Information retrieval device

Abstract

To provide an information retrieval device that can deal with a case of regression.SOLUTION: An information retrieval device includes: a similar problem solution information retrieval part which retrieves similar problem solution information similar to new problem phenomenon information from past problem solution information; a constituent item change information extraction part which extracts past constituent item change information being the changed constituent item information as similar problem solution-time constituent item change information from the similar problem solution information when the past similar problem is solved; a similar problem solution neighborhood constituent item change information extraction part which extracts similar problem solution neighborhood constituent item change information in a neighboring relationship with each other from the similar problem solution-time constituent item change information; and a problem solution information extraction part which extracts constituent item information in a neighboring relationship with the similar problem solution information from the similar problem solution neighborhood constituent item change information, determines the possibility of regression of the corresponding past problem solution information, and outputs the past problem solution information that has the possibility of regression as the similar problem solution neighborhood problem solution information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to an information retrieval device, in particular a software and / or system The present invention relates to an information retrieval device that searches past problem phenomena for the cause of a new problem phenomenon that occurs with a change in the system. [Background technology]

[0002] Software is becoming more and more complex as it becomes more multifunctional. It is also becoming increasingly common for multiple software programs and devices to work together to build a single system, thereby achieving high added value functions.

[0003] In order to reduce the software development costs of products, there is a demand to shorten the software development lead time.

[0004] In particular, in reuse development and derivative development, there is a need to efficiently obtain information about past developments. However, as past information accumulates and becomes larger and more complex, it is becoming more difficult to obtain information efficiently.

[0005] Therefore, for example, when a problem such as a software failure occurs during development, a search mechanism that utilizes artificial intelligence (AI) technology is being considered to efficiently obtain useful information from the vast amount of past problem-solving information.

[0006] For example, Patent Document 1 discloses a method for identifying combinations of small differences that will result in a test failure by using a list of small differences that subdivide the differences between source code that fails a test before the problem occurs and source code that passes the test after the problem occurs, in order to assist in investigating the cause when a new problem occurs.

[0007] At this time, if the cause of the problem is found in the difference information between the test-failed source code and the test-passed source code, this can lead to identification of the cause. [Prior art documents] [Patent documents]

[0008] [Patent Document 1] Patent No. 6903533 Summary of the Invention [Problem to be solved by the invention]

[0009] The technology disclosed in Patent Document 1 cannot deal with cases of regressions in complex systems that are unintentionally caused by changes in the external operating environment or other linked systems.

[0010] An object of the present disclosure is to provide an information search device that can handle regression cases. [Means for solving the problem]

[0011] An information retrieval device that retrieves the cause of a new problem phenomenon that has newly occurred due to a change in software and / or a system from past problem solution information that has been solved in the past and is stored in a storage device, the information retrieval device comprising: a similar problem solution information retrieval unit that retrieves similar problem solution information similar to new problem phenomenon information from the past problem solution information; a configuration item change information extraction unit that extracts past configuration item change information, which is configuration item information that was changed when a similar problem was solved in the past, from the similar problem solution information as similar problem solution-time configuration item change information; a similar problem solution neighboring configuration item change information extraction unit that extracts similar problem solution-time configuration item change information that is in a mutually neighboring relationship from the similar problem solution-time configuration item change information; and a problem solution information extraction unit that extracts configuration item information that is in a neighboring relationship with the similar problem solution information from the similar problem solution neighboring configuration item change information, determines a possibility of regression of the past problem solution information corresponding to the extracted configuration item information, and outputs the past problem solution information that has the possibility of regression as similar problem solution neighboring problem information. Effect of the Invention

[0012] According to the search device of the present disclosure, it is possible to handle cases of regression, and it is possible to improve the probability of providing information that is useful when investigating the cause of a new problem phenomenon and formulating countermeasures. [Brief description of the drawings]

[0013] [Figure 1] 1 is a block diagram showing an overall configuration of an information retrieval device according to a first embodiment of the present disclosure. [Diagram 2] FIG. 13 is a diagram showing an example of an input screen of a new problem phenomenon information input section; [Diagram 3] 13 is a diagram showing past problem solution information stored in a past problem solution information storage unit. FIG. [Figure 4] 13 is a diagram showing similar problem solution information stored in a past problem solution information storage unit. FIG. [Diagram 5] FIG. 13 is a diagram showing a correspondence table used by a configuration item change information extraction unit. [Figure 6] 10 is a diagram showing a schematic diagram of past configuration item change information stored in a past configuration item change information storage unit. FIG. [Figure 7] FIG. 13 is a diagram showing configuration item change information at the time of solving a similar problem stored in a past configuration item change information storage unit. [Figure 8] 13 is a diagram showing similar problem solving vicinity configuration item change information stored in a past configuration item change information storage unit. FIG. [Figure 9] FIG. 13 is a diagram showing a correspondence table used by a problem solving information extraction unit. [Figure 10] 13 is a diagram showing similar problem solving neighboring problem solving information stored in a past problem solving information storage unit. FIG. [Figure 11] 13 is a flowchart illustrating a process in a configuration item change information extraction unit. [Figure 12] 13 is a flowchart illustrating a process in a similar problem solving neighborhood configuration item change information extraction unit. [Figure 13] 13 is a flowchart illustrating a process in a problem solving information extraction unit. [Figure 14] FIG. 11 is a block diagram showing an overall configuration of an information retrieval device according to a second embodiment of the present disclosure. [Figure 15] FIG. 2 is a diagram illustrating a schematic diagram of a process chart input from a process chart input unit. [Figure 16] 13 is a diagram showing similar problem solving neighboring problem solution information and sorted similar problem solving neighboring problem solution information stored in a past problem solution information storage unit. FIG. [Figure 17] 13 is a flowchart illustrating a process in a problem solving information confirmation recommendation sorting unit. [Figure 18] FIG. 11 is a block diagram showing a partial configuration of a modified example of an information retrieval device according to the second embodiment of the present disclosure. [Figure 19] 13 is a flowchart illustrating a process in a problem solving information confirmation recommendation sorting unit. [Figure 20] FIG. 2 is a diagram illustrating a hardware configuration for implementing an information search device according to the first and second embodiments of the present disclosure. [Figure 21] FIG. 2 is a diagram illustrating a hardware configuration for implementing an information search device according to the first and second embodiments of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] <Embodiment 1> Fig. 1 is a block diagram showing the overall configuration of an information retrieval device 1000 according to the first embodiment of the present disclosure. As shown in Fig. 1, the information retrieval device 1000 includes a configuration item change information extraction unit 10, a similar problem solution neighboring configuration item change information extraction unit 20, a problem solution information extraction unit 30, a past problem solution information storage unit 50, a past configuration item change information storage unit 60, a new problem phenomenon information input unit 70, and a similar problem solution information search unit 100.

[0015] The past problem solving information storage unit 50 stores similar problem solving information 51 and similar problem solving neighboring problem solution information 52, and the past configuration item change information storage unit 60 stores similar problem solving time configuration item change information 61 and similar problem solving neighboring problem solution information 62.

[0016] <Similar problem-solving information search section> The similar problem solution information search unit 100 searches the past problem solution information stored in the past problem solution information storage unit 50 for the new problem phenomenon information input from the new problem phenomenon information input unit 70, and extracts the similar problem solution information 51. The new problem phenomenon information is information on a new problem phenomenon that occurs with a change in software and / or system, and Fig. 1 shows an example in which a parameter called a problem phenomenon occurrence process 71 is linked to the new problem phenomenon information.

[0017] More specifically, the similar problem solution information search unit 100 performs morphological analysis on the elements of the new problem phenomenon information acquired from the new problem phenomenon information input unit 70 and the natural sentences contained in the elements of the past problem solution information stored in the past problem solution information storage unit 50, i.e., the information of the problem phenomenon solved in the past, and converts them into word sequences. Then, the word sequences obtained for each element of the new problem phenomenon information and the past problem solution information are compared, and if the degree of agreement, i.e., the degree of sentence similarity, is sufficiently large, the element of the past problem solution information is determined to be similar problem solution information similar to the element of the new problem phenomenon information, and is extracted as similar problem solution information 51.

[0018] For example, if the degree of coincidence is 90%, it is extracted as similar problem solving information 51, and if it is 50%, it is not extracted. Alternatively, if the degree of coincidence is 90% or more, it is extracted, and if it is less than 90%, it is not extracted, but the present invention is not limited to this.

[0019] As described above, by using the morphological analysis, it is possible to relatively easily search past problem solution information and extract similar problem solution information 51.

[0020] 2 is a diagram showing an example of an input screen of the new problem phenomenon information input unit 70. The new problem phenomenon information input from the new problem phenomenon information input unit 70 is a character string representing a newly occurring problem phenomenon, and is input as a search character string for searching for useful information from past problem solution information.

[0021] In the example of Figure 2, "The state of AA does not change when XX process is executed" is entered in the search box for new problem phenomena for past problem solving information. Also, "Y1 process" is selected from the pull-down menu as the process where the problem phenomenon occurs.

[0022] Fig. 3 is a diagram showing past problem solution information stored in the past problem solution information storage unit 50. As shown in Fig. 3, the past problem solution information is composed of a "number (No) column" for identifying a problem that occurred in the past, and a "content column" showing the content and solution information of a similar problem that occurred in the past.

[0023] In the example of Fig. 3, "1357" and "1358" are exemplified as identification numbers, and the content of identification number 1357 is described as "When XXX is executed under conditions BB, an internal error YY occurs and the processing stops" as an example of the problem phenomenon "An error occurs when XXX is executed." Additionally, the content of identification number 1358 is described as "The execution time of XXX processing is ZZ seconds, and the requirements are not met" as an example of the problem phenomenon "The execution time of XXX processing is too long."

[0024] Fig. 4 is a diagram showing similar problem solution information 51 stored in the past problem solution information storage unit 50. As shown in Fig. 4, the similar problem solution information 51 is composed of a "No. column" for identifying problems that occurred in the past, a "search result column" showing the contents and solution information of similar problems that occurred in the past, a "text similarity column" showing the similarity between new problem phenomenon information and the contents described in the "search result column", and a "work process column" showing the process in which the problem occurred.

[0025] The "No. column" and the "search result column" correspond to the "No. column" and the "content column" of the past problem solution information shown in Figure 3, and the "sentence similarity column" indicates the degree of match between the word sequences obtained by the morphological analysis of the natural sentences of each element of the new problem phenomenon information and the past problem solution information performed by the similar problem solution information search unit 100, i.e., the sentence similarity.

[0026] In the example of FIG. 4, the text similarity for identification number 1357 is "0.9" and the work process is "X1 process," while the text similarity for identification number 1358 is "0.85" and the work process is "Y1 process."

[0027] <Component item change information extraction section> The configuration item change information extraction unit 10 reads out similar problem solution information 51 stored in the past problem solution information storage unit 50, and extracts similar problem solving time configuration item change information 61 using the correspondence table 80. The similar problem solving time configuration item change information 61 is information on configuration items that were changed when solving similar problems that occurred in the past. The processing flow in the configuration item change information extraction unit 10 will be explained later.

[0028] 5 is a diagram showing a correspondence table 80 used by the configuration item change information extraction unit 10. The correspondence table 80 used by the configuration item change information extraction unit 10 is a table in which changed configuration item information is associated with each item of past similar problem solution information, and is input in advance to the information retrieval device 1000 and stored in a storage device (not shown).

[0029] In the example of Figure 5, the table associates the "No column" of the similar problem solution information 51 shown in Figure 4 with an identification number (CommitID) that uniquely identifies the "configuration item change information (Commit)" that holds the changed configuration item information.

[0030] The Commit contains data of the configuration item's file before and after the change, and information that indicates the difference between before and after the change. The Commit is read from a storage device (not shown) that stores data related to software or system change work.

[0031] In the example of FIG. 5, CommitID "1234" is associated with identification number 1357, and CommitID "1235" is associated with identification number 1358.

[0032] 6 is a diagram showing the past configuration item change information stored in the past configuration item change information storage unit 60. The past configuration item change information has, for each CommitID described in the correspondence table 80 used by the configuration item change information extraction unit 10, information on configuration items changed in that Commit.

[0033] In the example of Figure 6, the changes in Commit1234 and the changes in Commit7654 are shown by file marks, and in both cases, the changes are shown by hatched file marks. Note that Figure 6 shows only Commit1234 and Commit7654, but this is merely an example.

[0034] Fig. 7 is a diagram showing similar problem solving configuration item change information 61 stored in the past configuration item change information storage unit 60. The similar problem solving configuration item change information 61 holds detailed information of Commits described in the correspondence table 80 used by the configuration item change information extraction unit 10 shown in Fig. 5. In the example of Fig. 7, it holds information on configuration items registered as change information in Commit1234, for example, a group of source codes for implementing software.

[0035] <Similar problem solving neighborhood configuration item change information extraction unit> The similar problem solving vicinity configuration item change information extraction unit 20 reads similar problem solving time configuration item change information 61 stored in the past configuration item change information storage unit 60, and extracts similar problem solving vicinity configuration item change information 62.

[0036] 8 is a diagram showing similar problem solving neighboring configuration item change information 62 stored in the past configuration item change information storage unit 60. Similar problem solving neighboring configuration item change information 62 is information that has a mutually neighboring relationship among the past configuration item change information, and in the example of FIG. 8, a change location 621 of Commit1234 and a change location 622 of Commit7654 are shown as similar problem solving neighboring configuration item change information 62. This indicates that Commit7654 is neighboring Commit1234 of similar problem solving information 51.

[0037] 8, the change location 621 in Commit1234 indicates that the configuration item group a has been changed, and the change location 622 in Commit7654 indicates that the configuration item group b has been changed. The configuration item group a in the change location 621 in Commit1234 and the configuration item group b in the change location 622 in Commit7654 are in a mutually adjacent relationship.

[0038] The similar problem solving nearby configuration item change information extraction unit 20 determines that the configuration items are in proximity to each other when the ratio of configuration items included in the configuration item group a changed in Commit1234 that are also included in the configuration item group b changed in Commit7654 is equal to or greater than a threshold value, and extracts them as similar problem solving nearby configuration item change information 62 that are in a mutually proximal relationship from the past configuration item change information.

[0039] More specifically, as shown in FIG. 6, the configuration items in multiple pieces of past configuration item change information stored in the past configuration item change information storage unit 60 from Commit1234 to Commit7654 are compared in a round-robin manner to calculate the percentage of matching configuration items.

[0040] For example, when a configuration item is "source code for implementing software," there are several possible units of the configuration item, even if it is the same source code, such as "file," "function," and "number of lines." In the case of "function," for example, "the ratio of functions that were also changed in Commit7645 among the functions changed in Commit1234" is calculated, and it is judged whether they are close to each other by comparing with a threshold value. The processing in the similar problem solving nearby configuration item change information extraction unit 20 will be explained further later.

[0041] As described above, by comparing the configuration items of multiple pieces of past configuration item change information in a round-robin manner, similar problem-solving nearby configuration item change information 62 that are in a mutually proximate relationship is extracted, so that more accurate similar problem-solving nearby configuration item change information 62 can be obtained.

[0042] <Problem solving information extraction part> The problem solution information extraction unit 30 reads the similar problem solving neighboring configuration item change information 62 stored in the past configuration item change information storage unit 60 and extracts the similar problem solving neighboring problem solution information 52 using the correspondence table 90.

[0043] 9 is a diagram showing the correspondence table 90 used by the problem solving information extraction unit 30. The correspondence table 90 used by the problem solving information extraction unit 30 is a table in which a "No column" indicating past problem solving information identified as being in the vicinity of the similar problem solving information 51 is associated with a CommitID that uniquely identifies a Commit that holds configuration item information changed to solve a past problem identified as being in the vicinity of the similar problem solving information 51, and is input in advance to the information retrieval device 1000 and stored in a storage device (not shown).

[0044] 9, CommitID "7654" is associated with identification number 5123. CommitID "9876" is associated with identification number 6987.

[0045] Fig. 10 is a diagram showing similar problem solution neighboring problem solution information 52 stored in the past problem solution information storage unit 50. As shown in Fig. 10, the similar problem solution neighboring problem solution information 52 is composed of a No. column 521 indicating past problem solution information identified as the neighbor of the similar problem solution information 51, a regression possibility search result column 522 indicating the possibility of a regression determined to be a regression as the cause of the occurrence of the new problem phenomenon information input from the new problem phenomenon information input unit 70, an influence range similarity column 523 indicating the similarity with the new problem phenomenon information, and an operation process column 524 indicating the operation process in which the similar problem solution neighboring problem occurred.

[0046] Similar problem solution neighboring problem solution information 52 is linked to an element in similar problem solution information 51 whose “No” matches the No column 521 , and the “content column” of the past problem solution information becomes the regression possibility search result column 522 .

[0047] In the example of Figure 10, identification number 5123 is shown as an item that may be a regression causing identification number 1357. In addition, "When ABC is displayed, Japanese characters are garbled" is written as an example of the problem phenomenon "Character display is garbled on screen ABC." The similarity of the scope of influence of this regression is "0.9," and the work process is "Y1 process."

[0048] In addition, the example in Figure 10 shows that another item with the possibility of a regression causing identification number 1357 is identification number 6987. Also, as an example of the problem phenomenon "A communication error occurs in AAA," it is written, "In the case of AAA, a communication error occurs." The similarity of the scope of influence of this regression is "0.85," and the work process is "Z1 process."

[0049] As described above, the similar problem solution neighboring problem solution information 52 is a regression possibility search result that is obtained by searching past problem solution information corresponding to configuration item information that is in a neighboring relationship with the changed configuration item information when a similar problem was solved in the past.

[0050] The similar problem solving neighboring problem solution information 52 is presented to the user of the information retrieval device 1000 by displaying the table shown in Fig. 10 on the screen of an application or a browser, etc. This also applies to the past problem solution information shown in Fig. 3 and the similar problem solution information 51 shown in Fig. 4.

[0051] The determination that the cause of the occurrence of new problem phenomenon information is a regression is made based on the rate at which changed configuration items match in a comparison of changed configuration items in the similar problem solving neighborhood configuration item change information extraction unit 20. For example, if the rate at which changed configuration items match is 90%, it is determined to be a regression, and if it is 50%, it is determined not to be a regression. Alternatively, if the rate at which changed configuration items match is 90% or more, it is determined to be a regression, and if it is less than 90%, it is determined not to be a regression, but the present invention is not limited to this.

[0052] As described above, in the comparison of changed configuration items in the similar problem solution vicinity configuration item change information extraction unit 20, it is possible to judge relatively easily whether the cause of the occurrence of new problem phenomenon information is a regression by judging the matching rate of changed configuration items.

[0053] In addition, to judge whether the similar problem solution information 51 is close to the similar problem solution information, the word sequences obtained for each element of the similar problem solution information 51 and the similar problem solution information 51 are compared using morphological analysis, and if the text similarity is sufficiently large, the similar problem solution information is judged to be close to the similar problem solution information 51. The text similarity judgment criteria used in the similar problem solution information search unit 100 described above can be adopted as the text similarity judgment criteria.

[0054] As described above, by using the morphological analysis, it is possible to relatively easily judge whether the past problem similar problem solving information 51 is in the vicinity of the past problem solving information.

[0055] The similarity of the affected range is the similarity between the new problem phenomenon information input from the new problem phenomenon information input unit 70 and the regression possibility search result, and can be calculated as the degree of agreement between the word sequences obtained by the morphological analysis. By using the morphological analysis, the similarity of the affected range can be obtained relatively easily.

[0056] Fig. 11 is a flowchart explaining the process in the configuration item change information extraction unit 10. As shown in Fig. 11, first, in step S101, the configuration item change information extraction unit 10 reads out the similar problem solution information 51 (Fig. 4) stored in the past problem solution information storage unit 50.

[0057] Next, the configuration item change information extraction unit 10 reads out the correspondence table 80 (FIG. 5) (S102).

[0058] Next, the configuration item change information extraction unit 10 extracts items corresponding to the similar problem solution information from the correspondence table 80, thereby extracting similar problem solving time configuration item change information 61 corresponding to the similar problem solution information (S103), and then terminates the series of processes.

[0059] 12 is a flowchart explaining the processing in the similar problem solving neighborhood configuration item change information extraction unit 20. As shown in FIG. 12, first, in step S201, the similar problem solving neighborhood configuration item change information extraction unit 20 reads out similar problem solving time configuration item change information 61 stored in the past configuration item change information storage unit 60.

[0060] Next, the similar problem solving vicinity configuration item change information extraction unit 20 extracts the change location 622 (FIG. 8) located in the vicinity of the change location 621 (FIG. 8), i.e., the similar problem solving vicinity configuration item change information 622, from the past configuration item change information stored in the past configuration item change information storage unit 60 (step S202), and ends a series of processes.

[0061] Fig. 13 is a flowchart explaining the process in the problem solving information extracting section 30. As shown in Fig. 13, first, in step S301, the problem solving information extracting section 30 reads out the similar problem solving neighboring configuration item change information 622 stored in the past configuration item change information storage section 60.

[0062] Next, the problem solution information extractor 30 reads out the correspondence table 90 (FIG. 9) (S302).

[0063] Next, the problem solving information extraction unit 30 extracts from the correspondence table 90 the item corresponding to the similar problem solution nearby configuration item change information 622 of the similar problem solution nearby configuration item change information 62 stored in the past configuration item change information storage unit 60, in other words, the item with the identification number 5123 in the example of Figure 9, thereby extracting the similar problem solution nearby problem solution information 52 corresponding to the similar problem solution nearby configuration item change information 622 (S303), and then ends the series of processes.

[0064] <Embodiment 2> Fig. 14 is a block diagram showing the overall configuration of an information retrieval device 2000 according to the second embodiment of the present disclosure. As shown in Fig. 2, the information retrieval device 2000 includes a problem-solving information confirmation recommendation sorting unit 40 and a schedule input unit 200 in addition to the configuration of the information retrieval device 1000 shown in Fig. 1, and is configured to store sorted similar problem-solving neighboring problem-solving information 53 in a past problem-solving information storage unit 50. Other components that are the same as those of the information retrieval device 1000 described using Fig. 1 are given the same reference numerals, and duplicated explanations will be omitted.

[0065] As shown in Figure 14, the problem solving information confirmation recommendation sorting unit 40 generates sorted similar problem solving nearby problem solution information 53 sorted in the order recommended for confirmation for solving a new problem based on new problem phenomenon information input from the new problem phenomenon information input unit 70, similar problem solving nearby problem solution information 52 stored in the past problem solution information storage unit 50, and the schedule (work process information) input from the schedule input unit 200.

[0066] Fig. 15 is a diagram showing a schematic diagram of a process schedule input from the process schedule input unit 200. As shown in Fig. 15, the process schedule is such that a "Y1 process" is executed in parallel with and for the same period as consecutive "X1 process" and "X2 process", and further, a "Z1" process, which has the same end period as the "Y1 process", starts to be executed midway through the "Y1 process".

[0067] 16 is a diagram showing similar problem solution neighboring problem solution information 52 and sorted similar problem solution neighboring problem solution information 53 stored in the past problem solution information storage unit 50. As shown in FIG. 16, the sorted similar problem solution neighboring problem solution information 53 is generated by rearranging the similar problem solution neighboring problem solution information 52 based on the schedule input from the schedule input unit 200.

[0068] Fig. 16 shows an example of generating sorted similar problem solving neighboring problem solution information 53 by rearranging the similar problem solving neighboring problem solution information 52 shown in Fig. 10 in a recommended order based on the process chart shown in Fig. 15. Here, an example of the order recommended for confirmation is an algorithm that ranks items with high similarity in the range of influence, that is, the relationship between new problem phenomenon information and the process, in order to rank regressions that are difficult to notice higher, but here, priority is given to items of work processes with low similarity to the work process of new problem phenomenon information. The evaluation of the relationship of the process may be, for example, that the relationship is low when the departments in charge of the process are different, that the relationship is low when the process is related to a derived model rather than the same model, and so on.

[0069] In the example of Figure 16, when the work process in which the problem occurred is Process Y1 and an algorithm is applied which ranks items with low process relevance at the top, the priority of identification number 5123, which is Process Y1 but has a high process relevance, i.e., has an impact range similarity of 0.9, is lowered, and the priority of identification number 6987, which is Process Z1 but has a low process relevance, i.e., has an impact range similarity of 0.85, is raised, so that identification number 6987 has a higher priority in the sorted similar problem-solving nearby problem-solving information 53.

[0070] In this way, by rearranging the similar problem-solving neighboring problem-solving information 52 in an order that is recommended for checking to solve a new problem phenomenon based on the degree of influence range similarity, for example, a regression that is difficult to notice becomes more likely to be checked.

[0071] In addition, by rearranging the similar problem-solving neighboring problem-solving information 52 so that the smaller the degree of influence range similarity is, the higher the ranking is, so that a regression that has a smaller degree of influence range similarity and is difficult to notice is more easily confirmed.

[0072] Fig. 17 is a flowchart explaining the processing in the problem solving information confirmation recommendation sorting unit 40. As shown in Fig. 17, first, in step S401, the problem solving information confirmation recommendation sorting unit 40 reads out similar problem solution neighboring problem solution information 52 (Fig. 10) stored in the past problem solution information storage unit 50.

[0073] Next, the problem solving information confirmation recommendation sorting section 40 reads out the new problem phenomenon information input from the new problem phenomenon information input section 70 (S402).

[0074] Next, the problem solving information confirmation recommendation sorting section 40 reads out the process chart (FIG. 15) inputted from the process chart input section 200 (S403).

[0075] Next, the problem-solving information confirmation recommendation sorting unit 40 generates sorted similar problem-solving neighboring problem-solving information 53 by rearranging the similar problem-solving neighboring problem-solving information 52 in the order recommended for confirmation based on the new problem phenomenon information and the schedule (step S404), and terminates the series of processes.

[0076] <Modification> Fig. 18 is a block diagram showing a partial configuration of a modified example of the information retrieval device 2000 of the second embodiment of the present disclosure. This modified example further includes a cost database 210 required to solve past problems as shown in Fig. 18, and the problem solution information confirmation recommendation sorting unit 40 generates sorted similar problem solution neighboring problem solution information 54 including costs required to obtain similar problem solution neighboring problem solution information 52, instead of generating sorted similar problem solution neighboring problem solution information 53 shown in Fig. 14.

[0077] The cost required to obtain similar problem solving neighboring problem solving information 52 includes, for example, a modification cost 541 required to modify the source code to solve the neighboring problem, and an evaluation cost 542 required to evaluate the operation after the source code is modified.

[0078] Figure 18 shows an example in which similar problem solving neighboring problem solution information 52 shown in Figure 10 is rearranged into a recommended order based on the schedule shown in Figure 15, and correction costs 541 and evaluation costs 542 are read from the cost database 210 required to solve past problems, and added to the items of identification number 5123 and identification number 6987 to generate sorted similar problem solving neighboring problem solution information 54.

[0079] In the example of Figure 18, the item with identification number 6987 has a correction cost 541 of "100 man-hours" and an evaluation cost 542 of "200 man-hours." Also, the item with identification number 512 has a correction cost 541 of "20 man-hours" and an evaluation cost 542 of "50 man-hours."

[0080] Here, "man-hours" is a unit of number of people x time, and represents the amount of work. 1 hour with 100 people, 2 hours with 50 people, and 100 hours with one person all amount to the same "100 man-hours."

[0081] By adding modification cost and evaluation cost as parameters to the algorithm that determines the order in which items are recommended to be checked, and placing items with higher cost at the top, it is possible to raise the priority of more important items.

[0082] Fig. 19 is a flowchart explaining the processing in the problem solving information confirmation recommendation sorting unit 40. As shown in Fig. 19, first, in step S401, the problem solving information confirmation recommendation sorting unit 40 reads out similar problem solution neighboring problem solution information 52 (Fig. 10) stored in the past problem solution information storage unit 50.

[0083] Next, the problem solving information confirmation recommendation sorting section 40 reads out the new problem phenomenon information input from the new problem phenomenon information input section 70 (S402).

[0084] Next, the problem solving information confirmation recommendation sorting section 40 reads out the process chart (FIG. 15) inputted from the process chart input section 200 (S403).

[0085] Next, the problem solving information confirmation recommendation sorting unit 40 reads out the correction cost 541 and the evaluation cost 542 from the past problem solving cost database 210 (S405).

[0086] Next, the problem-solving information confirmation recommendation sorting unit 40 rearranges the similar problem-solving neighboring problem solution information 52 in an order recommended for confirmation based on the new problem phenomenon information and the schedule, and generates sorted similar problem-solving neighboring problem solution information 53 to which a correction cost 541 and an evaluation cost 542 are added (step S406), thereby completing the series of processes.

[0087] Each of the components of the information retrieval devices 1000 and 2000 according to the first and second embodiments described above can be configured using a computer, and is realized by the computer executing a program. That is, the configuration item change information extraction unit 10, the similar problem-solving neighboring configuration item change information extraction unit 20, the problem solving information extraction unit 30, the problem solving information confirmation recommendation sorting unit 40, and the similar problem solving information search unit 100 of the information retrieval devices 1000 and 2000 are realized by, for example, a processing circuit 500 shown in Fig. 20. A processor such as a CPU or a DSP (Digital Signal Processor) is applied to the processing circuit 500, and the functions of each unit are realized by executing a program stored in a storage device.

[0088] Dedicated hardware may also be applied to the processing circuit 500. When the processing circuit 500 is dedicated hardware, the processing circuit 500 corresponds to, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a combination of these.

[0089] The configuration item change information extraction unit 10, similar problem-solving neighboring configuration item change information extraction unit 20, problem solving information extraction unit 30, problem solving information confirmation recommendation sorting unit 40 and similar problem solution information search unit 100 of the information search devices 1000 and 2000 can each have its own function realized by an individual processing circuit, or these functions can be realized together by a single processing circuit.

[0090] 21 shows a hardware configuration in the case where the processing circuit 500 is configured using a processor. In this case, the functions of the configuration item change information extraction unit 10, the similar problem solving neighboring configuration item change information extraction unit 20, the problem solving information extraction unit 30, the problem solving information confirmation recommendation sorting unit 40, and the similar problem solving information search unit 100 of the information retrieval devices 1000 and 2000 are realized by a combination of software, etc. (software, firmware, or software and firmware). The software, etc. are described as a program and stored in the memory 520. The processor 510 functioning as the processing circuit 500 realizes the function of each unit by reading and executing the program stored in the memory 520 (storage device). In other words, it can be said that this program causes a computer to execute the procedure and method of operation of the components of the information retrieval devices 1000 and 2000.

[0091] Here, memory 520 can be, for example, a non-volatile or volatile semiconductor memory such as RAM, ROM, flash memory, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), HDD (Hard Disk Drive), magnetic disk, flexible disk, optical disk, compact disk, mini disk, DVD (Digital Versatile Disc) and its drive device, or any storage medium to be used in the future.

[0092] Moreover, the memory 520 can function as the past problem solving information storage unit 50 and the past configuration item change information storage unit 60 of the information retrieval devices 1000 and 2000 .

[0093] The above describes a configuration in which the functions of each component of the information retrieval devices 1000 and 2000 are realized by either hardware or software, etc. However, the present invention is not limited to this, and some of the components of the information retrieval devices 1000 and 2000 may be realized by dedicated hardware, and other components may be realized by software, etc. For example, it is possible to realize the functions of some of the components by the processing circuit 500 as dedicated hardware, and realize the functions of other components by the processing circuit 500 as the processor 510 reading and executing a program stored in the memory 520.

[0094] As described above, the information retrieval devices 1000 and 2000 can realize the above-mentioned functions through hardware, software, etc., or a combination of these, and by connecting the new problem phenomenon information input unit 70 as a user interface, users can use the information retrieval devices 1000 and 2000.

[0095] In addition, within the scope of the present disclosure, it is possible to freely combine the respective embodiments, and to appropriately modify or omit the respective embodiments.

[0096] The present disclosure described above will now be summarized as an appendix.

[0097] (Appendix 1) An information retrieval device that retrieves a cause of a new problem phenomenon that occurs due to a change in software and / or a system from past problem solving information that has been solved in the past and stored in a storage device, a similar problem solution information search unit that searches for similar problem solution information similar to the new problem phenomenon information from the past problem solution information; a configuration item change information extraction unit for extracting, from the similar problem solution information, past configuration item change information, which is information on configuration items that were changed when a similar problem was solved in the past, as similar problem solution time configuration item change information; a similar problem solving neighboring configuration item change information extraction unit for extracting similar problem solving neighboring configuration item change information having a mutual neighboring relationship from the similar problem solving time configuration item change information; and a problem solution information extraction unit that extracts configuration item information that is in a neighborhood relationship with the similar problem solution information from the similar problem solution neighborhood configuration item change information, determines the possibility of regression of the past problem solution information corresponding to the extracted configuration item information, and outputs the past problem solution information that has the possibility of regression as similar problem solution neighborhood problem solution information.

[0098] (Appendix 2) The information search device described in Appendix 1 further comprises a problem solution information confirmation recommendation sorting unit that generates sorted similar problem-solving neighboring problem solution information by rearranging the similar problem-solving neighboring problem solution information in an order recommended for confirmation in order to solve the new problem phenomenon, based on the similar problem-solving neighboring problem solution information, the new problem phenomenon information, and work process information.

[0099] (Appendix 3) The problem solving information confirmation recommendation sorting unit 3. The information retrieval device according to claim 2, which generates the sorted similar problem-solving neighborhood problem-solving information by adding a correction cost required to solve a past problem and an evaluation cost required to evaluate an operation after the correction.

[0100] (Appendix 4) The similar problem solving information search unit includes: An information retrieval device as described in appendix 1, which performs morphological analysis on natural sentences contained in the past problem solution information and the new problem phenomenon information, converts them into word sequences, compares the word sequences to determine sentence similarity, and determines the similar problem solution information based on the sentence similarity.

[0101] (Appendix 5) The similar problem solving neighborhood configuration item change information extraction unit 2. An information retrieval device according to claim 1, which compares changed configuration items in a plurality of pieces of past configuration item change information in a round-robin manner, determines whether they are in close proximity to each other based on a ratio of matching changed configuration items, and extracts them as the similar problem-solving nearby configuration item change information if they are in close proximity to each other.

[0102] (Appendix 6) The problem-solving information extraction unit The information retrieval device according to claim 1, further comprising: a morphological analysis of natural sentences contained in the past problem solution information and the similar problem solution information, converting the natural sentences into word sequences; comparing the word sequences to determine a sentence similarity; and extracting configuration item information that is in a neighborhood relationship with the similar problem solution information based on the sentence similarity.

[0103] (Appendix 7) The problem-solving information extraction unit 2. An information search device according to claim 1, wherein in the comparison of the changed configuration items in the similar problem solving neighborhood configuration item change information extraction unit, the possibility of the regression is determined based on a matching ratio of the changed configuration items.

[0104] (Appendix 8) The similar problem solving neighborhood problem solving information is an influence range similarity which is a similarity between the past problem solution information having the possibility of regression and the new problem phenomenon information; The problem solving information confirmation recommendation sorting unit 3. The information search device according to claim 2, wherein the similar problem-solving neighboring problem-solving information is rearranged so that the smaller the influence range similarity, the higher the ranking is given to the order in which it is recommended to check for solving the new problem phenomenon.

[0105] (Appendix 9) The problem-solving information extraction unit 9. The information retrieval device according to claim 8, further comprising: performing morphological analysis on natural sentences contained in the past problem solution information and the new problem phenomenon information each having the possibility of regression, converting the natural sentences into word sequences; comparing the word sequences to determine sentence similarity; and determining the sentence similarity as the influence range similarity. [Explanation of symbols]

[0106] 10 configuration item change information extraction unit, 20 similar problem solving nearby configuration item change information extraction unit, 30 problem solving information extraction unit, 40 problem solving information confirmation recommendation sorting unit, 51 similar problem solving information, 52 similar problem solving nearby problem solving information, 53 sorted similar problem solving nearby problem solving information, 61 similar problem solving time configuration item change information, 62 similar problem solving nearby configuration item change information, 100 similar problem solving information search unit, 541 correction cost, 542 evaluation cost.

Claims

1. An information retrieval device that searches for the cause of a new problem phenomenon that has arisen due to a change in software or a system from past problem solution information that has been solved in the past and stored in a storage device, a similar problem solution information search unit that searches for similar problem solution information similar to the new problem phenomenon information from the past problem solution information; a configuration item change information extraction unit that extracts, from the similar problem solution information, past configuration item change information, which is information on configuration items that were changed when a similar problem was solved in the past, as similar problem solution-time configuration item change information; a similar problem solution neighboring configuration item change information extraction unit that extracts similar problem solution neighboring configuration item change information that are in a neighboring relationship with each other from the similar problem solution time configuration item change information; and a problem solution information extraction unit that extracts configuration item information that is in a neighborhood relationship with the similar problem solution information from the similar problem solution neighborhood configuration item change information, determines the possibility of regression of the past problem solution information corresponding to the extracted configuration item information, and outputs the past problem solution information that has the possibility of regression as similar problem solution neighborhood problem solution information.

2. 2. The information search device according to claim 1, further comprising a problem-solving information confirmation recommendation sorting unit that generates sorted similar problem-solving neighboring problem-solving information by rearranging the similar problem-solving neighboring problem-solving information in an order in which confirmation is recommended for solving the new problem phenomenon, based on the similar problem-solving neighboring problem-solving information, the new problem phenomenon information, and the work process information.

3. The problem-solving information confirmation recommendation sorting unit 3. The information retrieval device according to claim 2, wherein the sorted similar problem-solving neighboring problem-solving information is generated by adding a correction cost required to solve a past problem and an evaluation cost required to evaluate an operation after the correction.

4. The similar problem solution information search unit 2. The information retrieval device according to claim 1, wherein natural sentences contained in the past problem solution information and the new problem phenomenon information are converted into word sequences by performing morphological analysis, the word sequences are compared with each other to determine sentence similarity, and the similar problem solution information is determined based on the sentence similarity.

5. The similar problem solving neighborhood configuration item change information extraction unit 2. The information retrieval device according to claim 1, wherein the changed configuration items of the plurality of pieces of past configuration item change information are compared in a round-robin manner, and whether they are in proximity to each other is determined based on a ratio of the changed configuration items that match, and when they are in a proximity relationship to each other, they are extracted as the similar problem-solving nearby configuration item change information.

6. The problem-solving information extraction unit 2. The information retrieval device according to claim 1, wherein natural sentences contained in the past problem solution information and the similar problem solution information are converted into word sequences by performing morphological analysis, the word sequences are compared with each other to determine sentence similarity, and component item information that is in a neighborhood relationship with the similar problem solution information is extracted based on the sentence similarity.

7. The problem-solving information extraction unit 2. The information search device according to claim 1, wherein the possibility of regression is determined based on a matching rate of the changed configuration items in the comparison of the changed configuration items in the similar problem solving neighborhood configuration item change information extraction unit.

8. The similar problem-solving neighborhood problem-solving information is an impact range similarity, which is a similarity between the past problem solution information and the new problem phenomenon information, which may have the regression; The problem-solving information confirmation recommendation sorting unit 3. The information search device according to claim 2, wherein the similar problem-solving neighboring problem-solving information is rearranged so that the smaller the degree of influence range similarity, the higher the ranking is, as an order of recommended confirmation for solving the new problem phenomenon.

9. The problem-solving information extraction unit 9. The information retrieval device according to claim 8, wherein natural sentences contained in the past problem solution information and the new problem phenomenon information each having the possibility of regression are converted into word sequences by performing morphological analysis, the word sequences are compared with each other to determine sentence similarity, and the sentence similarity is set as the influence range similarity.

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