CN114579455A - Android software detection method and system - Google Patents
Android software detection method and system Download PDFInfo
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- CN114579455A CN114579455A CN202210221194.2A CN202210221194A CN114579455A CN 114579455 A CN114579455 A CN 114579455A CN 202210221194 A CN202210221194 A CN 202210221194A CN 114579455 A CN114579455 A CN 114579455A
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Abstract
The embodiment of the invention relates to the technical field of software detection, and particularly discloses an android software detection method and system. The embodiment of the invention generates test advertisement characteristic data by carrying out characteristic analysis on a plurality of test advertisements, and constructs an advertisement identification model; automatically identifying and opening a plurality of common software interfaces for detecting android software, and identifying a plurality of software advertisements according to an advertisement identification model to obtain the number of the software advertisements; generating performance loss data for clicking a plurality of software advertisements; and integrating the number of software advertisements and the performance loss data, carrying out advertisement detection evaluation on the detected android software, and generating an android software evaluation report. The characteristic analysis can be carried out through the test advertisement to a plurality of test android software, an advertisement recognition model is constructed, the identification of software advertisement is carried out to the detection android software through the advertisement recognition model, and then the software advertisement quantity and the performance loss data are obtained, an android software evaluation report is generated, and the detection and the evaluation of the internal advertisement of the android software are realized.
Description
Technical Field
The invention belongs to the technical field of software detection, and particularly relates to an android software detection method and system.
Background
Software is a collection of computer data and instructions organized in a particular order. Generally, software is divided into system software, application software, and middleware between the two. Software does not include only computer programs that can run on a computer, but documents associated with such computer programs are also generally considered to be part of the software.
Android software is an application program applied to an android system terminal, and is mainly used for mobile devices such as smart phones and tablet computers. Due to the openness of the android system, a very wide and free environment is provided for third-party developers, so that a large number of advertisements are enriched in a lot of android software, and the normal use of users is influenced. In the existing android software detection process, detection of internal advertisements of the android software is not usually involved, so that the android software with excellent performance in many detections is full of defects in practical application and cannot bring good use experience to users.
Disclosure of Invention
The embodiment of the invention aims to provide an android software detection method and system, and aims to solve the problems in the background art.
In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:
an android software detection method specifically comprises the following steps:
the method comprises the steps of obtaining a plurality of test android software, recording a plurality of test advertisements manually closed by a user in the test android software, carrying out feature analysis on the test advertisements, generating test advertisement feature data, and constructing an advertisement identification model according to the test advertisement feature data;
acquiring detection android software, automatically identifying and opening a plurality of common software interfaces of the detection android software, and identifying software advertisements of the common software interfaces according to the advertisement identification model to obtain the number of the software advertisements;
performing scene detection on the plurality of software advertisements to generate performance loss data for clicking the plurality of software advertisements;
and synthesizing the number of the software advertisements and the performance loss data, and performing advertisement detection evaluation on the detected android software to generate an android software evaluation report.
As a further limitation of the technical solution of the embodiment of the present invention, the obtaining of multiple test android software, recording multiple test advertisements manually closed by a user in the multiple test android software, performing feature analysis on the multiple test advertisements to generate test advertisement feature data, and constructing an advertisement identification model according to the test advertisement feature data specifically includes the following steps:
acquiring a plurality of test android software;
receiving an opening operation of manually opening a plurality of test android software by a user;
recording a plurality of test advertisements manually closed by a user according to the opening operation;
and performing characteristic analysis on the plurality of test advertisements to generate test advertisement characteristic data, and constructing an advertisement identification model according to the test advertisement characteristic data.
As a further limitation of the technical solution of the embodiment of the present invention, the performing feature analysis on the plurality of test advertisements to generate test advertisement feature data, and constructing an advertisement recognition model according to the test advertisement feature data specifically includes the following steps:
carrying out picture characteristic analysis on the test advertisements to generate advertisement picture characteristic data;
performing character characteristic analysis on the test advertisements to generate advertisement character characteristic data;
synthesizing the advertisement picture characteristic data and the advertisement character characteristic data to obtain test advertisement characteristic data;
and constructing an advertisement identification model according to the test advertisement characteristic data.
As a further limitation of the technical solution of the embodiment of the present invention, the acquiring of the detected android software, automatically identifying and opening a plurality of common software interfaces of the detected android software, and identifying software advertisements of the plurality of common software interfaces according to the advertisement identification model to obtain the number of the software advertisements specifically includes the following steps:
acquiring detection android software;
automatically recognizing and opening the detection android software;
intercepting a plurality of common software interfaces in the android detection software;
importing a plurality of common software interfaces into the advertisement recognition model;
and outputting a plurality of software advertisements identified by the advertisement identification model, and recording the number of the software advertisements.
As a further limitation of the technical solution of the embodiment of the present invention, the performing scene detection on a plurality of software advertisements and generating performance loss data for clicking a plurality of software advertisements specifically includes the following steps:
clicking a plurality of software advertisements to detect scenes;
acquiring resource occupation data, flow usage data and electric quantity loss data in the scene detection;
and integrating the resource occupation data, the flow use data and the electric quantity loss data to generate performance loss data.
As a further limitation of the technical solution of the embodiment of the present invention, the integrating the number of software advertisements and the performance loss data to perform advertisement detection evaluation on the detected android software, and generating an android software evaluation report specifically includes the following steps:
according to the advertisement quantity, carrying out advertisement quantity evaluation to generate quantity evaluation information;
according to the performance loss data, carrying out advertisement loss evaluation to generate loss evaluation information;
and integrating the quantity evaluation information and the loss evaluation information to generate an android software evaluation report.
The android software detection system comprises an advertisement detection test unit, an advertisement identification recording unit, an advertisement scene detection unit and an advertisement detection evaluation unit, wherein:
the advertisement detection testing unit is used for acquiring a plurality of test android software, recording a plurality of test advertisements manually closed by a user in the plurality of test android software, performing characteristic analysis on the plurality of test advertisements, generating test advertisement characteristic data, and constructing an advertisement identification model according to the test advertisement characteristic data;
the advertisement identification recording unit is used for acquiring detection android software, automatically identifying and opening a plurality of common software interfaces of the detection android software, and identifying software advertisements of the common software interfaces according to the advertisement identification model to obtain the number of the software advertisements;
the advertisement scene detection unit is used for carrying out scene detection on the plurality of software advertisements and generating performance loss data for clicking the plurality of software advertisements;
and the advertisement detection and evaluation unit is used for integrating the software advertisement quantity and the performance loss data, carrying out advertisement detection and evaluation on the detected android software and generating an android software evaluation report.
As a further limitation of the technical solution of the embodiment of the present invention, the advertisement detection test unit specifically includes:
the test software acquisition module is used for acquiring a plurality of test android software;
the opening operation receiving module is used for receiving the opening operation of manually opening the plurality of test android software by a user;
the advertisement closing recording module is used for recording a plurality of test advertisements manually closed by a user according to the opening operation;
and the advertisement identification model building module is used for carrying out characteristic analysis on the test advertisements to generate test advertisement characteristic data and building an advertisement identification model according to the test advertisement characteristic data.
As a further limitation of the technical solution of the embodiment of the present invention, the advertisement identification recording unit specifically includes:
the detection software acquisition module is used for acquiring detection android software;
the software identification opening module is used for automatically identifying and opening the detection android software;
the common interface intercepting module is used for intercepting a plurality of common software interfaces in the android detection software;
the common interface importing module is used for importing a plurality of common software interfaces into the advertisement identification model;
and the advertisement identification recording module is used for outputting the plurality of software advertisements identified by the advertisement identification model and recording the number of the software advertisements.
As a further limitation of the technical solution of the embodiment of the present invention, the advertisement scene detection unit specifically includes:
the advertisement scene detection module is used for clicking a plurality of software advertisements to detect scenes;
the detection data acquisition module is used for acquiring resource occupation data, flow use data and electric quantity loss data in the scene detection;
and the loss data generation module is used for integrating the resource occupation data, the flow use data and the electric quantity loss data to generate performance loss data.
Compared with the prior art, the invention has the beneficial effects that:
the embodiment of the invention generates test advertisement characteristic data by carrying out characteristic analysis on a plurality of test advertisements, and constructs an advertisement identification model; automatically identifying and opening a plurality of common software interfaces for detecting android software, and identifying a plurality of software advertisements according to an advertisement identification model to obtain the number of the software advertisements; generating performance loss data for clicking a plurality of software advertisements; and integrating the number of software advertisements and the performance loss data, carrying out advertisement detection evaluation on the detected android software, and generating an android software evaluation report. Can carry out characteristic analysis through the test advertisement to a plurality of test android software, construct advertisement recognition model to carry out the discernment of software advertisement to detecting android software through advertisement recognition model, and then obtain software advertisement quantity and performance loss data, generate android software evaluation report, realize the detection and the evaluation to the inside advertisement of android software.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
Fig. 1 shows a flow chart of a method provided by an embodiment of the invention.
Fig. 2 is a flow chart illustrating a test advertisement characteristic analysis in the method provided by the embodiment of the invention.
Fig. 3 shows a flowchart of constructing an advertisement recognition model in the method provided by the embodiment of the invention.
Fig. 4 shows a flowchart of software advertisement identification record in the method provided by the embodiment of the invention.
Fig. 5 shows a flowchart of advertisement scene detection in the method provided by the embodiment of the present invention.
Fig. 6 shows a flowchart of advertisement detection evaluation in the method provided by the embodiment of the invention.
Fig. 7 shows an application architecture diagram of a system provided by an embodiment of the invention.
Fig. 8 is a block diagram illustrating a structure of an advertisement detection test unit in the system according to the embodiment of the present invention.
Fig. 9 shows a block diagram of a structure of an advertisement identification recording unit in the system provided by the embodiment of the invention.
Fig. 10 shows a block diagram of an advertisement scene detection unit in the system according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It can be understood that in the prior art, detection of android software does not generally involve detection of internal advertisements of the android software, so that many android software which are excellent in detection are subjected to a problem in actual application and cannot bring a good use experience to a user.
In order to solve the problems, the embodiment of the invention generates test advertisement characteristic data and constructs an advertisement identification model by performing characteristic analysis on a plurality of test advertisements; automatically identifying and opening a plurality of common software interfaces for detecting android software, and identifying a plurality of software advertisements according to an advertisement identification model to obtain the number of the software advertisements; generating performance loss data for clicking a plurality of software advertisements; and integrating the number of software advertisements and the performance loss data, carrying out advertisement detection evaluation on the detected android software, and generating an android software evaluation report. Can carry out characteristic analysis through the test advertisement to a plurality of test android software, construct advertisement recognition model to carry out the discernment of software advertisement to detecting android software through advertisement recognition model, and then obtain software advertisement quantity and performance loss data, generate android software evaluation report, realize the detection and the evaluation to the inside advertisement of android software.
Fig. 1 shows a flow chart of a method provided by an embodiment of the invention.
Specifically, the android software detection method specifically comprises the following steps:
step S101, obtaining a plurality of test android software, recording a plurality of test advertisements manually closed by a user in the plurality of test android software, performing characteristic analysis on the plurality of test advertisements, generating test advertisement characteristic data, and constructing an advertisement identification model according to the test advertisement characteristic data.
In the embodiment of the invention, a plurality of pieces of test android software which are prepared in advance are obtained, a user manually opens the test android software in sequence for use, a plurality of test advertisements which are manually closed by the user and appear in the test android software are recorded in the process that the user manually opens the software for use, characteristic data of the test advertisements are obtained by performing characteristic analysis on the test advertisements, and an advertisement identification model is constructed according to the characteristic data of the test advertisements.
It will be appreciated that the test android software may be a plurality of different types of android software commonly used, and that the plurality of test android software may consist of: social android software, video android software, music android software, photographing android software, financial android software and reading android software. The test advertisements appearing in the android software can reflect the characteristics of the advertisements appearing in the android software, so that the test advertisement characteristic data can be obtained by carrying out characteristic analysis on the test advertisements, and an advertisement identification model capable of identifying the advertisements in the android software through the interface picture is constructed according to the test advertisement characteristic data.
Specifically, fig. 2 shows a flowchart of a test advertisement characteristic analysis in the method provided by the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the acquiring a plurality of test android software, recording a plurality of test advertisements manually closed by a user in the plurality of test android software, performing feature analysis on the plurality of test advertisements to generate test advertisement feature data, and constructing an advertisement recognition model according to the test advertisement feature data specifically includes the following steps:
step S1011, a plurality of android test software are obtained.
In the embodiment of the invention, a plurality of corresponding test android software are respectively installed through a plurality of installation packages by downloading the installation packages of the test android software.
Step S1012, receiving an opening operation of manually opening a plurality of the test android software by a user.
And step S1013, recording a plurality of test advertisements manually closed by the user according to the opening operation.
In the embodiment of the invention, a user closes the advertisements appearing in the process of opening the application of the test android software in the process of opening the test android software, performs manual closing operation on the user by analyzing the opening operation of the user, and marks the operation objects subjected to the manual closing as the test advertisements.
It can be understood that in the process of opening the test android software for application, a user closes the test advertisement appearing in the test android software, and the determination and marking of the test advertisement are performed by acquiring a series of manual closing operations such as "skipping" and "closing" clicked by the user.
And step S1014, carrying out characteristic analysis on the plurality of test advertisements to generate test advertisement characteristic data, and constructing an advertisement identification model according to the test advertisement characteristic data.
In the embodiment of the invention, picture characteristic analysis and character characteristic analysis are respectively carried out on the test advertisement to obtain advertisement picture characteristic data and advertisement character characteristic data, the test advertisement characteristic data are generated by integrating the advertisement picture characteristic data and the advertisement character characteristic data, and an advertisement identification model capable of identifying the advertisement in the android software through the interface picture is constructed according to the test advertisement characteristic data.
Specifically, fig. 3 shows a flowchart for constructing an advertisement recognition model in the method provided by the embodiment of the present invention.
In a preferred embodiment of the present invention, the performing feature analysis on the test advertisements to generate test advertisement feature data, and constructing an advertisement recognition model according to the test advertisement feature data specifically includes the following steps:
step S10141, performing picture characteristic analysis on the plurality of test advertisements to generate advertisement picture characteristic data.
Step S10142, carrying out character characteristic analysis on the plurality of test advertisements to generate advertisement character characteristic data.
Step S10143, integrating the advertisement picture characteristic data and the advertisement character characteristic data to obtain test advertisement characteristic data.
And step S10144, constructing an advertisement identification model according to the test advertisement characteristic data.
Further, the android software detection method further comprises the following steps:
step S102, obtaining detection android software, automatically identifying and opening a plurality of common software interfaces of the detection android software, and identifying software advertisements of the common software interfaces according to the advertisement identification model to obtain the number of the software advertisements.
In the embodiment of the invention, the detection android software to be detected is installed, the detection android software is automatically identified and opened for application simulation according to the operation guide in the detection android software, a plurality of common software interfaces in the detection android software opening are subjected to screenshot, the intercepted common software interfaces are respectively led into an advertisement identification model, software advertisements existing in the common software interfaces are identified through the advertisement identification model, and the number of the software advertisements in the detection android software is counted.
Specifically, fig. 4 shows a flowchart of software advertisement identification records in the method provided by the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the acquiring and detecting android software, automatically identifying and opening a plurality of common software interfaces of the detecting android software, and identifying software advertisements of the plurality of common software interfaces according to the advertisement identification model to obtain the number of the software advertisements specifically includes the following steps:
and step S1021, acquiring the android detection software.
Step S1022, automatically identifying and opening the detection android software.
And step S1023, intercepting a plurality of common software interfaces in the android detection software.
Step S1024, importing a plurality of common software interfaces into the advertisement identification model.
And step S1025, outputting a plurality of software advertisements identified by the advertisement identification model, and recording the number of the software advertisements.
Further, the android software detection method further comprises the following steps:
step S103, carrying out scene detection on the plurality of software advertisements, and generating performance loss data for clicking the plurality of software advertisements.
In the embodiment of the invention, an application scene of clicking advertisements is established, the condition that a user clicks software advertisements in android software carelessly is simulated, the resource occupation, flow usage and electric quantity loss of a plurality of software advertisements in the android software in the application scene are obtained, and performance loss data is generated.
Specifically, fig. 5 shows a flowchart of advertisement scene detection in the method provided by the embodiment of the present invention.
In a preferred embodiment of the present invention, the performing scene detection on a plurality of software advertisements and generating performance loss data for clicking a plurality of software advertisements specifically includes the following steps:
and step S1031, clicking a plurality of software advertisements to detect scenes.
Step S1032 acquires the resource occupation data, the traffic usage data, and the power consumption data in the scene detection.
Step S1033, synthesize the resource occupation data, the traffic usage data, and the power consumption data, and generate performance consumption data.
Further, the android software detection method further comprises the following steps:
and step S104, integrating the software advertisement quantity and the performance loss data, carrying out advertisement detection evaluation on the detected android software, and generating an android software evaluation report.
In the embodiment of the invention, the quantity evaluation information is obtained by evaluating the advertisement quantity of the android detection software according to the quantity of the software advertisements, the advertisement loss evaluation is carried out on the android detection software according to the performance loss data to obtain the loss evaluation information, and then the advertisements of the android detection software are comprehensively evaluated according to the quantity evaluation information and the advertisement loss evaluation to generate the android software evaluation report.
It can be understood that the larger the number of software advertisements is, the worse the user experience of detecting android software is; the higher the resource occupation, traffic usage and power consumption in the performance loss data, the worse the user experience of detecting the android software. The quantity evaluation information and the loss evaluation information can be experience scores of android software for detection, and the android software evaluation report can be comprehensive experience scores of the android software for detection according to the quantity evaluation information and the loss evaluation information.
Specifically, fig. 6 shows a flowchart of advertisement detection evaluation in the method provided by the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the generating an evaluation report of the android software by integrating the number of software advertisements and the performance loss data to perform advertisement detection evaluation on the detected android software specifically includes the following steps:
and step S1041, evaluating the advertisement amount according to the advertisement amount, and generating amount evaluation information.
And step S1042, according to the performance loss data, carrying out advertisement loss evaluation to generate loss evaluation information.
And step S1043, integrating the quantity evaluation information and the loss evaluation information to generate an android software evaluation report.
Further, fig. 7 is a diagram illustrating an application architecture of the system according to the embodiment of the present invention.
In another preferred embodiment, the present invention provides an android software detection system, which includes:
the advertisement detection testing unit 101 is configured to obtain a plurality of test android software, record a plurality of test advertisements manually closed by a user in the plurality of test android software, perform feature analysis on the plurality of test advertisements, generate test advertisement feature data, and construct an advertisement identification model according to the test advertisement feature data.
In the embodiment of the invention, the advertisement detection testing unit 101 acquires a plurality of pieces of test android software which are prepared in advance, a user manually opens the plurality of pieces of test android software in sequence for use, a plurality of test advertisements which are manually closed by the user and appear in the test android software are recorded in the process that the user manually opens the software for use, characteristic data of the test advertisements are obtained by performing characteristic analysis on the plurality of test advertisements, and an advertisement identification model is constructed according to the characteristic data of the test advertisements.
Specifically, fig. 8 shows a block diagram of the structure of the advertisement detection testing unit 101 in the system according to the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the advertisement detection testing unit 101 specifically includes:
the testing software obtaining module 1011 is configured to obtain a plurality of testing android software.
An opening operation receiving module 1012, configured to receive an opening operation that a user manually opens a plurality of the test android software.
And an advertisement closing recording module 1013 configured to record, according to the opening operation, a plurality of test advertisements manually closed by the user.
The advertisement identification model building module 1014 is configured to perform feature analysis on the plurality of test advertisements, generate test advertisement feature data, and build an advertisement identification model according to the test advertisement feature data.
Further, the android software detection system further includes:
the advertisement identification recording unit 102 is configured to acquire the detected android software, automatically identify and open a plurality of common software interfaces of the detected android software, and identify software advertisements of the plurality of common software interfaces according to the advertisement identification model to obtain the number of the software advertisements.
In the embodiment of the invention, the advertisement identification recording unit 102 is used for installing detection android software to be detected, automatically identifying and opening the detection android software for application simulation according to operation guidance in the detection android software, capturing a plurality of common software interfaces during opening of the detection android software, respectively introducing the captured common software interfaces into an advertisement identification model, identifying software advertisements existing in the common software interfaces through the advertisement identification model, and counting the number of the software advertisements in the detection android software.
Specifically, fig. 9 shows a block diagram of the structure of the advertisement identification recording unit 102 in the system provided by the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the advertisement identification recording unit 102 specifically includes:
and a detection software obtaining module 1021, configured to obtain detection android software.
A software identification opening module 1022, configured to automatically identify and open the detection android software.
And the common interface intercepting module 1023 is used for intercepting a plurality of common software interfaces in the android detection software.
A common interface importing module 1024, configured to import a plurality of common software interfaces into the advertisement recognition model.
And the advertisement identification recording module 1025 is used for outputting a plurality of software advertisements identified by the advertisement identification model and recording the number of the software advertisements.
Further, the android software detection system further includes:
an advertisement scene detection unit 103, configured to perform scene detection on the multiple software advertisements, and generate performance loss data for clicking the multiple software advertisements.
In the embodiment of the present invention, the advertisement scene detection unit 103 establishes an application scene of clicking advertisements, simulates that a user accidentally clicks software advertisements in the android test software, obtains the conditions of resource occupation, traffic usage and power consumption of a plurality of software advertisements in the android test software in the application scene, and generates performance loss data.
Specifically, fig. 10 shows a block diagram of the structure of the advertisement scene detection unit 103 in the system provided by the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the advertisement scene detection unit 103 specifically includes:
and an advertisement scene detection module 1031, configured to click a plurality of software advertisements to perform scene detection.
A detection data obtaining module 1032, configured to obtain resource occupation data, traffic usage data, and power consumption data in the scene detection.
A loss data generating module 1033, configured to synthesize the resource occupation data, the traffic usage data, and the power consumption data, and generate performance loss data.
Further, the android software detection system further includes:
and the advertisement detection and evaluation unit 104 is configured to synthesize the number of software advertisements and the performance loss data, perform advertisement detection and evaluation on the detected android software, and generate an android software evaluation report.
In the embodiment of the present invention, the advertisement detection and evaluation unit 104 evaluates the advertisement amount of the android software to be detected by the number of software advertisements to obtain number evaluation information, evaluates the advertisement loss of the android software to be detected by the performance loss data to obtain loss evaluation information, and then comprehensively evaluates the advertisements of the android software to be detected by the number evaluation information and the advertisement loss evaluation to generate an android software evaluation report.
In summary, the embodiment of the invention can construct the advertisement identification model by performing feature analysis on the test advertisements of the plurality of pieces of test android software, and perform software advertisement identification on the test android software through the advertisement identification model, so as to obtain the number of software advertisements and performance loss data, generate the evaluation report of the android software, and realize detection and evaluation of the internal advertisements of the android software.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the program is executed. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. An android software detection method is characterized by specifically comprising the following steps:
the method comprises the steps of obtaining a plurality of test android software, recording a plurality of test advertisements manually closed by a user in the test android software, carrying out feature analysis on the test advertisements, generating test advertisement feature data, and constructing an advertisement identification model according to the test advertisement feature data;
acquiring detection android software, automatically identifying and opening a plurality of common software interfaces of the detection android software, and identifying software advertisements of the common software interfaces according to the advertisement identification model to obtain the number of the software advertisements;
performing scene detection on the plurality of software advertisements to generate performance loss data for clicking the plurality of software advertisements;
and synthesizing the number of the software advertisements and the performance loss data, and performing advertisement detection evaluation on the detected android software to generate an android software evaluation report.
2. The android software detection method of claim 1, wherein the steps of obtaining a plurality of test android software, recording a plurality of test advertisements manually closed by a user in the plurality of test android software, performing feature analysis on the plurality of test advertisements to generate test advertisement feature data, and constructing an advertisement recognition model according to the test advertisement feature data specifically include the following steps:
acquiring a plurality of test android software;
receiving an opening operation of manually opening a plurality of test android software by a user;
recording a plurality of test advertisements manually closed by a user according to the opening operation;
and performing characteristic analysis on the plurality of test advertisements to generate test advertisement characteristic data, and constructing an advertisement identification model according to the test advertisement characteristic data.
3. The android software detection method of claim 2, wherein the performing feature analysis on the plurality of test advertisements to generate test advertisement feature data, and constructing an advertisement recognition model according to the test advertisement feature data specifically comprises the following steps:
carrying out picture characteristic analysis on the test advertisements to generate advertisement picture characteristic data;
performing character characteristic analysis on the test advertisements to generate advertisement character characteristic data;
synthesizing the advertisement picture characteristic data and the advertisement character characteristic data to obtain test advertisement characteristic data;
and constructing an advertisement identification model according to the test advertisement characteristic data.
4. The android software detection method of claim 1, wherein the obtaining detection android software, automatically identifying and opening a plurality of common software interfaces of the detection android software, and identifying software advertisements of the plurality of common software interfaces according to the advertisement identification model to obtain the number of the software advertisements specifically comprises the following steps:
acquiring detection android software;
automatically recognizing and opening the detection android software;
intercepting a plurality of common software interfaces in the android detection software;
importing a plurality of common software interfaces into the advertisement recognition model;
and outputting a plurality of software advertisements identified by the advertisement identification model, and recording the number of the software advertisements.
5. The android software detection method of claim 1, wherein the performing scene detection on the plurality of software advertisements to generate performance loss data for clicking the plurality of software advertisements specifically comprises:
clicking a plurality of software advertisements to detect scenes;
acquiring resource occupation data, flow use data and electric quantity loss data in the scene detection;
and integrating the resource occupation data, the flow use data and the electric quantity loss data to generate performance loss data.
6. The method for detecting the android software according to claim 1, wherein the step of performing advertisement detection evaluation on the detected android software by integrating the software advertisement quantity and the performance loss data to generate an android software evaluation report specifically includes the following steps:
according to the advertisement quantity, carrying out advertisement quantity evaluation to generate quantity evaluation information;
according to the performance loss data, carrying out advertisement loss evaluation to generate loss evaluation information;
and integrating the quantity evaluation information and the loss evaluation information to generate an android software evaluation report.
7. The android software detection system is characterized by comprising an advertisement detection test unit, an advertisement identification recording unit, an advertisement scene detection unit and an advertisement detection evaluation unit, wherein:
the advertisement detection testing unit is used for acquiring a plurality of test android software, recording a plurality of test advertisements manually closed by a user in the plurality of test android software, performing characteristic analysis on the plurality of test advertisements, generating test advertisement characteristic data, and constructing an advertisement identification model according to the test advertisement characteristic data;
the advertisement identification recording unit is used for acquiring detection android software, automatically identifying and opening a plurality of common software interfaces of the detection android software, and identifying software advertisements of the common software interfaces according to the advertisement identification model to obtain the number of the software advertisements;
the advertisement scene detection unit is used for carrying out scene detection on the plurality of software advertisements and generating performance loss data for clicking the plurality of software advertisements;
and the advertisement detection and evaluation unit is used for integrating the software advertisement quantity and the performance loss data, carrying out advertisement detection and evaluation on the detected android software and generating an android software evaluation report.
8. The android software detection system of claim 7, wherein the advertisement detection test unit specifically comprises:
the test software acquisition module is used for acquiring a plurality of test android software;
the opening operation receiving module is used for receiving the opening operation of manually opening the plurality of test android software by a user;
the advertisement closing recording module is used for recording a plurality of test advertisements manually closed by a user according to the opening operation;
and the advertisement identification model building module is used for carrying out characteristic analysis on the test advertisements to generate test advertisement characteristic data and building an advertisement identification model according to the test advertisement characteristic data.
9. The android software detection system of claim 7, wherein the advertisement identification recording unit specifically includes:
the detection software acquisition module is used for acquiring detection android software;
the software identification opening module is used for automatically identifying and opening the android detection software;
the common interface intercepting module is used for intercepting a plurality of common software interfaces in the android detection software;
the common interface importing module is used for importing a plurality of common software interfaces into the advertisement identification model;
and the advertisement identification recording module is used for outputting the plurality of software advertisements identified by the advertisement identification model and recording the number of the software advertisements.
10. The android software detection system of claim 7, wherein the advertisement scene detection unit specifically includes:
the advertisement scene detection module is used for clicking a plurality of software advertisements to perform scene detection;
the detection data acquisition module is used for acquiring resource occupation data, flow use data and electric quantity loss data in the scene detection;
and the loss data generation module is used for integrating the resource occupation data, the flow use data and the electric quantity loss data to generate performance loss data.
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