CN114281644A - Application monitoring method, application monitoring device, storage medium and electronic equipment - Google Patents
Application monitoring method, application monitoring device, storage medium and electronic equipment Download PDFInfo
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Abstract
The disclosure provides an application monitoring method and device, a computer readable storage medium and electronic equipment, and relates to the technical field of computers. The application monitoring method comprises the following steps: determining at least two application versions to be monitored of a target application; acquiring terminal data corresponding to each application version to be monitored, wherein the terminal data corresponding to the application version to be monitored are collected from a terminal provided with the application version to be monitored of the target application; analyzing the terminal data to obtain monitoring index data of each application version to be monitored; and determining the monitoring result of the target application by comparing the monitoring index data of different versions of the application to be monitored. The method and the device can monitor a plurality of application versions of the target application, and are beneficial to finding out abnormal problems caused by update iteration of the application versions.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to an application monitoring method, an application monitoring apparatus, a computer-readable storage medium, and an electronic device.
Background
With the development of electronic devices, the variety and number of applications installed on the electronic devices are increasing, and when there is an abnormality in the applications, the normal use of the electronic devices will be affected. For example, the power consumption of an application is too high, resulting in significant heating of the electronic device. Therefore, it is necessary to monitor the application.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those skilled in the art.
Disclosure of Invention
The present disclosure provides an application monitoring method, an application monitoring apparatus, a computer-readable storage medium, and an electronic device, so as to implement effective monitoring of an application.
According to a first aspect of the present disclosure, there is provided an application monitoring method, including: determining at least two application versions to be monitored of a target application; acquiring terminal data corresponding to each application version to be monitored, wherein the terminal data corresponding to the application version to be monitored are collected from a terminal provided with the application version to be monitored of the target application; analyzing the terminal data to obtain monitoring index data of each application version to be monitored; and determining the monitoring result of the target application by comparing the monitoring index data of different versions of the application to be monitored.
According to a second aspect of the present disclosure, there is provided an application monitoring apparatus comprising: the monitoring system comprises a to-be-monitored application version determining module, a monitoring module and a monitoring module, wherein the to-be-monitored application version determining module is configured to determine at least two to-be-monitored application versions of a target application; the terminal data acquisition module is configured to acquire terminal data corresponding to each application version to be monitored, and the terminal data corresponding to the application version to be monitored are collected from a terminal provided with the application version to be monitored of the target application; the terminal data analysis module is configured to analyze the terminal data to obtain monitoring index data of each application version to be monitored; and the monitoring index comparison module is configured to determine a monitoring result of the target application by comparing monitoring index data of different versions of the application to be monitored.
According to a third aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the application monitoring method of the first aspect described above and possible implementations thereof.
According to a fourth aspect of the present disclosure, there is provided an electronic device comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the application monitoring method of the first aspect and possible implementations thereof via execution of the executable instructions.
The technical scheme of the disclosure has the following beneficial effects:
on one hand, the method and the device can monitor a plurality of application versions of the target application, and are beneficial to finding out abnormal problems generated by update iteration of the application versions, so that effective and sufficient application monitoring is realized. On the other hand, by means of collecting and analyzing terminal data and comparing monitoring index data, abnormal problems can be found early, so that measures can be taken as early as possible, and user experience is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is apparent that the drawings in the following description are only some embodiments of the present disclosure, and that other drawings can be derived from those drawings without inventive effort for those skilled in the art.
FIG. 1 shows a schematic diagram of a system architecture in the present exemplary embodiment;
FIG. 2 illustrates a flow chart of a method of application monitoring in the exemplary embodiment;
FIG. 3 shows a schematic diagram of an application version in the present exemplary embodiment;
FIG. 4 illustrates a flow chart for determining stable users in the exemplary embodiment;
FIG. 5 illustrates a flow chart for determining monitoring results in the exemplary embodiment;
FIG. 6 illustrates a flow chart of a method of application monitoring in the exemplary embodiment;
FIG. 7 shows a schematic diagram of three phases of an application monitoring method in the present exemplary embodiment;
fig. 8 is a schematic structural diagram showing an application monitoring apparatus in the present exemplary embodiment;
fig. 9 shows a schematic configuration diagram of an electronic apparatus in the present exemplary embodiment; .
Detailed Description
Exemplary embodiments of the present disclosure will now be described with reference to the accompanying drawings. The exemplary embodiments, however, may be embodied in many different forms and should not be construed as limited to the examples set forth herein. These embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
In the related art, a problem is found and analyzed based on feedback of a user in many cases. For example, a user feedback path is provided, and the user can feed back abnormal phenomena such as heating and jamming, and when receiving the feedback, the user logs are collected and problems are analyzed based on a specific use scene, an operation state and the like of the user. However, the active feedback of the user indicates that the related phenomena are relatively serious, and at this time, the problem is analyzed and solved, so that high hysteresis exists, and the user experience is influenced.
In view of the above, exemplary embodiments of the present disclosure provide an application monitoring method. The system architecture and application scenario of the operating environment of the exemplary embodiment are described below with reference to fig. 1.
Fig. 1 shows a schematic diagram of a system architecture, and the system architecture 100 may include a terminal 110 and a server 120. The terminal 110 may be a terminal device such as a smart phone, a tablet computer, a desktop computer, or a notebook computer, and the server 120 generally refers to a background system providing application monitoring related services in the exemplary embodiment, and may be a server or a cluster formed by multiple servers. The terminal 110 and the server 120 may form a connection through a wired or wireless communication link for data interaction.
In one embodiment, the server 120 may perform the application monitoring method in the present exemplary embodiment. For example, the server 120 collects terminal data from the terminal 110, and performs monitoring on a target application on the terminal 110 through analysis of the terminal data. Therefore, the execution subject of the application monitoring method in the present exemplary embodiment may be the server 120, but the present disclosure does not limit this.
The following describes an application monitoring method in the present exemplary embodiment with reference to fig. 2, where fig. 2 shows an exemplary flow of the application monitoring method, and may include:
step S210, determining at least two application versions to be monitored of a target application;
step S220, acquiring terminal data corresponding to each application version to be monitored, wherein the terminal data corresponding to the application version to be monitored is collected from a terminal provided with the application version to be monitored of the target application;
step S230, analyzing the terminal data to obtain monitoring index data of each application version to be monitored;
step S240, determining a monitoring result of the target application by comparing the monitoring index data of different versions of the application to be monitored.
Based on the method, on one hand, a plurality of application versions of the target application can be monitored, and the abnormal problem caused by the update iteration of the application versions can be found, so that the effective and sufficient application monitoring is realized. On the other hand, by means of collecting and analyzing terminal data and comparing monitoring index data, abnormal problems can be found early, so that measures can be taken as early as possible, and user experience is improved.
Each step in fig. 2 is explained in detail below.
In step S210, at least two to-be-monitored application versions of the target application are determined.
Wherein the target application is an application that needs to be monitored. The present exemplary embodiment may target any one or more applications.
In an embodiment, before determining at least two versions of the target application to be monitored, the application monitoring method may further include the following steps:
acquiring application heat data of a plurality of applications;
and determining the target application from the plurality of applications according to the application heat data.
Wherein the plurality of applications may be all applications or all applications within a range. For example, the plurality of applications may be all applications in an App (Application) store, all applications in a certain model, all applications in a certain system, or the like. The application heat data is used to indicate the heat of a certain application, i.e., the degree to which a certain application is used or is focused on. The application heat data may include one or more heat indicator values, such as:
the number of users of the application refers to the number of users or equipment with a certain application installed;
the number of active users of an application refers to the number of users or devices using a certain application within a predetermined time range (e.g., the current day), and the present disclosure does not limit the criteria for determining whether to use the application, for example, opening the application may be regarded as a use, and using the application for a period of time longer than 5 minutes may be regarded as a use;
the application penetration rate refers to the ratio of the number of active users (or users) of a certain application to the number of all active users or all active users within a certain range (such as all active users in a certain system version).
In addition, other index values that reflect the heat of application may be employed.
In one embodiment, m applications with the highest heat index value may be determined as target application versions, where m is a positive integer. The value of m may be determined empirically, based on actual requirements or conditions, etc. For example, when a service party (e.g., user-oriented application anomaly early warning service) needs to perform comprehensive application monitoring, or when background service resources are sufficient, a larger m value can be set to obtain more target applications, so as to monitor a larger number of applications.
In an embodiment, the determining the target application from the plurality of applications according to the application heat data may include:
and determining the application with the heat index value exceeding the application heat threshold value as the target application.
The application heat threshold is used for screening out the application with the higher heat index value as the target application, so that the heat of the target application is guaranteed. The application heat threshold may be determined based on experience, actual demand or actual conditions, etc.
In an embodiment, the determining the target application from the plurality of applications according to the application heat data may further include:
and determining an application heat threshold according to the average value and the standard deviation of the heat index values of the plurality of applications.
For example, the application heat threshold may be calculated by the following formula (1):
Tapp＝avgapp+k1·σapp (1)
wherein, TappIndicating the application heat threshold, avgappRepresenting the average, σ, of the index values of heat for a plurality of applicationsappThe standard deviation of the heat index values representing a plurality of applications, k1 being a first coefficient, may be determined as a function of experience, actual demand or actual conditions, etc. the value of k1 may be determined. In general, the smaller the value of k1, the smaller the application heat threshold and the greater the number of target applications. For example, when a service party needs to monitor more comprehensive applications or when background service resources are sufficient, a smaller value of k1 may be set to obtain more target applications, thereby monitoring more applications.
In one embodiment, may be in the range of [ -1,1 [ ]]Is determined, e.g., the value of k1 may be-1, then Tapp＝avgapp-σapp。
The target applications are screened out in a mode of applying the heat threshold, and the target applications can be guaranteed to be all applications with certain heat, so that the monitoring of the target applications can be guaranteed to finally provide services for a huge user group.
In one embodiment, a numerical range of the application heat data may be set, and an application in which the application heat data is in the numerical range may be determined as a target application. The range of values may be determined empirically, based on actual needs or conditions, and the like, and may be, for example, [ avg ]app-f1·σapp,avgapp+f1·σapp]F1 is a coefficient greater than 0, and the larger the value, the larger the numerical range, the larger the number of target applications.
In an embodiment, the obtaining of the application heat data of the plurality of applications may include:
and acquiring application heat data of a plurality of applications under the version of the system to be monitored.
The system version refers to a version of an operating system of the device, and the operating systems such as Android and iOS on the mobile terminal all have a plurality of different system versions. Illustratively, The update of The system version of The mobile terminal may be implemented based on an OTA (Over The Air, Over-The-Air technology) manner, and thus The system version may be referred to as an OTA version. The system version to be monitored is a system version to be monitored, and monitoring of the system version may include monitoring of an application under the system version. The system version to be monitored can be an important system version or a latest system version, etc. The number of versions of the system to be monitored and the manner of determining the versions of the system to be monitored are not limited in the present disclosure.
In an embodiment, before the obtaining of the application heat data of the plurality of applications in the version of the system to be monitored, the application monitoring method may further include the following steps:
acquiring system version heat data of a plurality of system versions;
and determining the version of the system to be monitored from the plurality of system versions according to the system version heat data.
Wherein the plurality of system versions may be all system versions or all system versions within a range. For example, the multiple system versions may be all system versions after a critical system version, or multiple major system versions, etc. The system version popularity data is used to indicate the popularity of a certain system version, i.e., the degree to which a certain system version is used or attended to. The system version heat data may include one or more heat indicator values, such as:
the number of users of the system version refers to the number of users or equipment with a certain system version installed;
the number of active users of a system version refers to the number of users or devices using a certain system version within a predetermined time range (such as the current day);
the penetration rate of a system version refers to the ratio of the number of active users (or users) of a certain system version to the number of all active users or all active users within a certain range (such as all active users under a certain model).
In addition, other index values that reflect the popularity of the system version may be used.
In one embodiment, the n system versions with the highest heat index values may be determined as the system versions to be monitored, where n is a positive integer. The value of n may be determined empirically, based on actual requirements or conditions, etc. For example, when a service side needs to perform application monitoring under more system versions, or when background service resources are sufficient, a larger n value may be set to obtain more system versions to be monitored, so as to monitor a larger number of system versions.
In an embodiment, the determining a system version to be monitored from the plurality of system versions according to the system version heat data may include:
and determining the system version with the heat index value exceeding the heat threshold of the system version as the system version to be monitored.
The system version popularity threshold is used for screening out the system version with the high popularity index value to serve as the system version to be monitored, and therefore popularity of the system version to be monitored is guaranteed. The system version heat threshold may be determined based on experience, actual demand or actual conditions, and the like.
In an embodiment, the determining a system version to be monitored from the plurality of system versions according to the system version heat data may further include:
and determining a system version heat threshold according to the average value and the standard deviation of the heat index values of the plurality of system versions.
For example, the system version hotness threshold may be calculated by the following equation (2):
Tos_ver＝avgos_ver+k2·σos_ver (2)
wherein, Tos_verIndicating the system version hotness threshold, avgos_verMean value, σ, of heat index values representing multiple system versionsos_verRepresenting the standard deviation of the heat index values of multiple system versions, k2 is a second coefficient, and the value of k2 can be determined according to experience, actual demand or actual conditions, and the like. Generally, the smaller the value of k2, the smaller the system version heat threshold, and the greater the number of system versions to be monitored. For example, when a business side needs to perform application monitoring under more system versions, or when background service resources are sufficient, a smaller value of k2 may be set to obtain more system versions to be monitored, so as to monitor a greater number of system versions.
In one embodiment, can be in[-1,1]Is determined, e.g., the value of k2 may be-1, then Tos_ver＝avgos_ver-σos_ver。
The versions of the system to be monitored are screened out in a mode of applying the heat threshold, so that the versions of the system to be monitored can be guaranteed to be all applied with certain heat. Furthermore, the application heat data is obtained under the version of the system to be monitored so as to determine the target application, and the heat of the target application can be ensured. Therefore, monitoring of the target application can be guaranteed to provide service for a large user group finally.
In one embodiment, a numerical range of the system version heat data may be set, and the system version with the system version heat data in the numerical range may be determined as the system version to be monitored. The range of values may be determined empirically, based on actual needs or conditions, and the like, and may be, for example, [ avg ]os_ver-f2·σos_ver,avgos_ver+f2·σos_ver]F2 is a coefficient greater than 0, and the larger the value, the larger the value range, the larger the number of versions of the system to be monitored.
In one embodiment, the system version heat data may include a permeability of the system version. The determining the system version to be monitored from the plurality of system versions according to the system version heat data may include the following steps:
and according to the sequence of the permeability of the system versions from high to low, sequentially marking each system version as a system version to be monitored until the sum of the permeability of the marked system versions to be monitored reaches a system version permeability threshold.
Wherein the system version permeability threshold may be determined based on experience, actual demand, or actual conditions. And sequentially adding each system version as the system version to be monitored according to the sequence of the permeability from high to low. When the sum of the permeabilities of the system versions to be monitored reaches the permeability threshold of the system versions, the system versions to be monitored can be considered to cover enough users, and the rest of the system versions are non-system versions to be monitored. Furthermore, it can be ensured that the application monitoring method can cover enough users.
Under the condition that the version of the system to be monitored is determined, the application heat data of the plurality of applications under the version of the system to be monitored can be acquired. In one aspect, the plurality of applications may be limited to the scope of the system version to be monitored, that is, the plurality of applications may be applications in the system version to be monitored. On the other hand, the application heat data is the application heat data in the version of the system to be monitored, which means that the application heat data in other system versions can not be considered. Therefore, the range of the plurality of applications and the application heat data is reduced, and the processing efficiency is improved.
In the version of the system to be monitored, the statistical mode of the application heat data can be adaptively adjusted. For example, the penetration of an application may be the percentage of the number of active users of an application in a system version to be monitored over all active users in the system version to be monitored.
In an embodiment, when a plurality of versions of the system to be monitored are determined, the application heat data of each application may be acquired and counted under each version of the system to be monitored, and the target application may be determined under each version of the system to be monitored. For example, the system versions to be monitored include system versions OSv1 and OSv2, the heat data of application a and application B are counted under OSv1 and OSv2, respectively, and if the heat of application a is higher under OSv1 and the heat of application B is higher under OSv2, application a is determined to be the target application under OSv1, and application B is determined to be the target application under OSv 2.
The application generally has a plurality of versions, and the present exemplary embodiment refers to the version of the application as an application version to distinguish it from the system version above. The application version to be monitored refers to an application version to be monitored in each version of the target application, and may be an important application version or a latest application version.
Referring to fig. 3, an a game is targeted for use. Game a has multiple application versions shown in the figure, v1.0.0 denotes a version number, including three levels of application version numbers: the first bit is the major version number, the second bit is the minor version number, and the third bit is the patch version number. The version number of any bit can be accurately obtained when the application version is divided. For example, each patch version number may be considered as one application version, such as treating v1.0.0, v1.0.1, v1.0.2 as three different application versions. Or, each sub-version number may be used as an application version, for example, v1.0.0, v1.0.1, and v1.0.2 are regarded as an application version, so that different patch versions under the sub-versions can be monitored and managed uniformly. Or, each main version number may be used as an application version, for example, v1.0.0-v1.2.3 is regarded as an application version, so that different sub-versions and patch versions under the main version can be monitored and managed uniformly.
In an embodiment, the determining at least two versions of the target application to be monitored may include the following steps:
acquiring application version heat data of a plurality of application versions of a target application;
and determining the application version to be monitored from the plurality of application versions according to the application version heat data.
Wherein the plurality of application versions of the target application may be all application versions of the target application or all application versions within a range. For example, the plurality of application versions may be all application versions after a certain critical application version of the target application. The application version popularity data is used to represent the popularity of a certain application version of the target application, i.e. the extent to which a certain application version is used or attended to. The application version popularity data may include one or more popularity indicator values, such as:
the number of users of the application version refers to the number of users or equipment of a certain application version of the installed target application;
the number of active users of the application version refers to the number of users or devices using a certain application version of the target application within a predetermined time range (such as the current day), and the present disclosure does not limit the criteria for determining whether to use, for example, opening the application version of the target application may be regarded as used, and the duration of using the application version of the target application exceeds 5 minutes may be regarded as used, etc.;
the penetration rate of an application version refers to the ratio of the number of active users (or users) of a certain application version to the number of all active users or all active users within a certain range (such as all active users in a certain system version).
In addition, other index values that reflect the popularity of the application version may be used.
In an embodiment, the p application versions with the highest value of the heat index among the multiple application versions may be determined as the application version to be monitored, where p is a positive integer not less than 2. The value of p may be determined empirically, based on actual requirements or actual conditions, etc. For example, when a business side needs to perform comprehensive application monitoring or a background service resource is sufficient, a larger p value can be set to obtain more application versions to be monitored, and then a larger number of application versions are monitored.
In an embodiment, the determining, according to the application version popularity data, an application version to be monitored from the plurality of application versions may include the following steps:
and determining the application version with the heat index value exceeding the heat threshold of the application version as the application version to be monitored.
The application version popularity threshold is used for screening out the application version with a high popularity index value to serve as the application version to be monitored, and therefore popularity of the application version to be monitored is guaranteed. The application version hotness threshold may be determined based on experience, actual demand or actual conditions, etc.
In an embodiment, the determining, according to the application version popularity data, an application version to be monitored from the plurality of application versions may further include:
and determining the hot degree threshold of the application version according to the average value and the standard deviation of the hot degree index values of the plurality of application versions.
For example, the heat threshold may be calculated by the following equation (3):
Tapp_ver＝avgapp_ver+k3·σapp_ver (3)
wherein, Tapp_verIndicating the application version hotness threshold, avgapp_verAverage of heat index values representing multiple application versionsValue σapp_verRepresenting the standard deviation of the heat index values of multiple application versions, k3 is a third coefficient, and the value of k3 can be determined according to experience, actual demand or actual conditions, and the like. In general, the smaller the value of k3, the smaller the application version hot threshold, and the greater the number of application versions to be monitored. For example, when a business party needs to perform comprehensive application monitoring or when background service resources are sufficient, a smaller value of k3 may be set to obtain more application versions to be monitored, so as to monitor a larger number of application versions.
In one embodiment, may be in the range of [ -1,1 [ ]]Is determined, e.g., the value of k3 may be 1, then Tapp_ver＝avgapp_ver+σapp_ver。
The target application is screened out in the mode of the popularity threshold of the application version, and the application versions to be monitored can be guaranteed to be all application versions with certain popularity, so that the monitoring of the application versions to be monitored can be guaranteed to finally provide service for a huge user group.
In one embodiment, a numerical range of the application version popularity data may be set, and the application version with the application version popularity data in the numerical range may be determined as the application version to be monitored. The range of values may be determined empirically, based on actual needs or conditions, and the like, and may be, for example, [ avg ]app_ver-f3·σapp_ver,avgapp_ver+f3·σapp_ver]F3 is a coefficient greater than 0, and the larger the value, the larger the numerical range, the larger the number of versions of the application to be monitored.
In one embodiment, the heat data for each version of the target application may include application version permeability. The determining the version of the application to be monitored from the versions of the target application according to the heat data of the versions of the target application may include the following steps:
and according to the sequence of the permeability of the plurality of application versions from high to low, sequentially marking each application version as an application version to be monitored until the sum of the permeability of the marked application versions to be monitored reaches an application version permeability threshold.
Wherein the application version permeability threshold may be determined based on experience, actual demand, or actual conditions. And sequentially adding each application version as the application version to be monitored according to the sequence of the permeability from high to low. When the sum of the permeabilities of the application versions to be monitored reaches the permeability threshold of the application versions, it can be considered that the application versions to be monitored cover enough users, and the rest of the application versions are non-application versions to be monitored. Furthermore, it can be ensured that the application monitoring method can cover enough users.
In an embodiment, the obtaining of the application version popularity data of the plurality of application versions of the target application may include the following steps:
and acquiring the application version hot data of the plurality of application versions under the version of the system to be monitored.
Therefore, on one hand, the plurality of application versions can be limited within the range of the system version to be monitored, that is, the plurality of application versions can be the application versions in the system version to be monitored. On the other hand, the application version hot degree data is the application version hot degree data under the system version to be monitored, which means that the application version hot degree data under other system versions can not be considered. Therefore, the range of the plurality of application versions and the range of the hot data of the application versions are reduced, and the processing efficiency is improved.
Under the version of the system to be monitored, the statistical mode of the heat data of the application version can be adaptively adjusted. For example, the penetration rate of an application version may be the percentage of the number of active users of an application version under the system version to be monitored among all active users under the system version to be monitored.
In an embodiment, when a plurality of versions of the system to be monitored are determined, the application version heat data of each application version may be acquired and counted under each version of the system to be monitored, and the application version to be monitored is determined under each version of the system to be monitored. For example, the system versions to be monitored include system versions OSv1 and OSv2, the heat data of the application versions v1.0 and v2.0 of the target application are counted under OSv1 and OSv2, respectively, if the heat of the application version v1.0 is higher under OSv1 and the heat of the application version v2.0 is higher under OSv2, the application version v1.0 is determined to be the application version to be monitored under OSv1, and the application version v2.0 is determined to be the application version to be monitored under OSv 2.
With continued reference to fig. 2, in step S220, terminal data corresponding to each application version to be monitored is obtained, and the terminal data corresponding to the application version to be monitored is collected from the terminal of the application version to be monitored, on which the target application is installed.
For example, after v1.1.3 and v2.0.0 of the game a in fig. 3 are determined as two versions of the application to be monitored, terminal data corresponding to v1.1.3 may be collected from a terminal installed with the game a v1.1.3, and terminal data corresponding to v2.0.0 may be collected from a terminal installed with the game a v 2.0.0.
The terminal data is data for reflecting the operation state of the terminal. The present disclosure is not limited to the kind of terminal data, and may be determined according to a specific monitoring purpose. For example, in order to monitor whether the target application may affect the normal use of the terminal, the acquired terminal data may include: the terminal runs temperature data, power consumption data (such as electric quantity data), processor occupation data, memory occupation data, network occupation data, communication signal data and the like when the application version to be monitored of the target application runs.
In an embodiment, terminal data corresponding to each version of the application to be monitored in the version of the system to be monitored may be obtained. That is, terminal data may be collected from a terminal that installs the version of the application to be monitored under the version of the system to be monitored.
In an embodiment, the obtaining terminal data corresponding to each application version to be monitored may include:
determining a stable user group corresponding to each application version to be monitored;
and acquiring terminal data of a stable user group.
The stable user group refers to a user group which stably uses a certain application version to be monitored of the target application. A corresponding stable user group can be determined for each application version to be monitored, and terminal data corresponding to the application version to be monitored is collected from the stable user group. Therefore, the influence of unstable users is eliminated, and the monitoring of the target application is more accurate and effective.
The screening condition of the stable user group is not limited in the present disclosure, and can be determined according to the specific situation of the target application. In an embodiment, the determining a stable user group corresponding to each application version to be monitored may include the following steps:
and adding the users who use the version of the application to be monitored in the first preset time range and do not change the version of the target application in the second preset time range into a stable user group corresponding to the version of the application to be monitored.
The first preset time range and the second preset time range may both use the current time as an end point, and the second preset time range may be greater than the first preset time range. For example, the first predetermined time range may be the current day or the last 24 hours, and the second predetermined time range may be the current day and the previous day or the last 48 hours. Taking fig. 4 as an example for explanation, the process of screening stable users includes:
step S401, obtaining a user list for installing the application version v1.0 to be monitored;
step S402, judging whether the user uses the application version v1.0 to be monitored on the same day, if so, continuing to execute the judgment of the step S403 on the user, and if not, determining the user as an unstable user;
step S403, determining whether the user has performed version change with the previous day, if yes, determining the user as an unstable user, and if not, determining the user as a stable user, and adding the stable user into a stable user group corresponding to the application version v1.0 to be monitored.
By the above conditions, users who have not used the version of the application to be monitored recently and have made version changes of the target application recently are effectively excluded. The reference value of the terminal data of the user who has not used the version of the application to be monitored in the recent time is not high, and the user who has performed the version change of the target application in the recent time may have unstable use, for example, the process of the version change may cause the fluctuation of the terminal data, and the terminal data needs to be excluded. Therefore, the terminal data of the stable user group has high referential performance.
With continued reference to fig. 2, in step S230, the terminal data is analyzed to obtain monitoring index data of each application version to be monitored.
The monitoring index data is used for representing the performance of the to-be-monitored application version of the target application, and may include temperature rise index data, power consumption index data, processor resource occupation index data, storage resource occupation index data, network bandwidth occupation index data and the like. In the exemplary embodiment, monitoring index data of each application version to be monitored is obtained by counting and analyzing a large amount of terminal data. The present disclosure is not limited to the analysis method. Illustratively, for the application version v1.0 to be monitored, terminal data of a stable user of the application version v1.0 is obtained, different index data in the terminal data are respectively summarized and counted, monitoring index data of the application version v1.0 to be monitored are obtained according to a counting result, for example, outliers can be removed from the terminal data, and then an average value is calculated to serve as a numerical value of a corresponding monitoring index.
With continued reference to fig. 2, in step S240, the monitoring result of the target application is determined by comparing the monitoring index data of different versions of the application to be monitored.
For example, if a difference between different application versions to be monitored is too large (e.g., exceeds a threshold value between versions corresponding to the monitoring index data), it indicates that the difference between the application versions to be monitored is too large, and at least one of the application versions to be monitored has an abnormality. Thereby obtaining the corresponding monitoring result of the abnormal version of the application to be monitored.
In addition, the monitoring index data of each application version to be monitored can be managed, if the monitoring index data of each application version to be monitored does not exceed the corresponding normal numerical range, otherwise, the application version to be monitored is abnormal.
In an embodiment, the determining the monitoring result of the target application by comparing the monitoring index data of different versions of the application to be monitored may include the following steps:
and determining that at least one of the application versions to be monitored is abnormal in response to the fact that the difference between the monitoring index data of the two application versions to be monitored is larger than the monitoring threshold of the monitoring index data.
The monitoring threshold is a difference threshold set for each monitoring index, that is, the difference between the monitoring index data of different application versions to be monitored should be within the monitoring threshold. The monitoring threshold may be determined based on empirical or practical requirements, which are not limited by this disclosure. For example, for the application versions v1.0 and v2.0 to be monitored, if the difference between the temperature rise index data of v1.0 and the temperature rise index data of v2.0 is greater than the monitoring threshold of temperature rise, the application version to be monitored, in which the temperature rise index data is higher, is determined as the abnormal version.
It should be understood that the difference between the monitoring index data may be an absolute difference of the monitoring index values, or may be a relative difference, for example, Δ T (v1.0) represents the temperature rise index data of the application version to be monitored v1.0, Δ T (v2.0) represents the temperature rise index data of the application version to be monitored v2.0, and the difference between the two may be | Δ T (v1.0) - Δ T (v2.0) |, or may be | Δ T (v1.0) - Δ T (v2.0) |
When the comparison is performed, if the difference between the monitoring index data is too large, the version of the application to be monitored with poor monitoring index data is usually determined as an abnormal version. In one embodiment, considering that sometimes better monitoring index data may be caused by the target application not actually performing a certain function or functions, both of the compared versions of the application to be monitored may be determined as abnormal versions for further analysis.
In an embodiment, as shown in fig. 5, the above determining the monitoring result of the target application by comparing the monitoring index data of different versions of the application to be monitored may include the following steps S510 and S520:
step S510, determining at least one comparable version group in the application version to be monitored according to the application version heat data of the application version to be monitored;
step S520, comparing the monitoring index data of different versions to be monitored in the contrastable version group, and determining a monitoring result of the target application.
The difference between the application version heat data of any two application versions to be monitored in the version group can be compared to be smaller than a heat balance threshold. The heat balance threshold is a threshold for the heat difference of different application versions to be monitored, so as to ensure that the heat difference of two application versions to be monitored for comparison is not too large. The heat balance threshold may be determined based on experience, actual demand, or actual conditions, which are not limited by this disclosure. Illustratively, for the application versions v1.0 and v2.0 to be monitored, if the difference between the application version heat data of v1.0 and the application version heat data of v2.0 is less than the heat balance threshold, v1.0 and v2.0 are formed into a contrastable version group.
It should be understood that the difference between the heat data of the application version may be an absolute difference of the heat index values, or may be a relative difference, for example, S (v1.0) represents the heat index value of the application version to be monitored v1.0 (such as permeability of the application version), S (v2.0) represents the heat index value of the application version to be monitored v2.0, and the difference between the two may be | S (v1.0) -S (v2.0) |, or may be | S (v1.0) -S (v2.0) |
In particular, when a relative difference is used, a heat balance threshold of 0.5 may be set.
And generating a contrastable version group by setting a heat balance threshold value, and further performing contrast on monitoring index data of different application versions to be monitored in the contrastable version group. Therefore, the balance between the compared application versions to be monitored is ensured, the overlarge heat difference of the compared application versions to be monitored is avoided, and the effectiveness of application monitoring is improved.
In one embodiment, the application monitoring method may further include:
and generating prompt information about the abnormal application version to be monitored in response to the monitoring result indicating that at least one application version to be monitored of the target application is abnormal.
Wherein, the prompt message can be used for pushing to the related service party. For example, the service party may be a user-oriented application exception early warning service party, which may perform early warning on a terminal installed with the exception application version to be monitored according to the prompt information. Or, the business party may be a developer of the target application, and may check and improve the abnormal version of the application to be monitored according to the prompt information.
In an implementation manner, the prompt message may also be used to send to the terminal installed with the abnormal application version to be monitored, so that the user may be prompted in time. For example, when an old version of the target application is abnormal, the user may be reminded to update to the new version of the target application in time.
Fig. 6 shows a schematic flow of the application monitoring method in the present exemplary embodiment, including:
step S601, system version heat data of a plurality of system versions are obtained;
step S602, judging whether the system version heat data of each system version meets the requirement, if so, determining the system version as the system version to be monitored, and if not, not monitoring the system version;
step S603, acquiring application heat data of a plurality of applications under the version of the system to be monitored;
step S604, judging whether the application heat data of each application meets the requirement, if so, determining the application as a target application, and if not, not monitoring the application;
step S605, acquiring application version heat data of a plurality of application versions of the target application under the version of the system to be monitored;
step S606, judging whether the application version heat data of each application version meets the requirement, if so, determining the application version as the application version to be monitored, and if not, not bringing the application version into monitoring;
step S607, determining a stable user group corresponding to the application version to be monitored, acquiring terminal data of the stable user group, and analyzing the terminal data to obtain monitoring index data;
step S608, determining whether the difference between the heat data of the application versions of different application versions to be monitored meets the requirement, if yes, comparing the monitoring index data of the different application versions to be monitored to perform monitoring, and if not, not comparing.
In one embodiment, the application monitoring method may be performed periodically, for example once a day. Referring to fig. 7, the specific implementation flow of application monitoring can be divided into three main stages:
in the first stage, a data table of information to be monitored is designed.
Table 1 shows a monitoring index data table, which mainly records monitoring index information of different application versions of different applications under different system versions. In table 1, the temperature rise (heat generation) index is used as a monitoring index. The data of table 1 may be derived from a heat-related data fact table that distinguishes the application versions.
TABLE 1
Table 2 shows a system version data table, which mainly records information of system version heat data (including number of active people, permeability, etc.) of different system versions. The data of Table 2 may be derived from a daily fact table that records user application usage.
TABLE 2
| Name of field | Meaning of a field | Type of field |
| dayno | Date | Character string |
| model_type | Model name (model code) | Character string |
| ota_version | System version | Character string |
| model_cnt | Number of machine type people | Integer number of |
| ota_cnt | Number of active people in system version | Integer number of |
| ota_ratio | Permeability of system version | Floating point number |
Table 3 shows an application data table, which mainly records information of application heat data (including the number of active people, permeability, etc.) of each application in different system version ranges. The data of Table 3 may be derived from a daily fact table that records user application usage.
TABLE 3
| Name of field | Meaning of a field | Type of field |
| dayno | Date | Character string |
| model_type | Model name (model code) | Character string |
| ota_version | System version | Character string |
| app_name | Application name | Character string |
| ota_cnt | Number of active people in system version | Integer number of |
| app_cnt | Number of active people applying | Integer number of |
| app_ratio | Permeability of application | Floating point number |
Table 4 shows an application version data table, which mainly records information of application version heat data (including the number of active people, penetration rate, etc.) of different application versions of different applications in the range of different system versions. For example, two application versions with the largest number of active people in the target application may be screened out as the application versions to be monitored, and the two application versions are respectively represented as a new version new _ app _ ver and an old version old _ app _ ver. A gap indicator for the two application versions is determined. The data of Table 4 may be derived from a daily fact table that records user application usage.
TABLE 4
| Name of field | Meaning of a field | Type of field |
| dayno | Date | Character string |
| model_type | Model name (model code) | Character string |
| ota_version | System version | Character string |
| app_name | Application name | Character string |
| new_app_ver_cnt | Number of active people of new edition | Integer number of |
| new_app_ver_pack_name | New edition application package name (including version number) | Character string |
| old_app_ver_pack_name | Name of old version application package (including version number) | Character string |
| new_app_ver_ratio | Permeability of new edition | Floating point number |
| old_app_ver_cnt | Number of active people in old version | Integer number of |
| old_app_ver_ratio | Permeability of old version | Floating point number |
| app_ver_ratio_gap | Permeability gap between new and old versions | Floating point number |
Table 5 shows a to-be-monitored information data table, which mainly records monitoring index information of the to-be-monitored system version, the target application, and the to-be-monitored application version that meet the monitoring conditions every day. The data of table 5 can be derived from tables 1 and 4.
TABLE 5
And the second stage, data scheduling. A daily data table can be created by the associated script. To enable daily automated application monitoring, a first scheduling task may be established for daily updating of data in the data table. The first scheduling task may construct a cross-task dependency, that is, the first scheduling task may first identify whether the update of the previous table is completed, and then perform the update of the subsequent table when the update of the previous table is completed. In this exemplary embodiment, the monitoring index data table may be updated first, and the version data table of the system to be monitored, the target application data table, and the application version data table to be monitored may be updated in sequence, and then the information data table to be monitored may be updated according to the monitoring index data table and the application version data table to be monitored.
And in the third stage, pushing prompt information. And screening the application version to be monitored according to the model and the system version, constructing a daily early warning frame, and generating prompt information according to a monitoring result. For example, terminal data of a relevant model can be acquired, and whether abnormal heating fluctuation data exists in the current day or not can be determined through analysis, so that whether a heating risk exists in the application version to be monitored or not can be determined. Prompt information is generated according to the daily warning framework, and table data can be converted into a text form which is easy to understand. In order to realize daily automatic early warning and improve early warning efficiency, a second scheduling task can be established for automatically pushing prompt information to a service party every day.
Exemplary embodiments of the present disclosure also provide an application monitoring apparatus. Referring to fig. 8, the application monitoring apparatus 800 may include:
a to-be-monitored application version determination module 810 configured to determine at least two to-be-monitored application versions of a target application;
a terminal data obtaining module 820 configured to obtain terminal data corresponding to each application version to be monitored, where the terminal data corresponding to the application version to be monitored is collected from a terminal of the application version to be monitored, where the target application is installed;
the terminal data analysis module 830 is configured to analyze the terminal data to obtain monitoring index data of each application version to be monitored;
the monitoring index comparison module 840 is configured to determine a monitoring result of the target application by comparing monitoring index data of different versions of the application to be monitored.
In one embodiment, the application monitoring apparatus 800 may further include a target application determination module configured to:
acquiring application heat data of a plurality of applications;
and determining the target application from the plurality of applications according to the application heat data.
In an embodiment, the acquiring the application heat data of the plurality of applications includes:
and acquiring application heat data of a plurality of applications under the version of the system to be monitored.
In one embodiment, the application monitoring apparatus 800 may further include a system to be monitored version determination module configured to:
acquiring system version heat data of a plurality of system versions;
and determining the version of the system to be monitored from the plurality of system versions according to the system version heat data.
In an embodiment, the determining at least two versions of the target application to be monitored includes:
acquiring application version heat data of a plurality of application versions of a target application;
and determining the application version to be monitored from the plurality of application versions according to the application version heat data.
In an embodiment, the obtaining terminal data corresponding to each application version to be monitored includes:
determining a stable user group corresponding to each application version to be monitored;
and acquiring terminal data of a stable user group.
In an embodiment, the determining a stable user group corresponding to each application version to be monitored includes:
and adding the users who use the version of the application to be monitored in the first preset time range and do not change the version of the target application in the second preset time range into a stable user group corresponding to the version of the application to be monitored.
In an embodiment, the determining the monitoring result of the target application by comparing the monitoring index data of different versions of the application to be monitored includes:
determining at least one contrastable version group in the application version to be monitored according to the application version heat data of the application version to be monitored, wherein the difference of the application version heat data of any two application versions to be monitored in the contrastable version group is smaller than a heat balance threshold;
and determining the monitoring result of the target application by comparing the monitoring index data of different application versions to be monitored in the contrastable version group.
In an embodiment, the determining the monitoring result of the target application by comparing the monitoring index data of different versions of the application to be monitored includes:
and determining that at least one of the application versions to be monitored is abnormal in response to the fact that the difference between the monitoring index data of the two application versions to be monitored is larger than the monitoring threshold of the monitoring index data.
In one embodiment, the application monitoring apparatus 800 may further include a prompt information determination module configured to:
and generating prompt information about the abnormal application version to be monitored in response to the monitoring result indicating that at least one application version to be monitored of the target application is abnormal.
The specific details of each part in the above device have been described in detail in the method part embodiments, and details that are not disclosed may be referred to in the method part embodiments, and thus are not described again.
Exemplary embodiments of the present disclosure also provide a computer-readable storage medium, which may be implemented in the form of a program product, including program code for causing an electronic device to perform the steps according to various exemplary embodiments of the present disclosure described in the above-mentioned "exemplary method" section of this specification, when the program product is run on the electronic device. In an alternative embodiment, the program product may be embodied as a portable compact disc read only memory (CD-ROM) and include program code, and may be run on an electronic device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
Exemplary embodiments of the present disclosure also provide an electronic device, which may be, for example, the server 120 described above. The electronic device may include a processor and a memory. The memory stores executable instructions of the processor, such as may be program code. The processor performs the application monitoring method in the exemplary embodiment by executing the executable instructions, such as may perform the method steps of fig. 2.
Referring now to FIG. 9, an electronic device in the form of a general purpose computing device is illustrated. It should be understood that the electronic device 900 shown in FIG. 9 is only one example and should not be taken to limit the scope of use and functionality of embodiments of the present disclosure.
As shown in fig. 9, the electronic device 900 may include: a processor 910, a memory 920, a bus 930, an I/O (input/output) interface 940, and a network adapter 950.
The memory 920 may include volatile memory, such as RAM 921, a cache unit 922, and may also include non-volatile memory, such as ROM 923. Memory 920 may also include one or more program modules 924, such program modules 924 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment. For example, program modules 924 may include modules in apparatus 800 described above.
The bus 930 is used to enable connections between different components of the electronic device 900 and may include a data bus, an address bus, and a control bus.
The electronic device 900 may communicate with one or more external devices 1000 (e.g., keyboard, mouse, external controller, etc.) via the I/O interface 940.
The electronic device 900 may communicate with one or more networks through the network adapter 950, for example, the network adapter 950 may provide a mobile communication solution such as 3G/4G/5G, or a wireless communication solution such as wireless local area network, Bluetooth, near field communication, etc. The network adapter 950 may communicate with other modules of the electronic device 900 over the bus 930.
Although not shown in FIG. 9, other hardware and/or software modules may also be provided in the electronic device 900, including but not limited to: displays, microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functions of two or more modules or units described above may be embodied in one module or unit, according to exemplary embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
As will be appreciated by one skilled in the art, aspects of the present disclosure may be embodied as a system, method or program product. Accordingly, various aspects of the present disclosure may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is to be limited only by the following claims.
Claims (13)
1. An application monitoring method, comprising:
determining at least two application versions to be monitored of a target application;
acquiring terminal data corresponding to each application version to be monitored, wherein the terminal data corresponding to the application version to be monitored are collected from a terminal provided with the application version to be monitored of the target application;
analyzing the terminal data to obtain monitoring index data of each application version to be monitored;
and determining the monitoring result of the target application by comparing the monitoring index data of different versions of the application to be monitored.
2. The method of claim 1, wherein prior to determining at least two versions of the target application to be monitored, the method further comprises:
acquiring application heat data of a plurality of applications;
determining the target application from the plurality of applications according to the application popularity data.
3. The method of claim 2, wherein obtaining application heat data for a plurality of applications comprises:
and acquiring the application heat data of the plurality of applications under the version of the system to be monitored.
4. The method of claim 3, wherein prior to obtaining application heat data for the plurality of applications under a system version to be monitored, the method further comprises:
acquiring system version heat data of a plurality of system versions;
and determining the system version to be monitored from the plurality of system versions according to the system version heat data.
5. The method of claim 1, wherein determining at least two versions of the target application to be monitored comprises:
acquiring application version heat data of a plurality of application versions of the target application;
and determining the application version to be monitored from the plurality of application versions according to the application version hot degree data.
6. The method according to claim 1, wherein the obtaining of the terminal data corresponding to each application version to be monitored comprises:
determining a stable user group corresponding to each application version to be monitored;
and acquiring the terminal data of the stable user group.
7. The method according to claim 6, wherein the determining a stable user group corresponding to each application version to be monitored comprises:
and adding the user who uses the version of the application to be monitored in a first preset time range and does not change the version of the target application in a second preset time range into a stable user group corresponding to the version of the application to be monitored.
8. The method according to claim 1, wherein the determining the monitoring result of the target application by comparing the monitoring index data of different versions of the application to be monitored comprises:
determining at least one contrastable version group in the application version to be monitored according to the application version heat data of the application version to be monitored, wherein the difference of the application version heat data of any two application versions to be monitored in the contrastable version group is smaller than a heat balance threshold;
and determining the monitoring result of the target application by comparing the monitoring index data of different application versions to be monitored in the contrastable version group.
9. The method according to claim 1, wherein the determining the monitoring result of the target application by comparing the monitoring index data of different versions of the application to be monitored comprises:
and determining that at least one of the application versions to be monitored is abnormal in response to the difference between the monitoring index data of the two application versions to be monitored being larger than the monitoring threshold of the monitoring index data.
10. The method of claim 1, further comprising:
and generating prompt information about the abnormal application version to be monitored in response to the monitoring result indicating that at least one application version to be monitored of the target application is abnormal.
11. An application monitoring device, comprising:
the monitoring system comprises a to-be-monitored application version determining module, a monitoring module and a monitoring module, wherein the to-be-monitored application version determining module is configured to determine at least two to-be-monitored application versions of a target application;
the terminal data acquisition module is configured to acquire terminal data corresponding to each application version to be monitored, and the terminal data corresponding to the application version to be monitored are collected from a terminal provided with the application version to be monitored of the target application;
the terminal data analysis module is configured to analyze the terminal data to obtain monitoring index data of each application version to be monitored;
and the monitoring index comparison module is configured to determine a monitoring result of the target application by comparing monitoring index data of different versions of the application to be monitored.
12. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method of any one of claims 1 to 10.
13. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the method of any of claims 1 to 10 via execution of the executable instructions.
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