CN117149481A - Abnormality repairing method, abnormality repairing device, computer device and storage medium - Google Patents
Abnormality repairing method, abnormality repairing device, computer device and storage medium Download PDFInfo
- Publication number
- CN117149481A CN117149481A CN202310967159.XA CN202310967159A CN117149481A CN 117149481 A CN117149481 A CN 117149481A CN 202310967159 A CN202310967159 A CN 202310967159A CN 117149481 A CN117149481 A CN 117149481A
- Authority
- CN
- China
- Prior art keywords
- target
- data image
- abnormal data
- abnormal
- repair
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 43
- 230000005856 abnormality Effects 0.000 title claims abstract description 39
- 230000002159 abnormal effect Effects 0.000 claims abstract description 343
- 230000008439 repair process Effects 0.000 claims description 142
- 238000004590 computer program Methods 0.000 claims description 34
- 238000005516 engineering process Methods 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 5
- 238000013500 data storage Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 4
- 238000012423 maintenance Methods 0.000 description 4
- 230000008859 change Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 229910021389 graphene Inorganic materials 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
- G06F11/0793—Remedial or corrective actions
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Facsimiles In General (AREA)
Abstract
The application relates to an abnormality repairing method, an abnormality repairing device, computer equipment and a storage medium, which can be used in the field of financial science and technology or other related fields. The method comprises the following steps: acquiring a target abnormal data image of an application program with a target abnormal problem; determining a target restoration scheme of the target abnormal problem according to the target abnormal data image; and repairing the target abnormal problem according to the target repairing scheme. By adopting the method, the accuracy and the efficiency for repairing the abnormal problems of the application program can be improved.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to an anomaly repair method, apparatus, computer device, and storage medium, which may be used in the field of financial science and technology or other related fields.
Background
An application may refer to a computer program that performs one or more specific tasks, which can be executed at a user terminal and interacted with by a user. Due to the ever changing demands of users, applications also need to be updated continuously to meet the various demands of users. After the application program is updated, an abnormal error reporting situation may occur.
In the prior art, the mode of repairing the abnormality of the application program is generally that an operation and maintenance person manually determines a repairing scheme for the abnormality according to specific information of the abnormality. However, this method is too dependent on experience of operation staff, and has problems of low accuracy and poor timeliness of abnormality repair.
Disclosure of Invention
In view of the foregoing, it is desirable to provide an abnormality repairing method, apparatus, computer device, and storage medium that can improve the accuracy and efficiency of repairing an abnormality occurring in an application program.
In a first aspect, the present application provides an anomaly repair method, the method comprising:
acquiring a target abnormal data image of an application program with a target abnormal problem;
determining a target repairing scheme of the target abnormal problem according to the target abnormal data image;
and repairing the abnormal problem of the target according to the target repairing scheme.
In one embodiment, obtaining an anomaly data image of an application program with a target anomaly problem includes:
and constructing a target abnormal data image of the target abnormal problem according to the abnormal information of the target abnormal problem of the application program.
In one embodiment, determining a target repair scheme for a target anomaly problem according to a target anomaly data image includes:
and determining a target restoration scheme of the target abnormal problem according to the target abnormal data image based on a preset corresponding relation between the candidate abnormal data image and the candidate restoration scheme.
In one embodiment, determining a target repair solution for a target anomaly problem from a target anomaly data image based on a predetermined correspondence between candidate anomaly data images and candidate repair solutions includes:
performing similarity comparison on the target abnormal data image and the candidate abnormal data image;
if the candidate abnormal data image has a reference abnormal data image with the similarity with the target abnormal data image being larger than a preset threshold value, extracting a repair scheme corresponding to the reference abnormal data image from the candidate repair scheme based on a preset corresponding relation between the candidate abnormal data image and the candidate repair scheme;
and taking the repair scheme corresponding to the reference abnormal data image as a target repair scheme of the target abnormal problem.
In one embodiment, determining a target repair solution for a target anomaly problem from a target anomaly data image based on a predetermined correspondence between candidate anomaly data images and candidate repair solutions includes:
performing similarity comparison on the target abnormal data image and the candidate abnormal data image;
and if the candidate abnormal data image does not have the reference abnormal data image with the similarity with the target abnormal data image being larger than the preset threshold value, using the general repairing scheme as the target repairing scheme of the target abnormal problem.
In one embodiment, the method further comprises:
determining a repairing result for repairing the target abnormal problem;
and if the repair result is that the repair fails, outputting alarm information.
In a second aspect, the present application also provides an abnormality repair apparatus, including:
the image acquisition module is used for acquiring a target abnormal data image of the application program with the target abnormal problem;
the scheme determining module is used for determining a target repairing scheme of the target abnormal problem according to the target abnormal data image;
and the abnormality repairing module is used for repairing the abnormal problem of the target according to the target repairing scheme.
In a third aspect, the present application also provides a computer device comprising a memory storing a computer program and a processor implementing the following steps when executing the computer program:
acquiring a target abnormal data image of an application program with a target abnormal problem;
determining a target repairing scheme of the target abnormal problem according to the target abnormal data image;
and repairing the abnormal problem of the target according to the target repairing scheme.
In a fourth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
acquiring a target abnormal data image of an application program with a target abnormal problem;
determining a target repairing scheme of the target abnormal problem according to the target abnormal data image;
and repairing the abnormal problem of the target according to the target repairing scheme.
In a fifth aspect, the application also provides a computer program product comprising a computer program which, when executed by a processor, performs the steps of:
acquiring a target abnormal data image of an application program with a target abnormal problem;
determining a target repairing scheme of the target abnormal problem according to the target abnormal data image;
and repairing the abnormal problem of the target according to the target repairing scheme.
According to the method, the device, the computer equipment and the storage medium for repairing the target abnormality, the target abnormality data image of the target abnormality problem of the constructed application program is introduced, and the target repairing scheme aiming at the target abnormality problem can be more rapidly and accurately determined according to the target abnormality data image; furthermore, according to the determined target repairing scheme aiming at the target abnormal problem, the target abnormal problem of the application program can be repaired more quickly and accurately, so that the target abnormal problem of the application program can be rapidly solved, and the normal use effect of the application program is not affected.
Drawings
FIG. 1 is a flow chart of an anomaly repair method in one embodiment;
FIG. 2 is a flow diagram of a target repair solution for determining a target anomaly problem in one embodiment;
FIG. 3 is a flowchart of an anomaly repair method according to another embodiment;
FIG. 4 is a block diagram of an anomaly repair device in one embodiment;
FIG. 5 is a block diagram of an anomaly repair device in one embodiment;
fig. 6 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The abnormality repairing method provided by the embodiment of the application can be applied to repairing the target abnormality problem of the application program under the condition that the abnormality of the application program is detected. The application program is a computer program running in a user mode and can interact with a user. The application may be presented in the form of an applet, a web page, or a standalone APP, etc. Alternatively, the abnormality repair method may be performed by a server or a terminal. It will be appreciated that the method may also be applied to a system comprising a terminal and a server and implemented by interaction of the terminal and the server. The method is applied to a server for example, wherein the data storage system can store data which needs to be processed by the server, such as data of a corresponding relation between a candidate abnormal data portrait and a candidate restoration scheme. The data storage system may be integrated on a server or may be placed on a cloud or other network server. The server may be implemented as a stand-alone server or as a server cluster composed of a plurality of servers.
In one embodiment, as shown in fig. 1, an exception repairing method is provided, and the method is applied to a server for illustration, and in this embodiment, the method includes the following steps:
s101, acquiring a target abnormal data image of the application program with the target abnormal problem.
The target abnormal problem is an abnormal problem that occurs in the application program and is detected at present, such as a flashing problem, a white screen problem and the like. The target abnormal data image is the image describing the target abnormal problem.
Specifically, after detecting that a problem occurs in an application program, the problem of target abnormality occurring in the application program may be input into a preset image generation model, and a target abnormality data image of the problem of target abnormality may be determined by the image generation model.
Optionally, after detecting that a problem occurs in the application program, the anomaly information of the target anomaly problem occurring in the application program may be collected, so as to construct a target anomaly data image of the target anomaly problem according to the anomaly information of the target anomaly problem occurring in the application program.
The abnormal information may include stack information characteristics, key stack information, abnormal phenomena, and the like.
Specifically, the abnormal information of the target abnormal problem occurring in the application program can be collected, and a target abnormal data image aiming at the target abnormal problem is constructed through an image construction model according to the collected abnormal information.
It can be understood that by collecting the anomaly information of the target anomaly problem and further constructing the target anomaly data image of the target anomaly problem according to the anomaly information, the constructed target anomaly data image can be more accurate.
S102, determining a target restoration scheme of the target abnormal problem according to the target abnormal data image.
The target repairing scheme is a scheme for repairing the target abnormal problem.
Specifically, after the target abnormal data image of the target abnormal problem is obtained, the target abnormal data image may be input into a predetermined repair scheme determination model, and a target repair scheme for the target abnormal problem may be generated by the repair scheme determination model.
S103, repairing the abnormal problem of the target according to the target repairing scheme.
Specifically, after determining the target repairing scheme for the target abnormal problem, the target abnormal problem can be repaired by self according to the target repairing scheme, and the repairing result is obtained.
According to the anomaly repairing method, the target anomaly data image of the target anomaly problem of the constructed application program is introduced, and the target repairing scheme aiming at the target anomaly problem can be more rapidly and accurately determined according to the target anomaly data image; furthermore, according to the determined target repairing scheme aiming at the target abnormal problem, the target abnormal problem of the application program can be repaired more quickly and accurately, so that the target abnormal problem of the application program can be rapidly solved, and the normal use effect of the application program is not affected.
Further, after repairing the target abnormal problem according to the target repairing scheme, a repairing result of repairing the target abnormal problem can be determined; and if the repair result is that the repair fails, outputting alarm information.
The repair result is the result of repairing the target abnormal problem, and can be repair success or repair failure.
Specifically, after repairing the target abnormal problem according to the target repairing scheme, the repairing result can be fed back, and the repairing result is judged to be successful or failed; optionally, if the repair result is determined to be successful, the problem of target abnormality of the application program is solved, and the application program is recovered to be normal; if the repair result is failure repair, it is indicated that the problem of the abnormal target occurred in the application program is not solved, and then alarm information is output to prompt the operation and maintenance personnel that the problem of the abnormal target is not solved, and the operation and maintenance personnel is required to repair the problem manually.
It can be understood that by determining the repair result of repairing the target abnormal problem, and outputting alarm information to prompt the operation and maintenance personnel to manually intervene under the condition that the repair result is that the repair fails, the target abnormal problem appearing in the application program can be repaired more timely, so that the situation that service processing on the application program is influenced for a long time is avoided.
In order to make the determined target repairing scheme of the target abnormal problem more reasonable and accurate, in one embodiment, after obtaining the target abnormal data image of the target abnormal problem, the target repairing scheme of the target abnormal problem may be determined according to the target abnormal data image based on a preset correspondence between the candidate abnormal data image and the candidate repairing scheme.
The candidate abnormal data images are the pre-stored abnormal data images corresponding to various abnormal problems; the candidate repair schemes are a plurality of repair schemes corresponding to a plurality of abnormal problems stored in advance.
Specifically, after the target abnormal data image of the target abnormal problem is determined, the corresponding relation between the candidate abnormal data image and the candidate repair scheme can be obtained from the data storage system, the target abnormal data image is further used as an index, the candidate abnormal data image similar to the target abnormal data image is searched from the corresponding relation between the candidate abnormal data image and the candidate repair scheme, and the candidate repair scheme corresponding to the candidate abnormal data image similar to the target abnormal data image is further extracted and used as the target repair scheme of the target abnormal problem.
It can be understood that by introducing the correspondence between the candidate abnormal data image and the candidate repair scheme, further according to the target abnormal data image of the target abnormal problem, the effect of determining the target repair scheme of the target abnormal problem more quickly and reasonably can be achieved.
Based on the foregoing embodiments, in one embodiment, as shown in fig. 2, in order to determine, according to the target abnormal data image, the target repair scheme of the target abnormal problem based on the preset correspondence between the candidate abnormal data image and the candidate repair scheme, an implementation manner is provided, which specifically may include the following steps:
s201, comparing the similarity of the target abnormal data image and the candidate abnormal data image.
Specifically, after the target abnormal data image of the target abnormal problem is determined, the corresponding relation between the candidate abnormal data image and the candidate restoration scheme can be obtained from the data storage system, the target abnormal data image and the candidate abnormal data image are further input into a preset similarity comparison model, and the similarity comparison model is used for performing similarity comparison on the target abnormal data image and the candidate abnormal data image to obtain the similarity between the target abnormal data image and each candidate abnormal data image.
Alternatively, the feature extraction model may be used to extract features of the target abnormal data image and the candidate abnormal data images, and the features of the target abnormal data image and the features of the candidate abnormal data images may be compared in similarity, so as to obtain the similarity between the target abnormal data image and each candidate abnormal data image.
S202, determining whether a reference abnormal data image with the similarity to the target abnormal data image being larger than a preset threshold exists in the candidate abnormal data images; if yes, executing S203; if not, S205 is performed.
The reference abnormal data image is the abnormal data image that the target abnormal data image can use to reference in the candidate abnormal data image.
Specifically, after obtaining the similarity between the target abnormal data image and each candidate abnormal data image, comparing each similarity with a preset threshold; if the similarity is larger than the preset threshold, the candidate abnormal data image corresponding to the similarity is used as the reference abnormal data image of the target abnormal data image.
S203, extracting a repair scheme corresponding to the reference abnormal data image from the candidate repair schemes based on the preset corresponding relation between the candidate abnormal data image and the candidate repair schemes.
Specifically, after the reference abnormal data image is determined, the reference abnormal data image can be used as an index, and the corresponding relation between the preset candidate abnormal data image and the candidate repairing scheme is searched, so that the repairing scheme corresponding to the reference abnormal data image in the candidate repairing scheme is determined, and the repairing scheme corresponding to the reference abnormal data image is extracted.
S204, taking the repair scheme corresponding to the reference abnormal data image as a target repair scheme of the target abnormal problem.
Specifically, after the repair scheme corresponding to the reference abnormal data image is extracted from the candidate repair schemes, the extracted repair scheme can be used as a target repair scheme for the target abnormal problem to repair the target abnormal problem of the application program.
It can be understood that by determining the similarity between the target abnormal data image and the candidate abnormal data image, when there is a candidate abnormal data image with the similarity greater than the preset threshold, the reference abnormal data image similar to the target abnormal data image can be determined more accurately, and the repair scheme corresponding to the reference abnormal data image is used as the target repair scheme of the target abnormal problem, so that the rationality and accuracy of the determined target abnormal problem repair scheme can be improved.
S205, using the general restoration scheme as a target restoration scheme of the target abnormal problem.
The general repairing scheme is a pre-stored repairing scheme which can be suitable for various abnormal problems.
Specifically, if it is determined that the candidate abnormal data image does not have the reference abnormal data image of the target abnormal data image, a general repairing scheme can be acquired from the data set storage system, and the general repairing scheme is used as a target repairing scheme for the target abnormal problem to repair the target abnormal problem of the application program.
It can be understood that by determining the similarity between the target abnormal data image and the candidate abnormal data image, the general repairing scheme is used as the target repairing scheme of the target abnormal problem under the condition that the candidate abnormal data image with the similarity larger than the preset threshold value does not exist, so that the target repairing scheme can be determined more quickly, and the target abnormal problem of the application program can be repaired more quickly.
In one embodiment, as shown in FIG. 3, a preferred example of an exception repair method is provided. The specific process is as follows:
s301, constructing a target abnormal data image of the target abnormal problem according to the abnormal information of the target abnormal problem of the application program.
S302, comparing the similarity of the target abnormal data image and the candidate abnormal data image.
S303, determining whether a reference abnormal data image with the similarity to the target abnormal data image being larger than a preset threshold value exists; if yes, executing S304; if not, S306 is performed.
S304, extracting a repair scheme corresponding to the reference abnormal data image from the candidate repair schemes based on the preset corresponding relation between the candidate abnormal data image and the candidate repair schemes.
S305, taking a repair scheme corresponding to the reference abnormal data image as a target repair scheme of the target abnormal problem; and then S307 is performed.
S306, using the general repair scheme as a target repair scheme for the target abnormal problem; and then S307 is performed.
S307, repairing the abnormal problem of the target according to the target repairing scheme.
S308, determining a repairing result for repairing the target abnormal problem.
S309, if the repair result is that the repair fails, outputting alarm information.
The specific process of S301 to S309 may refer to the description of the foregoing method embodiment, and the implementation principle and technical effects are similar, and are not repeated herein.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides an abnormality repair device for realizing the abnormality repair method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiment of one or more abnormality repair devices provided below may be referred to the limitation of the abnormality repair method hereinabove, and will not be repeated here.
In one embodiment, as shown in fig. 4, there is provided an abnormality repairing device 1 including: a representation acquisition module 10, a scheme determination module 20, and an anomaly repair module 30, wherein:
and the portrait acquisition module 10 is used for acquiring a target abnormal data portrait of the target abnormal problem of the application program.
The solution determining module 20 is configured to determine a target repair solution for the target abnormal problem according to the target abnormal data image.
The anomaly repair module 30 is configured to repair the target anomaly problem according to a target repair scheme.
In one embodiment, the image acquisition module 10 may be specifically configured to:
and constructing a target abnormal data image of the target abnormal problem according to the abnormal information of the target abnormal problem of the application program.
In one embodiment, on the basis of fig. 4, as shown in fig. 5, the scheme determining module 20 may include:
the solution determining unit 21 is configured to determine a target repair solution of the target abnormality problem from the target abnormality data image based on a preset correspondence between the candidate abnormality data image and the candidate repair solution.
In one embodiment, the scheme determining unit 21 may specifically be configured to:
performing similarity comparison on the target abnormal data image and the candidate abnormal data image; if the candidate abnormal data image has a reference abnormal data image with the similarity with the target abnormal data image being larger than a preset threshold value, extracting a repair scheme corresponding to the reference abnormal data image from the candidate repair scheme based on a preset corresponding relation between the candidate abnormal data image and the candidate repair scheme; and taking the repair scheme corresponding to the reference abnormal data image as a target repair scheme of the target abnormal problem.
In an embodiment, the above scheme determination unit 21 may be further specifically configured to:
performing similarity comparison on the target abnormal data image and the candidate abnormal data image; and if the candidate abnormal data image does not have the reference abnormal data image with the similarity with the target abnormal data image being larger than the preset threshold value, using the general repairing scheme as the target repairing scheme of the target abnormal problem.
In one embodiment, the abnormality repairing device 1 may further include:
the alarm module is used for determining a repairing result of repairing the target abnormal problem; and if the repair result is that the repair fails, outputting alarm information.
The respective modules in the above-described abnormality repairing device may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 6. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer equipment is used for storing data such as the corresponding relation between the candidate abnormal data image and the candidate repair scheme. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements an exception repair method.
It will be appreciated by those skilled in the art that the structure shown in FIG. 6 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
acquiring a target abnormal data image of an application program with a target abnormal problem;
determining a target repairing scheme of the target abnormal problem according to the target abnormal data image;
and repairing the abnormal problem of the target according to the target repairing scheme.
In one embodiment, when the processor executes logic for acquiring an abnormal data image of an application program with a target abnormal problem, the following steps are further implemented:
and constructing a target abnormal data image of the target abnormal problem according to the abnormal information of the target abnormal problem of the application program.
In one embodiment, when the processor executes logic of the target repair scheme for determining the target abnormal problem according to the target abnormal data image, the following steps are further implemented:
and determining a target restoration scheme of the target abnormal problem according to the target abnormal data image based on a preset corresponding relation between the candidate abnormal data image and the candidate restoration scheme.
In one embodiment, when the processor executes logic for determining a target repair solution for a target anomaly problem from the target anomaly data image based on a predetermined correspondence between candidate anomaly data images and candidate repair solutions, the processor further performs the steps of:
performing similarity comparison on the target abnormal data image and the candidate abnormal data image; if the candidate abnormal data image has a reference abnormal data image with the similarity with the target abnormal data image being larger than a preset threshold value, extracting a repair scheme corresponding to the reference abnormal data image from the candidate repair scheme based on a preset corresponding relation between the candidate abnormal data image and the candidate repair scheme; and taking the repair scheme corresponding to the reference abnormal data image as a target repair scheme of the target abnormal problem.
In one embodiment, when the processor executes logic for determining a target repair solution for a target anomaly problem from the target anomaly data image based on a predetermined correspondence between candidate anomaly data images and candidate repair solutions, the processor further performs the steps of:
performing similarity comparison on the target abnormal data image and the candidate abnormal data image; and if the candidate abnormal data image does not have the reference abnormal data image with the similarity with the target abnormal data image being larger than the preset threshold value, using the general repairing scheme as the target repairing scheme of the target abnormal problem.
In one embodiment, the processor when executing the computer program further performs the steps of:
determining a repairing result for repairing the target abnormal problem; and if the repair result is that the repair fails, outputting alarm information.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring a target abnormal data image of an application program with a target abnormal problem;
determining a target repairing scheme of the target abnormal problem according to the target abnormal data image;
and repairing the abnormal problem of the target according to the target repairing scheme.
In one embodiment, the logic for the computer program to obtain an anomaly data image of an application program that presents a target anomaly problem when executed by the processor further performs the steps of:
and constructing a target abnormal data image of the target abnormal problem according to the abnormal information of the target abnormal problem of the application program.
In one embodiment, the logic of the computer program for determining a target repair solution for a target anomaly problem based on a target anomaly data image, when executed by the processor, further performs the steps of:
and determining a target restoration scheme of the target abnormal problem according to the target abnormal data image based on a preset corresponding relation between the candidate abnormal data image and the candidate restoration scheme.
In one embodiment, the computer program further implements the following steps when the logic for determining the target repair solution for the target anomaly issue is executed by the processor based on the predetermined correspondence between the candidate anomaly data image and the candidate repair solution, based on the target anomaly data image:
performing similarity comparison on the target abnormal data image and the candidate abnormal data image; if the candidate abnormal data image has a reference abnormal data image with the similarity with the target abnormal data image being larger than a preset threshold value, extracting a repair scheme corresponding to the reference abnormal data image from the candidate repair scheme based on a preset corresponding relation between the candidate abnormal data image and the candidate repair scheme; and taking the repair scheme corresponding to the reference abnormal data image as a target repair scheme of the target abnormal problem.
In one embodiment, the computer program further implements the following steps when the logic for determining the target repair solution for the target anomaly issue is executed by the processor based on the predetermined correspondence between the candidate anomaly data image and the candidate repair solution, based on the target anomaly data image:
performing similarity comparison on the target abnormal data image and the candidate abnormal data image; and if the candidate abnormal data image does not have the reference abnormal data image with the similarity with the target abnormal data image being larger than the preset threshold value, using the general repairing scheme as the target repairing scheme of the target abnormal problem.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining a repairing result for repairing the target abnormal problem; and if the repair result is that the repair fails, outputting alarm information.
In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of:
acquiring a target abnormal data image of an application program with a target abnormal problem;
determining a target repairing scheme of the target abnormal problem according to the target abnormal data image;
and repairing the abnormal problem of the target according to the target repairing scheme.
In one embodiment, the logic for the computer program to obtain an anomaly data image of an application program that presents a target anomaly problem when executed by the processor further performs the steps of:
and constructing a target abnormal data image of the target abnormal problem according to the abnormal information of the target abnormal problem of the application program.
In one embodiment, the logic of the computer program for determining a target repair solution for a target anomaly problem based on a target anomaly data image, when executed by the processor, further performs the steps of:
and determining a target restoration scheme of the target abnormal problem according to the target abnormal data image based on a preset corresponding relation between the candidate abnormal data image and the candidate restoration scheme.
In one embodiment, the computer program further implements the following steps when the logic for determining the target repair solution for the target anomaly issue is executed by the processor based on the predetermined correspondence between the candidate anomaly data image and the candidate repair solution, based on the target anomaly data image:
performing similarity comparison on the target abnormal data image and the candidate abnormal data image; if the candidate abnormal data image has a reference abnormal data image with the similarity with the target abnormal data image being larger than a preset threshold value, extracting a repair scheme corresponding to the reference abnormal data image from the candidate repair scheme based on a preset corresponding relation between the candidate abnormal data image and the candidate repair scheme; and taking the repair scheme corresponding to the reference abnormal data image as a target repair scheme of the target abnormal problem.
In one embodiment, the computer program further implements the following steps when the logic for determining the target repair solution for the target anomaly issue is executed by the processor based on the predetermined correspondence between the candidate anomaly data image and the candidate repair solution, based on the target anomaly data image:
performing similarity comparison on the target abnormal data image and the candidate abnormal data image; and if the candidate abnormal data image does not have the reference abnormal data image with the similarity with the target abnormal data image being larger than the preset threshold value, using the general repairing scheme as the target repairing scheme of the target abnormal problem.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining a repairing result for repairing the target abnormal problem; and if the repair result is that the repair fails, outputting alarm information.
It should be noted that, the data related to the present application (including, but not limited to, the data such as the correspondence between the candidate abnormal data image and the candidate repair scheme) are the information and the data that are fully authorized by each party.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
Claims (10)
1. A method of anomaly repair, the method comprising:
acquiring a target abnormal data image of an application program with a target abnormal problem;
determining a target restoration scheme of the target abnormal problem according to the target abnormal data image;
and repairing the target abnormal problem according to the target repairing scheme.
2. The method of claim 1, wherein the acquiring the anomaly data image of the target anomaly problem for the application comprises:
and constructing a target abnormal data image of the target abnormal problem according to the abnormal information of the target abnormal problem of the application program.
3. The method of claim 1, wherein determining a target repair solution for the target anomaly problem based on the target anomaly data image comprises:
and determining a target restoration scheme of the target abnormal problem according to the target abnormal data image based on a preset corresponding relation between the candidate abnormal data image and the candidate restoration scheme.
4. The method of claim 3, wherein determining the target repair solution for the target anomaly issue from the target anomaly data image based on a predetermined correspondence between candidate anomaly data images and candidate repair solutions comprises:
performing similarity comparison on the target abnormal data image and the candidate abnormal data image;
if the candidate abnormal data image has a reference abnormal data image with the similarity with the target abnormal data image being larger than a preset threshold value, extracting a repair scheme corresponding to the reference abnormal data image from the candidate repair scheme based on a preset corresponding relation between the candidate abnormal data image and the candidate repair scheme;
and taking the repair scheme corresponding to the reference abnormal data image as a target repair scheme of the target abnormal problem.
5. The method of claim 3, wherein determining the target repair solution for the target anomaly issue from the target anomaly data image based on a predetermined correspondence between candidate anomaly data images and candidate repair solutions comprises:
performing similarity comparison on the target abnormal data image and the candidate abnormal data image;
and if the candidate abnormal data image does not have the reference abnormal data image with the similarity with the target abnormal data image being larger than a preset threshold value, using the general repairing scheme as the target repairing scheme of the target abnormal problem.
6. The method according to claim 1, wherein the method further comprises:
determining a repairing result for repairing the target abnormal problem;
and if the repair result is that the repair fails, outputting alarm information.
7. An abnormality repair device, the device comprising:
the image acquisition module is used for acquiring a target abnormal data image of the application program with the target abnormal problem;
the scheme determining module is used for determining a target repairing scheme of the target abnormal problem according to the target abnormal data image;
and the abnormality repairing module is used for repairing the target abnormal problem according to the target repairing scheme.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310967159.XA CN117149481A (en) | 2023-08-02 | 2023-08-02 | Abnormality repairing method, abnormality repairing device, computer device and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310967159.XA CN117149481A (en) | 2023-08-02 | 2023-08-02 | Abnormality repairing method, abnormality repairing device, computer device and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117149481A true CN117149481A (en) | 2023-12-01 |
Family
ID=88901615
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310967159.XA Pending CN117149481A (en) | 2023-08-02 | 2023-08-02 | Abnormality repairing method, abnormality repairing device, computer device and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117149481A (en) |
-
2023
- 2023-08-02 CN CN202310967159.XA patent/CN117149481A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110471945B (en) | Active data processing method, system, computer equipment and storage medium | |
| CN116737495A (en) | Method, device, computer equipment and storage medium for determining running state | |
| CN115793990B (en) | Memory health state determining method and device, electronic equipment and storage medium | |
| CN116933035A (en) | Data anomaly detection method, device, computer equipment and storage medium | |
| CN117149481A (en) | Abnormality repairing method, abnormality repairing device, computer device and storage medium | |
| CN116168462A (en) | Safety hidden danger identification method, device and equipment based on intelligent inspection equipment | |
| CN114198863B (en) | Fault detection method and device for air conditioner in machine room, computer equipment and storage medium | |
| US20230367932A1 (en) | Adaptive density estimation with multi-layered histograms | |
| US8780471B2 (en) | Linking errors to particular tapes or particular tape drives | |
| CN118051364A (en) | Host operation and maintenance method, device, computer equipment and storage medium | |
| CN117437437A (en) | Method, device, equipment, medium and program product for determining state of machine room server | |
| CN117331984A (en) | Data comparison method, device, computer equipment and storage medium | |
| CN117349184A (en) | Test case generation method, device, computer equipment and storage medium | |
| CN116975072A (en) | Data processing method, device, computer equipment and storage medium | |
| CN118095623A (en) | Reactor operation strategy generation method, device, equipment, medium and product | |
| CN118134099A (en) | Equipment monitoring method, device, equipment, storage medium and computer program product | |
| CN116846670A (en) | Method and device for generating network security configuration policy and computer equipment | |
| CN118279037A (en) | Resource gain data determining method, device, computer equipment and storage medium | |
| CN116578455A (en) | Change risk monitoring method, device, computer equipment and storage medium | |
| CN116577586A (en) | Power equipment fault monitoring method, device, computer equipment and storage medium | |
| CN116881092A (en) | Method, device, equipment and storage medium for predicting alarm data | |
| CN117041015A (en) | Network fault detection method, device, computer equipment and storage medium | |
| CN116828505A (en) | Fault processing method, device, computer equipment and storage medium | |
| CN116932677A (en) | Address information matching method, device, computer equipment and storage medium | |
| CN117973940A (en) | Urban system electric power emergency capacity prediction method and device and computer equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |