Although the present invention has been specifically described above based on the embodiments, it goes without saying that the present invention is not limited to the above embodiments and can be variously modified without departing from the gist thereof. No. For example, the above-described embodiment has been described in detail in order to explain the present invention in an easy-to-understand manner, and is not necessarily limited to the one including all the described configurations. Further, it is possible to add / delete / replace a part of the configuration of the above embodiment with another configuration.

Further, each of the above configurations, functional units, processing units, processing means and the like may be realized by hardware by designing a part or all of them by, for example, an integrated circuit. Further, each of the above configurations, functions, and the like may be realized by software by the processor interpreting and executing a program that realizes each function. Information such as programs, tables, and files that realize each function can be placed in a memory, a hard disk, a recording device such as an SSD (Solid State Drive), or a recording medium such as an IC card, an SD card, or a DVD.

Further, in each of the above figures, the control lines and information lines are shown as necessary for explanation, and not all the control lines and information lines in the implementation are necessarily shown. For example, in practice almost all configurations may be considered interconnected.

Further, the arrangement form of the various functional units, the various processing units, and the various databases of the defect detection device 100 described above is only an example. The arrangement form of the various function units, the various processing units, and the various databases can be changed to the optimum arrangement form from the viewpoints of the performance, processing efficiency, communication efficiency, and the like of the hardware and software included in the defect detection device 100.

Further, the above-mentioned configurations of various databases (schema, etc.) can be flexibly changed from the viewpoints of efficient use of resources, improvement of processing efficiency, improvement of access efficiency, improvement of search efficiency, and the like.

100 Defect detection device, 210 Rule specification generator, 220 Defect detection unit, 230 Information storage unit, 240 Source code, 250 Rule specifications, 260 Defect pattern list, 270 Defect detection result, 520 Defect detection condition list, S600 Defect detection process

Claims (13)

A rule specification, which is information that describes a software specification by one or more rules including information indicating a condition for an input variable and information indicating a value of an output variable.
The failure of the features to be detected, including information expressed by the pattern on the syntax of the rule specification, and defect pattern list,
Information storage unit that stores
A defect detection unit that collates the rule specification with the defect pattern list and generates a defect occurrence condition list that is information obtained by extracting the rule that satisfies the pattern from the rule specification.
A defect detection device equipped with. The defect detection device according to claim 1.
The defect pattern list includes information representing the characteristics of the defect to be detected by the semantic pattern of the rule specification.
The defect pattern list is
Includes one or more determination conditions with each item of type and conditional expression
Information indicating whether the judgment condition is a judgment condition in terms of syntax or meaning is set in the type.
In the conditional expression, a pattern for determining that the rule specification includes a defect is set.
Defect detection device. The defect detection device according to claim 1 or 2.
The defect detection unit generates a defect summary which is information indicating the presence or absence of a defect in the output variable.
Defect detection device. The defect detection device according to claim 2.
The defect detection unit
Based on the rule specifications, a plurality of rule pairs that are a combination of the rule that constitutes the function that is the output side of the data and the rule that constitutes the function that is the input side of the data are generated.
The rule pair is collated with the defect pattern list, and the information obtained by extracting the rule pair satisfying the pattern is generated as the defect occurrence condition list.
Defect detection device. The defect detection device according to claim 4.
The defect detection unit determines whether or not the rule pair satisfies the semantic pattern by using an SMT solver (Satisfiability Modulo Theories solver).
Defect detection device. The defect detection device according to any one of claims 1 to 5.
The rule specifications are described in IF-THEN format.
Defect detection device. The defect detection device according to any one of claims 1 to 5.
The rule specifications are described in a decision table format.
Defect detection device. The defect detection device according to any one of claims 1 to 5.
The defect occurrence condition list is described in IF-THEN format.
Defect detection device. The defect detection device according to any one of claims 1 to 5.
The list of conditions for occurrence of the defect is described in a decision table format.
Defect detection device. Information processing device
A rule specification, which is information that describes a software specification by one or more rules including information indicating a condition for an input variable and information indicating a value of an output variable.
The failure of the features to be detected, including information expressed by the pattern on the syntax of the rule specification, and defect pattern list,
Steps to memorize, and
A step of collating the rule specification with the defect pattern list and generating a defect occurrence condition list which is information obtained by extracting the rule satisfying the pattern from the rule specification.
How to detect defects. The defect detection method according to claim 10.
The defect pattern list includes information representing the characteristics of the defect to be detected by the semantic pattern of the rule specification.
The defect pattern list includes one or more judgment conditions having each item of a type and a conditional expression, and the type is set with information indicating whether the judgment condition is a judgment condition for syntax or meaning. Then, in the conditional expression, a pattern for determining that the rule specification includes a defect is set.
Defect detection method. The defect detection method according to claim 10 or 11.
The information processing apparatus further executes a step of generating a defect summary which is information indicating the presence or absence of a defect in the output variable.
Defect detection method. The defect detection method according to claim 11.
The information processing device
Based on the rule specifications, a step of generating a plurality of rule pairs which are a combination of the rule constituting the function of the data output side and the rule constituting the function of the data input side, and the rule pair. And the defect pattern list, and the information obtained by extracting the rule pair satisfying the pattern is generated as the defect occurrence condition list.
How to detect defects.

Images