CN105630656A - Log model based system robustness analysis method and apparatus - Google Patents
Log model based system robustness analysis method and apparatus Download PDFInfo
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- CN105630656A CN105630656A CN201410637968.5A CN201410637968A CN105630656A CN 105630656 A CN105630656 A CN 105630656A CN 201410637968 A CN201410637968 A CN 201410637968A CN 105630656 A CN105630656 A CN 105630656A
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Abstract
The present application provides a log model based system robustness analysis method and apparatus. The method comprises: calling a log model library, wherein the log model library comprises log models corresponding to test styles of system logs; acquiring a system log generated in a current robustness test, and matching the system log with the log model library and according to the number of pieces of the system logs matched with each log model, determining robustness of a system. By means of the technical scheme of the present application, the operation amount of the system robustness test can be reduced, and test efficiency and accuracy can be improved.
Description
Technical field
The application relates to technical field of data processing, particularly relates to the system robustness based on daily record model and analyzes method and device.
Background technology
In software system development process, it is required for system is carried out robustness testing (RobustnessTesting), it is also called fault-tolerance test (FaultToleranceTesting), for the test environment of simulating system failure, can automatically recover or run with ignoring fault with checking system.
In the process of robustness testing, the system journal of enormous amount can be generated, and how by the system journal of magnanimity is carried out quick, effectively analyze, to determine the vigorousness situation of system, become solving the technical problem that urgently at present.
Summary of the invention
In view of this, the application provides a kind of system robustness based on daily record model to analyze method and device, it is possible to reduces the operand of system robustness test, promotes testing efficiency and accuracy.
For achieving the above object, the application provides technical scheme as follows:
First aspect according to the application, it is proposed that a kind of system robustness based on daily record model analyzes method, including:
Transferring daily record model library, described daily record model library includes the daily record model corresponding with the text style of system journal;
Obtain the system journal generated in this robustness testing, and mate with described daily record model library;
According to the system journal bar number being matched with each daily record model, it is determined that the vigorousness of system.
Second aspect according to the application, it is proposed that a kind of system robustness analytical equipment based on daily record model, including:
Transferring unit, transfer daily record model library, described daily record model library includes the daily record model corresponding with the text style of system journal;
Matching unit, obtains the system journal generated in this robustness testing, and mates with described daily record model library;
Determine unit, according to the system journal bar number being matched with each daily record model, it is determined that the vigorousness of system.
From above technical scheme, the application is by analyzing the text style of system journal, extract daily record model and set up daily record model library, the system journal of magnanimity can be classified, and every class system journal is carried out aggregate analysis, without analyzing every system journal one by one, significantly reduce the amount of analysis of system journal, contribute to promoting testing efficiency and accuracy.
Accompanying drawing explanation
Fig. 1 is the flow chart of a kind of system robustness analysis method based on daily record model of the application one exemplary embodiment;
Fig. 2 is a kind of schematic diagram analyzing system robustness based on daily record model of the application one exemplary embodiment;
Fig. 3 is a kind of flow chart generating daily record model of the application one exemplary embodiment;
Fig. 4 is the structural representation of a kind of electronic equipment of the application one exemplary embodiment;
Fig. 5 is the block diagram of a kind of system robustness analytical equipment based on daily record model of the application one exemplary embodiment.
Detailed description of the invention
For the application is further described, it is provided that the following example:
Refer to a kind of system robustness based on daily record model that Fig. 1, Fig. 1 are the application one exemplary embodiments and analyze the flow chart of method, the method can comprise the steps:
Step 102, transfers daily record model library, and described daily record model library includes the daily record model corresponding with the text style of system journal.
In the present embodiment, owing to the text style of system journal has certain form, such as only it is made up of constant, or it is made up of constant and variable, then by the text style of system journal is carried out statistical analysis, common portion therein can be extracted, i.e. daily record model. Wherein, when the type of system journal increases, by the analysis to newly-increased system journal, new daily record model is extracted.
In the present embodiment, daily record model can come from management passage, it is also possible to by the analysis of system journal and statistics are extracted automatically.
Step 104, obtains the system journal generated in this robustness testing, and mates with described daily record model library.
In the present embodiment, each robustness testing may relate to one or more systems of same application function, and each system can generate the system journal of correspondence. By the system journal of generation is mated with daily record model library, may identify which out the daily record model belonging to system journal, being equivalent to by the classification to system journal of the daily record model realization, wherein same daily record model can correspond to the system journal from one or more systems.
Step 106, according to the system journal bar number being matched with each daily record model, it is determined that the vigorousness of system.
In the present embodiment, as an exemplary embodiment, same system is under identical application scenarios, if it is properly functioning, then should there is larger fluctuation in the system journal bar number of each daily record model, then the application scenarios that can adopt according to this robustness testing, it is determined that the numerical range of the normal system daily record bar number that each daily record model is corresponding, and the system journal bar number actually generated with this compares, namely can determine that whether the vigorousness of system is normal.
As another exemplary embodiment, by obtaining respectively under same type, simulated failure environment in various degree, it is matched with the system journal bar number of same daily record model, if the vigorousness of system is normal, the system journal bar number then obtained respectively should not have larger fluctuation, namely can determine that the vigorousness situation of system.
By above-described embodiment it can be seen that the application is by setting up daily record model library, it is possible to undertaken the system journal of magnanimity processing based on the classification of daily record model, thus significantly reducing data processing amount, contribute to promoting robustness analysis efficiency; Simultaneously, owing to same system is under same application scene, the system journal quantity produced time properly functioning has concordance, thus the application passes through to add up the system journal quantity that each daily record model is corresponding, namely can determine that whether system is properly functioning, thus accurately obtaining the vigorousness situation of system.
Refer to a kind of schematic diagram analyzing system robustness based on daily record model that Fig. 2, Fig. 2 are the application one exemplary embodiments, describe the process that system robustness is tested by the application:
1, daily record model library is set up
The foundation of daily record model library, is actually the extraction to each daily record model and storage. Wherein, each daily record model is the unification by the text style to a class system journal and abstract, the model statement of " formulaic " that obtain.
Wherein, based on the text style of system journal, it is possible to include following two kinds of forms:
(1) constant (constantsonly) is only comprised
For the system journal of this kind of form, statement only comprises constant, without variable, the daily record statement of such as following selected parts:
�� " SystemA-CLIENT-inquiry system parameter is empty, it is impossible to provide client query, closes client configuration switch "
Therefore, for only comprising the system journal of constant, it is possible to be directly defined as daily record model.
(2) constant and variable (constants+variables) are comprised
For the system journal of this kind of form, statement comprises constant and variable simultaneously, the daily record statement of such as following selected parts:
��SystemB-biz-decision-process-
UserId [2088102002768374], securityId [web | SystemC_payment_3 | 161247a4-48a7-43fd-ac1f-d96b16da4985] executing rule failure "
��SystemB-biz-decision-process-
UserId [2088102002768253], securityId [web | SystemC_payment_3 | 00194db2-3503-4032-8028-2a259b088369] executing rule failure "
In above-mentioned daily record statement, " SystemB-biz-decision-process-userId [] ", " securityId [] executing rule failure " are constant, and " 2088102002768374 ", " 2088102002768253 ", " web | SystemC_payment_3 | 161247a4-48a7-43fd-ac1f-d96b16da4985 " and " web | SystemC_payment_3 | 00194db2-3503-4032-8028-2a259b088369 " are variable; Wherein, " 2088102002768374 " and " 2088102002768253 " are corresponding, and " web | SystemC_payment_3 | 161247a4-48a7-43fd-ac1f-d96b16da4985 " and " web | SystemC_payment_3 | 00194db2-3503-4032-8028-2a259b088369 " is corresponding.
Therefore, for comprising the system journal of constant and variable simultaneously, it is possible to by extracting public constant part, corresponding daily record model is generated.
Visible, by the public constant part of multiple pieces of system daily record is extracted, and variable part is carried out abstract, then the statement that this multiple pieces of system daily record is carried out Unify legislation obtained, i.e. daily record model. In the process analyzing system robustness shown in Fig. 2, after specifically history log being analyzed by " daily record model extraction module " (or other are for realizing module or the equipment of identical function), extract daily record model and constitute daily record model library. Wherein, Fig. 3 is a kind of flow chart generating daily record model of the application one exemplary embodiment, and this flow process can comprise the steps:
Step 302, obtains history log.
In the present embodiment, the system journal that " history log " generates when can be and perform system robustness test in history, by the history log of magnanimity is analyzed, contributes to the type of abundant daily record model, and promote the accuracy of daily record model.
Step 304, is grouped history log.
In the present embodiment, it is possible to make to be grouped in each group obtained the history log comprising predetermined number, then by the history log of each group is compared and analyzed, the common portion of correspondence can be extracted, for obtaining daily record model.
For example, such as history log includes following 4 statements:
A) 2014-08-2012:30:00, the failure of 231SystemB-biz-decision-process-userId [2088102002768374], securityId [web | SystemC_payment_3 | 161247a4-48a7-43fd-ac1f-d96b16da4985] executing rule
B) 2014-08-2012:40:20, the failure of 131SystemB-biz-decision-process-userId [2088102002768253], securityId [web | SystemC_payment_3 | 00194db2-3503-4032-8028-2a259b088369] executing rule
C) 2014-08-2012:42:20,622SystemA-CLIENT-inquiry system parameter is empty, it is impossible to provide client query, closes client configuration switch
D) 2014-08-2012:42:22,523SystemA-CLIENT-inquiry system parameter is empty, it is impossible to provide client query, closes client configuration switch
As an exemplary embodiment, can be dimension according to system name, daily record name and timestamp, above-mentioned 4 history logs are divided into 6 groups, be respectively as follows: (a, b), (a, c), (a, d), (b, c), (b, d) and (c, d).
Step 306, carries out pretreatment to history log.
In the present embodiment, by the pretreatment to history log so that result contributes to computer and performs data analysis more accurately.
In the present embodiment, the pretreatment of history log be may include that the processes such as filtration time stamp, cutting serializing, filtered variable.
I. filtration time stamp
For above-mentioned 4 history logs, timestamp is positioned at the forefront of each bar daily record statement, " 2014-08-2012:30:00,231 " in daily record a, " 2014-08-2012:40:20,131 " in daily record b etc.
Ii. cutting serializing
History log for each group, it is possible to be respectively processed. Wherein, for every history log, according to predefined cutting symbol (such as comma, space etc.), the character in history log can be carried out cutting, thus being a character string (i.e. token sequence) by corresponding history log cutting.
Such as above-mentioned group (a, in b), when history log a being carried out cutting serializing, it is possible to obtain following character string:
[SystemB-biz-decision-process, userId, 2088102002768374, securityId, web | SystemC_payment_3 | 161247a4-48a7-43fd-ac1f-d96b16da4985, executing rule failure]
Iii. filtered variable
Optionally, the character string obtained due to cutting is likely to long, then reduce subsequent calculations amount for abbreviated character sequence, promote the analysis efficiency of history log, variable can be simplified, such as the unification of all of variable is reduced to " (*. ?) " or other identifiers, then the above-mentioned character string corresponding to history log a can be reduced to:
[SystemB-biz-decision-process, userId, (*.?), securityId, (*.?), executing rule failure]
Step 308, for the history log in each group, calculates corresponding longest common subsequence.
In the present embodiment, when the history log in a group all completes pretreatment, after obtaining corresponding character string, can by the character string that history logs all in this group are corresponding be compared, it is determined that common portion.
As an exemplary embodiment, it is possible to adopt LCS (longestcommonsubsequence, longest common subsequence)) algorithm performs above-mentioned comparison operation, the common portion obtained and longest common subsequence. Specifically, such as arbitrary group (m, n), it is assumed that the character string that daily record m, n are corresponding respectively be Xi=[x1, x2 ..., xi] and Yi=[y1, y2 ..., yj], then the longest common subsequence of correspondence can be defined as:
Corresponding to above-mentioned group (a, b), then can obtain corresponding longest common subsequence based on above-mentioned formula is:
[SystemB-biz-decision-process, userId, *, securityId, *, executing rule failure]
And corresponding to above-mentioned group (a, c), then can obtain corresponding longest common subsequence based on above-mentioned formula is:(empty set), it was shown that two history logs do not have common portion.
Step 310, according to the longest common subsequence calculated, extracts daily record model.
In the present embodiment, as an illustrative embodiments, it is possible to directly using the longest common subsequence that obtains as daily record model, as another exemplary embodiment, although at above-mentioned a, b, in the embodiment that c and d is corresponding, longest common subsequence between a (or b) and c (or d) is empty set, but in other cases, also likely to be present the longest common subsequence of nonvoid set, such as one of them or two fields are identical, but this longest common subsequence does not obviously have meaning, thus can pass through in the analysis process of all history logs, the number of times that each longest common subsequence occurs is added up, and when this statistics number is more than or equal to preset times threshold value, just this longest common subsequence is extracted as daily record model.
In the present embodiment, when daily record model is stored to daily record model library, it is also possible to the metadata information that log model is corresponding, the such as system name of correspondence, daily record name, daily record rank are (such as DEBUG, INFO, WARN, ERROR etc.), extraction time etc.
In the present embodiment, as an exemplary embodiment, carry out pretreatment based on to history log, then generate the feature of the processing procedure of longest common subsequence, it is possible under MapReduce framework, perform the extraction to daily record model, to promote treatment effeciency.
2, detection vigorousness
When performing robustness testing every time, obtain the system journal generated, and based on the daily record model library having built up, the system journal generated is identified and classification processes. Ratio is as shown in Figure 2, daily record model identification module (or other are for realizing module or the equipment of identical function) can be passed through by the new daily record (system journal that namely this robustness testing obtains, be different from " history log ") daily record data mate with daily record model library, and add up according to matching result, determine all daily record models being matched, and the new daily record bar number that each daily record model is corresponding, such as table 1 illustrates the statistical result of an exemplary embodiment.
Table 1
In Table 1, the application function performing test comprises multiple system, such as " SystemB " and " SystemC " etc., and each system all matches one or more daily record model, such as system " SystemB " is matched with daily record model " SystemB.pattern0 " and daily record model " SystemB.pattern1 " etc., and system " SystemC " is matched with daily record model " SystemC.pattern0 " and daily record model " SystemC.pattern1 " etc.
Optionally, if there is the new daily record not matching daily record model library, then new daily record model can be extracted according to by this new daily record, to expand daily record model library.
(1) based on the numeric ratio of vigorousness benchmark relatively
As an illustrative embodiments, in the log statistic quantity of each daily record Model Matching that Corpus--based Method obtains, it is determined that during system robustness, it is possible to adopt following processing mode:
According to current application scene, it is determined that the preset reference bar number that each daily record model being matched is corresponding, and according to the system journal bar number in this robustness testing and the comparative result between corresponding described preset reference bar number, so that it is determined that the vigorousness of system.
In the present embodiment, the change of application scenarios during based on each robustness testing, same system is likely to match different daily record bar numbers for identical daily record model, so that determine the preset reference bar number corresponding to current application scene; Wherein, preset reference bar number can be first successful execution corresponding robustness testing time, it is matched with the system journal bar number of each daily record model, or during the corresponding robustness testing of the last successful execution, is matched with the system journal bar number etc. of each daily record model.
Table 2
For example, such as the corresponding application scenarios of table 2 his-and-hers watches 1 and preset reference bar number have supplemented: when current application scene is for " Taobao's transaction creation ", the comparable situation of the daily record bar number that each daily record model being matched is corresponding, the fluctuation ratio of the daily record bar number that such as daily record model " SystemB.pattern0 " mates is 1.20%, and the fluctuation ratio of the daily record bar number that daily record model " SystemC.pattern0 " mates is 101.17%; And by pre-setting acceptable fluctuation ratio, such as 5%, then it is believed that the fluctuation ratio of above-mentioned daily record model " SystemB.pattern0 " is normal, namely system " SystemB " has good vigorousness, and the fluctuation ratio of daily record model " SystemC.pattern0 " is abnormal, i.e. the vigorousness existing problems of system " SystemC ".
Certainly, table 2 is only an exemplary embodiment, it is also possible to system journal (namely above-mentioned new daily record) and daily record model are carried out Information Statistics and the analysis of more various dimensions, the such as rank etc. of the information of daily record model, system journal.
(2) change based on the injection degree of fault
As an illustrative embodiments, in the log statistic quantity of each daily record Model Matching that Corpus--based Method obtains, it is determined that during system robustness, it is possible to adopt following processing mode:
Obtain respectively under same type, simulated failure environment in various degree, be matched with the system journal bar number of same daily record model; When the diversity factor of the system journal bar number corresponding with other simulated failure environment when the system journal bar number that arbitrary simulated failure environment is corresponding is more than or equal to default diversity factor, using the described arbitrary simulated failure environment vigorousness flex point as system. The vigorousness flex point of system is construed as: certain test condition (such as simulated failure environment), and the vigorousness that this system is in this test condition is not enough.
Table 3
As shown in table 3, for the simulated failure " SystemD.consult interface delay " under application scenarios " cashier renders ", implementing failure environment in various degree respectively, such as time delay is 100ms, 200ms ... 500ms etc. For system " SystemC ", under simulated failure environment in various degree, the daily record bar number being matched with daily record model " SystemC.pattern0 " and daily record model " SystemC.pattern1 " would be likely to occur certain change, but for the system that vigorousness is good, intensity of variation should be limited, otherwise illustrates that this system necessarily occurs in that the situation of abnormal running.
Therefore, by under relatively various degrees of failure environment, the daily record bar number corresponding respectively to daily record model " SystemC.pattern0 " and daily record model " SystemC.pattern1 " is known: when time delay is 500ms, the daily record bar number that daily record model " SystemC.pattern0 " is corresponding is 0, with be time delay during 100ms 512, time delay be compared with 409 during 200ms, daily record bar number there occurs acute variation; Meanwhile, when time delay is 500ms, the daily record bar number that daily record model " SystemC.pattern1 " is corresponding is 14, be time delay during 100ms 1234, time delay be compared with 1013 during 200ms, daily record bar number there occurs acute variation. Visible, " SystemD.consult interface delay 500ms " is the vigorousness flex point of corresponding system " SystemC ".
Fig. 4 illustrates the schematic configuration diagram of the electronic equipment of the exemplary embodiment according to the application. Refer to Fig. 4, at hardware view, this electronic equipment includes processor, internal bus, network interface, internal memory and nonvolatile memory, is certainly also possible that the hardware required for other business. Processor reads the computer program of correspondence from nonvolatile memory and then runs in internal memory, forms the system robustness analytical equipment based on daily record model on logic level. Certainly, except software realization mode, the application is not precluded from other implementations, mode of such as logical device or software and hardware combining etc., that is the executive agent of following handling process is not limited to each logical block, it is also possible to be hardware or logical device.
Refer to Fig. 5, in Software Implementation, can should include transferring unit, matching unit and determining unit based on the system robustness analytical equipment of daily record model. Wherein:
Transferring unit, transfer daily record model library, described daily record model library includes the daily record model corresponding with the text style of system journal;
Matching unit, obtains the system journal generated in this robustness testing, and mates with described daily record model library;
Determine unit, according to the system journal bar number being matched with each daily record model, it is determined that the vigorousness of system.
Optionally, legacy system daily record is carried out process by longest common subsequence LCS algorithm and obtains by described daily record model.
Optionally, described legacy system daily record is divided into multiple group, each group comprises the system journal of predetermined number, and the system journal of each group obtains corresponding longest common subsequence by described LCS algorithm process, then the frequency of occurrences is registered as described daily record model more than or equal to the longest common subsequence of predeterminated frequency.
Optionally, it is a character string that every system journal in each group is carried out cutting by the default cutting symbol comprised according to this system journal, and by described LCS algorithm, all character strings of each group is carried out process and obtain corresponding longest common subsequence.
Optionally, also include:
Generate unit, according to the system journal not matching described daily record model library, generate new daily record model;
Adding device, is added into described new daily record model in described daily record model library.
Optionally, described determine unit for:
According to current application scene, it is determined that the preset reference bar number that each daily record model being matched is corresponding;
According to the system journal bar number in this robustness testing and the comparative result between corresponding described preset reference bar number, it is determined that the vigorousness of system.
Optionally, described preset reference bar number includes:
First described in successful execution during robustness testing, it is matched with the system journal bar number of each daily record model;
Or, described in the last successful execution during robustness testing, it is matched with the system journal bar number of each daily record model.
Optionally, described determine unit for:
Obtain respectively under same type, simulated failure environment in various degree, be matched with the system journal bar number of same daily record model;
When the diversity factor of the system journal bar number corresponding with other simulated failure environment when the system journal bar number that arbitrary simulated failure environment is corresponding is more than or equal to default diversity factor, using the described arbitrary simulated failure environment vigorousness flex point as system.
Therefore, the application is by analyzing the text style of system journal, extract daily record model and set up daily record model library, the system journal of magnanimity can be classified, and every class system journal is carried out aggregate analysis, without analyzing every system journal one by one, significantly reduce the amount of analysis of system journal, contribute to promoting testing efficiency and accuracy.
In a typical configuration, computing equipment includes one or more processor (CPU), input/output interface, network interface and internal memory.
Internal memory potentially includes the forms such as the volatile memory in computer-readable medium, random access memory (RAM) and/or Nonvolatile memory, such as read only memory (ROM) or flash memory (flashRAM). Internal memory is the example of computer-readable medium.
Computer-readable medium includes permanent and impermanency, removable and non-removable media can by any method or technology to realize information storage. information can be computer-readable instruction, data structure, the module of program or other data. the example of the storage medium of computer includes, but it is not limited to phase transition internal memory (PRAM), static RAM (SRAM), dynamic random access memory (DRAM), other kinds of random access memory (RAM), read only memory (ROM), Electrically Erasable Read Only Memory (EEPROM), fast flash memory bank or other memory techniques, read-only optical disc read only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tape, the storage of tape magnetic rigid disk or other magnetic storage apparatus or any other non-transmission medium, can be used for the information that storage can be accessed by a computing device. according to defining herein, computer-readable medium does not include temporary computer readable media (transitorymedia), such as data signal and the carrier wave of modulation.
It can further be stated that, term " includes ", " comprising " or its any other variant are intended to comprising of nonexcludability, so that include the process of a series of key element, method, commodity or equipment not only include those key elements, but also include other key elements being not expressly set out, or also include the key element intrinsic for this process, method, commodity or equipment. When there is no more restriction, statement " including ... " key element limited, it is not excluded that there is also other identical element in including the process of described key element, method, commodity or equipment.
The foregoing is only the preferred embodiment of the application, not in order to limit the application, all within spirit herein and principle, any amendment of making, equivalent replacements, improvement etc., should be included within the scope that the application protects.
Claims (16)
1. the system robustness based on daily record model analyzes method, it is characterised in that including:
Transferring daily record model library, described daily record model library includes the daily record model corresponding with the text style of system journal;
Obtain the system journal generated in this robustness testing, and mate with described daily record model library;
According to the system journal bar number being matched with each daily record model, it is determined that the vigorousness of system.
2. method according to claim 1, it is characterised in that legacy system daily record is carried out process by longest common subsequence LCS algorithm and obtains by described daily record model.
3. method according to claim 2, it is characterized in that, described legacy system daily record is divided into multiple group, each group comprises the system journal of predetermined number, and the system journal of each group obtains corresponding longest common subsequence by described LCS algorithm process, then the frequency of occurrences is registered as described daily record model more than or equal to the longest common subsequence of predeterminated frequency.
4. method according to claim 3, it is characterized in that, it is a character string that every system journal in each group is carried out cutting by the default cutting symbol comprised according to this system journal, and by described LCS algorithm, all character strings of each group is carried out process and obtain corresponding longest common subsequence.
5. method according to claim 1, it is characterised in that also include:
According to the system journal not matching described daily record model library, generate new daily record model;
Described new daily record model is added in described daily record model library.
6. method according to claim 1, it is characterised in that described basis is matched with the system journal bar number of each daily record model, it is determined that the vigorousness of system, including:
According to current application scene, it is determined that the preset reference bar number that each daily record model being matched is corresponding;
According to the system journal bar number in this robustness testing and the comparative result between corresponding described preset reference bar number, it is determined that the vigorousness of system.
7. method according to claim 6, it is characterised in that described preset reference bar number includes:
First described in successful execution during robustness testing, it is matched with the system journal bar number of each daily record model;
Or, described in the last successful execution during robustness testing, it is matched with the system journal bar number of each daily record model.
8. method according to claim 1, it is characterised in that described basis is matched with the system journal bar number of each daily record model, it is determined that the vigorousness of system, including:
Obtain respectively under same type, simulated failure environment in various degree, be matched with the system journal bar number of same daily record model;
When the diversity factor of the system journal bar number corresponding with other simulated failure environment when the system journal bar number that arbitrary simulated failure environment is corresponding is more than or equal to default diversity factor, using the described arbitrary simulated failure environment vigorousness flex point as system.
9. the system robustness analytical equipment based on daily record model, it is characterised in that including:
Transferring unit, transfer daily record model library, described daily record model library includes the daily record model corresponding with the text style of system journal;
Matching unit, obtains the system journal generated in this robustness testing, and mates with described daily record model library;
Determine unit, according to the system journal bar number being matched with each daily record model, it is determined that the vigorousness of system.
10. device according to claim 9, it is characterised in that legacy system daily record is carried out process by longest common subsequence LCS algorithm and obtains by described daily record model.
11. device according to claim 10, it is characterized in that, described legacy system daily record is divided into multiple group, each group comprises the system journal of predetermined number, and the system journal of each group obtains corresponding longest common subsequence by described LCS algorithm process, then the frequency of occurrences is registered as described daily record model more than or equal to the longest common subsequence of predeterminated frequency.
12. device according to claim 11, it is characterized in that, it is a character string that every system journal in each group is carried out cutting by the default cutting symbol comprised according to this system journal, and by described LCS algorithm, all character strings of each group is carried out process and obtain corresponding longest common subsequence.
13. device according to claim 9, it is characterised in that also include:
Generate unit, according to the system journal not matching described daily record model library, generate new daily record model;
Adding device, is added into described new daily record model in described daily record model library.
14. device according to claim 9, it is characterised in that described determine unit for:
According to current application scene, it is determined that the preset reference bar number that each daily record model being matched is corresponding;
According to the system journal bar number in this robustness testing and the comparative result between corresponding described preset reference bar number, it is determined that the vigorousness of system.
15. device according to claim 14, it is characterised in that described preset reference bar number includes:
First described in successful execution during robustness testing, it is matched with the system journal bar number of each daily record model;
Or, described in the last successful execution during robustness testing, it is matched with the system journal bar number of each daily record model.
16. device according to claim 9, it is characterised in that described determine unit for:
Obtain respectively under same type, simulated failure environment in various degree, be matched with the system journal bar number of same daily record model;
When the diversity factor of the system journal bar number corresponding with other simulated failure environment when the system journal bar number that arbitrary simulated failure environment is corresponding is more than or equal to default diversity factor, using the described arbitrary simulated failure environment vigorousness flex point as system.
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| CN107664680A (en) * | 2016-07-27 | 2018-02-06 | 复凌科技（上海）有限公司 | A kind of adaptive acquiring method and device of water quality soft-sensing model |
| CN107664680B (en) * | 2016-07-27 | 2020-08-14 | 复凌科技（上海）有限公司 | Self-adaptive acquisition method and device of water quality soft measurement model |
| CN106844576A (en) * | 2017-01-06 | 2017-06-13 | 北京蓝海讯通科技股份有限公司 | A kind of method for detecting abnormality, device and monitoring device |
| CN106844576B (en) * | 2017-01-06 | 2020-10-13 | 北京蓝海讯通科技股份有限公司 | Abnormity detection method and device and monitoring equipment |
| CN109189840A (en) * | 2018-07-20 | 2019-01-11 | 西安交通大学 | A kind of online log analytic method of streaming |
| CN109726185A (en) * | 2018-12-28 | 2019-05-07 | 杭州安恒信息技术股份有限公司 | A kind of log analytic method, system and computer-readable medium based on syntax tree |
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| CN110825873A (en) * | 2019-10-11 | 2020-02-21 | 支付宝(杭州)信息技术有限公司 | Method and device for expanding log exception classification rule |
| CN114697238A (en) * | 2022-03-30 | 2022-07-01 | 四川九州电子科技股份有限公司 | System and method for testing robustness of communication equipment system |
| CN114697238B (en) * | 2022-03-30 | 2023-04-28 | 四川九州电子科技股份有限公司 | System and method for testing robustness of communication equipment system |
| CN115329900A (en) * | 2022-10-12 | 2022-11-11 | 北京安帝科技有限公司 | Abnormal event mining method and system for massive industrial control network log data |
| CN115329900B (en) * | 2022-10-12 | 2023-01-24 | 北京安帝科技有限公司 | Abnormal event mining method and system for massive industrial control network log data |
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