CN114937316B - Software fault detection method, device, equipment and medium - Google Patents
Software fault detection method, device, equipment and medium Download PDFInfo
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- CN114937316B CN114937316B CN202210539493.0A CN202210539493A CN114937316B CN 114937316 B CN114937316 B CN 114937316B CN 202210539493 A CN202210539493 A CN 202210539493A CN 114937316 B CN114937316 B CN 114937316B
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- 238000004590 computer program Methods 0.000 claims description 15
- 230000006870 function Effects 0.000 description 12
- 238000003745 diagnosis Methods 0.000 description 7
- 238000004891 communication Methods 0.000 description 5
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0808—Diagnosing performance data
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/008—Registering or indicating the working of vehicles communicating information to a remotely located station
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0841—Registering performance data
- G07C5/085—Registering performance data using electronic data carriers
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0677—Localisation of faults
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/069—Management of faults, events, alarms or notifications using logs of notifications; Post-processing of notifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/14—Arrangements for monitoring or testing data switching networks using software, i.e. software packages
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Abstract
The application discloses a software fault detection method, a device, equipment and a medium, and relates to the technical field of computers, wherein the method is applied to a server and comprises the following steps: acquiring a plurality of groups of original detection data which are sent by equipment and comprise an object identifier of a detection object, a detection item and a detection state corresponding to the detection item; the original detection data are data obtained after the equipment detects the detection object by utilizing local software; and retrieving target detection data with the detection state of detection abnormality from the plurality of groups of original detection data, and determining faults in the software according to the detection items in the target detection data and the object identifiers. Therefore, the method and the device increase the detection state for searching out the target detection data of the abnormal retrieval so as to determine the faults in the software according to the detection items and the object identifiers in the target detection data, thereby improving the efficiency of retrieving the faults of the software.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a medium for detecting a software failure.
Background
Currently, as the amount of maintenance of automobiles is increased, the number of vehicles entering a repair shop for repair every day is large, and diagnosis of the vehicles by diagnostic software is an indispensable way to perform various repair functions. The diagnostic software developer has very limited information through offline feedback, and can not timely determine the faults of the diagnostic software according to the received information, and similarly, other software can also do so, and the existing software fault detection method can not timely detect the faults of the software.
In summary, how to improve the efficiency of detecting software faults is a current urgent issue to be solved.
Disclosure of Invention
In view of the above, the present invention aims to provide a method, an apparatus, a device and a medium for detecting a software failure, which can improve the efficiency of detecting the software failure. The specific scheme is as follows:
in a first aspect, the present application discloses a fault detection method, applied to a server, including:
acquiring a plurality of groups of original detection data which are sent by equipment and comprise an object identifier of a detection object, a detection item and a detection state corresponding to the detection item; the original detection data are data obtained after the equipment detects the detection object by utilizing local software;
and retrieving target detection data with the detection state of detection abnormality from the plurality of groups of original detection data, and determining faults in the software according to the detection items in the target detection data and the object identifiers.
Optionally, the acquiring several sets of original detection data including the object identifier of the detection object, one detection item and the detection state corresponding to the detection item sent by the device includes:
acquiring a detection log file sent by equipment, and analyzing the detection log file to acquire a plurality of character strings;
and analyzing each character string to obtain a plurality of groups of original detection data comprising an object identifier of a detection object, a detection item and a detection state corresponding to the detection item.
Optionally, the obtaining the detection log file sent by the device includes:
and acquiring detection log files sent by equipment, and receiving and recording the character strings through a preset data interface in advance.
Optionally, the obtaining the detection log file sent by the device and analyzing the detection log file include:
and acquiring a detection log file sent by the equipment, searching whether the detection log file which is not analyzed exists locally according to a preset period, and then analyzing the detection log file which is not analyzed.
Optionally, the determining the fault in the software according to the detection item in the target detection data and the object identifier includes:
determining all original detection data which comprise the same object identifier with the target detection data, and searching whether error flows exist in detection flows corresponding to the detection items in all the original detection data;
and if the detection process corresponding to the detection item does not have an error process, determining a fault in the software by using the target item and the object identifier in the target detection data.
Optionally, after determining the fault in the software according to the detection item in the target detection data and the object identifier, the method further includes:
and adjusting the detection state in the target detection data from abnormal detection to normal detection.
In a second aspect, the present application discloses a software fault detection device, applied to a server, including:
the detection data acquisition module is used for acquiring a plurality of groups of original detection data which are sent by equipment and comprise object identifiers of detection objects, detection items and detection states corresponding to the detection items; the original detection data are data obtained after the equipment detects the detection object by utilizing local software;
and the fault determining module is used for retrieving target detection data with the detection state of detection abnormality from the plurality of groups of original detection data, and determining faults in the software according to the detection items in the target detection data and the object identifiers.
Optionally, the detection data acquisition module includes:
the first analysis unit is used for acquiring a detection log file sent by the equipment and analyzing the detection log file to acquire a plurality of character strings;
and the second analysis unit is used for analyzing each character string to acquire a plurality of groups of original detection data comprising an object identifier of a detection object, a detection item and a detection state corresponding to the detection item.
In a third aspect, the present application discloses an electronic device comprising a processor and a memory; the processor implements the software fault detection method disclosed above when executing the computer program stored in the memory.
In a fourth aspect, the present application discloses a computer-readable storage medium for storing a computer program; wherein the computer program, when executed by a processor, implements the software fault detection method disclosed previously.
As can be seen, the present application acquires several sets of original detection data including an object identifier of a detection object, a detection item, and a detection state corresponding to the detection item, which are sent by an apparatus; the original detection data are data obtained after the equipment detects the detection object by utilizing local software; and retrieving target detection data with the detection state of detection abnormality from the plurality of groups of original detection data, and determining faults in the software according to the detection items in the target detection data and the object identifiers. Therefore, the method and the device increase the detection state for retrieving the target detection data of the retrieval abnormality, so that the faults in the software are determined according to the detection items and the object identifiers in the target detection data, the efficiency of retrieving the faults of the software is improved, and the faults can be timely positioned according to the detected faults, so that the software is modified, the software execution success rate is improved, and the software execution success rate is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a software fault detection method provided in the present application;
FIG. 2 is a schematic diagram of a specific software fault detection method provided in the present application;
FIG. 3 is a block diagram of a software failure device provided herein;
fig. 4 is a block diagram of an electronic device provided in the present application.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
The existing software fault detection method can not timely detect the faults of the software.
In order to overcome the problems, the application provides a software fault detection scheme which can improve the efficiency of detecting software faults.
Referring to fig. 1, an embodiment of the present application discloses a software fault detection method, which is applied to a server, and includes:
step S11: acquiring a plurality of groups of original detection data which are sent by equipment and comprise an object identifier of a detection object, a detection item and a detection state corresponding to the detection item; the original detection data are data obtained after the equipment detects the detection object by utilizing local software.
In the embodiment of the application, a plurality of groups of original detection data, which are sent by equipment and comprise object identifiers of detection objects, detection items and detection states corresponding to the detection items, are acquired; the original detection data are data obtained after the equipment detects the detection object by utilizing local software. Specifically, firstly, a detection log file sent by equipment is obtained, and the detection log file is analyzed to obtain a plurality of character strings; and analyzing each character string to obtain a plurality of groups of original detection data comprising an object identifier of a detection object, a detection item and a detection state corresponding to the detection item. It should be noted that the obtained detection log file is a detection log file sent by the device, and the detection log files of the plurality of character strings are received and recorded through a preset data interface in advance.
In the embodiment of the application, when the software is vehicle diagnosis software, the server acquires a detection log file sent by the device, which is received and recorded in advance through a preset data interface, wherein the plurality of character strings are formed by a plurality of groups of original detection data, and specifically, the vehicle diagnosis software is required to record a plurality of groups of original detection data including the VIN (Vehicle Identification Number, vehicle identification code), the ECU (Electronic Control Unit ) model, the name of an execution function, the name of an execution sub-function and a status tag of a function execution process of the current vehicle, then the plurality of groups of original detection data are converted into character strings, the character strings are sent to the detection log file through a preset data interface, and then the detection log file is sent to the server, and the character strings are in the form of VIN+ECU keywords+the name of the execution function execution sub-function name+the status tag of the function execution process; it should be noted that, a specific set of raw detection data is shown in table one:
list one
The detection items specifically comprise VIN, ECU model, execution function name and execution sub-function name of the current vehicle, the corresponding execution sub-function names correspond to sub-function labels, the detection state is a function execution process state label, the detection state comprises detection normal and detection abnormal, the detection abnormal is detection failure, the detection normal is detection success, as shown in a table I, 1 indicates the detection normal, and 0 indicates the detection failure.
In this embodiment of the present application, after recording a plurality of sets of original detection data as shown in table one, the vehicle diagnostic software is required to record the plurality of sets of original detection data as shown in table one to a detection log file through a data recording interface, and specifically, the vehicle diagnostic software is required to record a plurality of sets of recorded character strings to the diagnosis log file through the data recording interface.
In this embodiment of the present application, the obtaining device obtains a diagnostic log file sent after the client agrees with the diagnostic feedback, specifically, needs the vehicle diagnostic software to record the original detection data into the diagnostic log file, and sends the diagnostic log file to the server after the client agrees with the diagnostic feedback, specifically, needs the vehicle diagnostic software to send the log to the server through the client diagnostic feedback.
Step S12: and retrieving target detection data with the detection state of detection abnormality from the plurality of groups of original detection data, and determining faults in the software according to the detection items in the target detection data and the object identifiers.
In this embodiment of the present application, target detection data including the detection state that is abnormal is retrieved from the plurality of sets of original detection data, and a fault in the software is determined according to the detection item and the object identifier in the target detection data. It should be noted that, after determining a fault in the software according to the detection item and the object identifier in the target detection data, the detection state in the target detection data is adjusted from abnormal detection to normal detection.
In the embodiment of the application, a detection log file sent by equipment is obtained, whether the detection log file which is not analyzed exists locally or not is searched according to a preset period, and then the detection log file which is not analyzed is analyzed. It should be noted that, when the software is vehicle diagnosis software, the received vehicle diagnosis log file is parsed to obtain a character string, the character string is parsed to the original detection data, and the original detection data is recorded into the database, as shown in table two:
watch II
And retrieving target detection data with abnormal detection states from the plurality of groups of original detection data, namely retrieving target detection data with retrieval failure, wherein the selected wave box mode programming verification signature fails as shown in a second table, determining and positioning faults in software according to the original detection data in the database and the target detection data, and timely positioning the faults according to the detected faults so as to modify the software, thereby perfecting the software and improving the software execution success rate. Wherein, "WBAXXXXXXXXXXXXX1" and "WBAXXXXXXXXXXX 2" are VIN of different vehicles, and wave box mode 1 and wave box mode 2 are wave box modes of different vehicles.
According to the embodiment of the application, the server background calculates the relevant labels recorded in the first step by periodically searching the feedback diagnosis log, records the statistical data, and locates and perfects the diagnosis software problem according to the data and the log.
In the embodiment of the application, VIN, ECU and function execution process labels are set through codes, setting data are recorded to a local log through a data transmission interface and transmitted to a server, a server background screens through big data, corresponding labels are counted, whether the function is abnormal to execute or not is checked, software is corrected according to the recorded related data and the screening result, and finally the success rate of the software is improved; in addition, most of the current diagnosis devices on the market can be upgraded on line and connected with the Internet. The diagnosis software can record the diagnosis log by setting each function execution label and feed back the diagnosis log to the server, and the server background calculates each function execution condition by classified retrieval.
As can be seen, the present application acquires several sets of original detection data including an object identifier of a detection object, a detection item, and a detection state corresponding to the detection item, which are sent by an apparatus; the original detection data are data obtained after the equipment detects the detection object by utilizing local software; and retrieving target detection data with the detection state of detection abnormality from the plurality of groups of original detection data, and determining faults in the software according to the detection items in the target detection data and the object identifiers. Therefore, the method and the device increase the detection state for retrieving the abnormal target detection data so as to determine the faults in the software according to the detection items and the object identifiers in the target detection data, thereby improving the efficiency of retrieving the faults of the software, and timely fault location according to the detected faults so as to modify the software, thereby perfecting the software and improving the success rate of executing the software; in addition, a large amount of original detection data are collected, and the detection state is set to be used as a label for successful or failed detection, so that the statistics of the function execution condition data can be more accurately carried out, and the software development condition can be more intuitively known.
Referring to fig. 2, an embodiment of the present application discloses a specific software fault detection method, which is applied to a server, and the method includes:
step S21: acquiring a plurality of groups of original detection data which are sent by equipment and comprise an object identifier of a detection object, a detection item and a detection state corresponding to the detection item; the original detection data are data obtained after the equipment detects the detection object by utilizing local software.
In this embodiment, for the specific process of step S21, reference may be made to the corresponding content disclosed in the foregoing embodiment, and no further description is given here.
Step S22: and retrieving target detection data with the detection state of detection abnormality from the plurality of groups of original detection data.
In this embodiment, for the specific process of step S22, reference may be made to the corresponding content disclosed in the foregoing embodiment, and no further description is given here.
Step S23: and determining whether error flows exist in detection flows corresponding to the detection items in all the original detection data.
In this embodiment of the present application, it is determined whether there is an error flow in the detection flows corresponding to the detection items in all the original detection data, where the original detection data includes the same object identifier. It should be noted that, the determination of whether the error flow exists is determined according to the original detection data having the same object identifier as the target detection data, and specifically, when the software is the vehicle diagnosis software, it is determined according to the original detection data having the same VIN as the target detection data.
Step S24: and if the detection process corresponding to the detection item does not have an error process, determining a fault in the software by using the target item and the object identifier in the target detection data.
In this embodiment of the present application, if there is no error flow in the detection flow corresponding to the detection item, determining a fault in the software by using the target item and the object identifier in the target detection data. If the error flow exists in the detection flow corresponding to the detection item, the error can be judged to occur in the process of adding the software by the equipment, and the software can be added again.
As can be seen, the present application acquires several sets of original detection data including an object identifier of a detection object, a detection item, and a detection state corresponding to the detection item, which are sent by an apparatus; the original detection data are data obtained after the equipment detects the detection object by utilizing local software; and retrieving target detection data with the detection state of detection abnormality from the plurality of groups of original detection data, and determining faults in the software according to the detection items in the target detection data and the object identifiers. Therefore, the method and the device increase the detection state for retrieving the target detection data of the retrieval abnormality so as to determine the faults in the software according to the detection items and the object identifiers in the target detection data, thereby improving the efficiency of retrieving the faults of the software, and can timely locate the faults according to the detected faults so as to modify the software, thereby perfecting the software and improving the success rate of executing the software.
Referring to fig. 3, an embodiment of the present application discloses a software fault detection device, which is applied to a server, and includes:
the detection data acquisition module 11 is used for acquiring a plurality of groups of original detection data which are sent by equipment and comprise an object identifier of a detection object, a detection item and a detection state corresponding to the detection item; the original detection data are data obtained after the equipment detects the detection object by utilizing local software;
the fault determining module 12 is configured to retrieve target detection data including the detection state that is abnormal from the several sets of original detection data, and determine a fault in the software according to the detection item and the object identifier in the target detection data.
The more specific working process of each module may refer to the corresponding content disclosed in the foregoing embodiment, and will not be described herein.
Therefore, the method and the device increase the detection state for retrieving the target detection data of the retrieval abnormality so as to determine the faults in the software according to the detection items and the object identifiers in the target detection data, thereby improving the efficiency of retrieving the faults of the software, and can timely locate the faults according to the detected faults so as to modify the software, thereby perfecting the software and improving the success rate of executing the software.
In some embodiments, the detection data obtaining module 11 may specifically include:
the first analysis unit is used for acquiring a detection log file sent by the equipment and analyzing the detection log file to acquire a plurality of character strings;
the second analysis unit is used for analyzing each character string to obtain a plurality of groups of original detection data comprising an object identifier of a detection object, a detection item and a detection state corresponding to the detection item;
the first parsing unit may specifically include:
the file acquisition unit is used for acquiring detection log files which are sent by equipment, received and recorded in advance through a preset data interface;
the first parsing unit may specifically include:
the first specific analysis unit is used for acquiring detection log files sent by equipment, searching whether the detection log files which are not analyzed exist locally according to a preset period, and then analyzing the detection log files which are not analyzed;
in some embodiments, the fault determination module 12 may specifically include:
a process searching unit, configured to determine that all the original detection data that includes the same object identifier as the target detection data, and search whether an error process exists in detection processes corresponding to the detection items in all the original detection data;
the fault determining unit is used for determining faults in the software by utilizing the target item and the object identifier in the target detection data if no error flow exists in the detection flow corresponding to the detection item;
in some embodiments, the software fault detection device specifically further includes:
and the adjusting module is used for adjusting the detection state in the target detection data from abnormal detection to normal detection.
Further, the embodiment of the present application further provides an electronic device, and fig. 4 is a structural diagram of the electronic device 20 according to an exemplary embodiment, where the content in the drawing is not to be considered as any limitation on the scope of use of the present application.
Fig. 4 is a schematic structural diagram of an electronic device 20 according to an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, an input-output interface 24, a communication interface 25, and a communication bus 26. Wherein the memory 22 is adapted to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps of the software fault detection method disclosed in any of the foregoing embodiments.
In this embodiment, the power supply 23 is configured to provide an operating voltage for each hardware device on the electronic device 20; the communication interface 25 can create a data transmission channel between the electronic device 20 and an external device, and the communication protocol to be followed is any communication protocol applicable to the technical solution of the present application, which is not specifically limited herein; the input/output interface 24 is used for obtaining external input data or outputting external output data, and the specific interface type thereof may be selected according to the specific application needs, which is not limited herein.
The memory 22 may be a carrier for storing resources, such as a read-only memory, a random access memory, a magnetic disk, or an optical disk, and the memory 22 may be a nonvolatile memory including a random access memory as a running memory and a storage purpose for an external memory, and the storage resources include an operating system 221, a computer program 222, and the like, and the storage may be temporary storage or permanent storage.
The operating system 221 is used to manage and control various hardware devices on the electronic device 20 and the computer program 222 on the source host, and the operating system 221 may be Windows, unix, linux or the like. The computer program 222 may further include a computer program capable of performing other specific tasks in addition to the computer program capable of performing the software fault detection method performed by the electronic device 20 as disclosed in any of the foregoing embodiments.
In this embodiment, the input/output interface 24 may specifically include, but is not limited to, a USB interface, a hard disk read interface, a serial interface, a voice input interface, a fingerprint input interface, and the like.
Further, the embodiment of the application also discloses a computer readable storage medium for storing a computer program; wherein the computer program, when executed by a processor, implements the software fault detection method disclosed previously.
For specific steps of the method, reference may be made to the corresponding contents disclosed in the foregoing embodiments, and no further description is given here.
The computer readable storage medium as referred to herein includes random access Memory (Random Access Memory, RAM), memory, read-Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, magnetic or optical disk, or any other form of storage medium known in the art. Wherein the computer program, when executed by a processor, implements the aforementioned software fault detection method. For specific steps of the method, reference may be made to the corresponding contents disclosed in the foregoing embodiments, and no further description is given here.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, so that the same or similar parts between the embodiments are referred to each other. For the device disclosed in the embodiment, since the device corresponds to the software fault detection method disclosed in the embodiment, the description is relatively simple, and the relevant parts refer to the description of the method section.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of an algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing has described in detail the method, apparatus, device and medium for detecting software faults, and specific examples have been used herein to illustrate the principles and embodiments of the present invention, and the above examples are only for aiding in understanding the method and core idea of the present invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Claims (9)
1. A software fault detection method, applied to a server, comprising:
acquiring a plurality of groups of original detection data which are sent by equipment and comprise an object identifier of a detection object, a detection item and a detection state corresponding to the detection item; the original detection data are data obtained after the equipment detects the detection object by utilizing local software;
retrieving target detection data with abnormal detection states from the plurality of groups of original detection data, and determining faults in the software according to the detection items in the target detection data and the object identifiers;
wherein the determining the fault in the software according to the detection item in the target detection data and the object identifier includes:
determining all original detection data which comprise the same object identifier with the target detection data, and searching whether error flows exist in detection flows corresponding to the detection items in all the original detection data;
and if the detection process corresponding to the detection item does not have an error process, determining a fault in the software by using the target item and the object identifier in the target detection data.
2. The software fault detection method according to claim 1, wherein the acquiring the sets of raw detection data including the object identifier of the detection object, one detection item, and the detection state corresponding to the detection item sent by the device includes:
acquiring a detection log file sent by equipment, and analyzing the detection log file to acquire a plurality of character strings;
and analyzing each character string to obtain a plurality of groups of original detection data comprising an object identifier of a detection object, a detection item and a detection state corresponding to the detection item.
3. The software fault detection method according to claim 2, wherein the obtaining the detection log file sent by the device includes:
and acquiring detection log files sent by equipment, and receiving and recording the character strings through a preset data interface in advance.
4. The software fault detection method according to claim 2, wherein the obtaining the detection log file sent by the device and parsing the detection log file includes:
and acquiring a detection log file sent by the equipment, searching whether the detection log file which is not analyzed exists locally according to a preset period, and then analyzing the detection log file which is not analyzed.
5. The software fault detection method according to any one of claims 1 to 4, wherein after the fault in the software is determined from the detection item and the object identification in the target detection data, further comprising:
and adjusting the detection state in the target detection data from abnormal detection to normal detection.
6. A software fault detection device, applied to a server, comprising:
the detection data acquisition module is used for acquiring a plurality of groups of original detection data which are sent by equipment and comprise object identifiers of detection objects, detection items and detection states corresponding to the detection items; the original detection data are data obtained after the equipment detects the detection object by utilizing local software;
the fault determining module is used for retrieving target detection data with the detection state of detection abnormality from the plurality of groups of original detection data and determining faults in the software according to the detection items in the target detection data and the object identifiers;
wherein, the trouble determination module includes:
a process searching unit, configured to determine that all the original detection data that includes the same object identifier as the target detection data, and search whether an error process exists in detection processes corresponding to the detection items in all the original detection data;
and the fault determining unit is used for determining faults in the software by utilizing the target item and the object identifier in the target detection data if no error flow exists in the detection flow corresponding to the detection item.
7. The software fault detection device of claim 6, wherein the detection data acquisition module comprises:
the first analysis unit is used for acquiring a detection log file sent by the equipment and analyzing the detection log file to acquire a plurality of character strings;
and the second analysis unit is used for analyzing each character string to acquire a plurality of groups of original detection data comprising an object identifier of a detection object, a detection item and a detection state corresponding to the detection item.
8. An electronic device comprising a processor and a memory; wherein the processor, when executing the computer program stored in the memory, implements the software fault detection method according to any one of claims 1 to 5.
9. A computer-readable storage medium storing a computer program; wherein the computer program, when executed by a processor, implements a software failure detection method according to any of claims 1 to 5.
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