CN112448860B - Application program testing method and related equipment - Google Patents

Abstract

The embodiment of the invention provides a test method and related equipment of an application program, wherein the method comprises the following steps: acquiring a network characteristic parameter set of a real network where the electronic equipment is located, wherein each data in the network characteristic parameter set comprises: parameter values of the target network characteristic parameters and time points of the parameter values; determining a target parameter value of a target network characteristic parameter at a test time point based on the network characteristic parameter set; and calling the target parameter value to test the simulation network of the application program at the test time point. Therefore, the difference between the network environment of the simulation network and the network environment of the real network can be reduced, and the testing accuracy of the application program is further improved.

Description

Application program testing method and related equipment

Technical Field

The present invention relates to the field of application program testing, and in particular, to a method and a device for testing an application program.

Background

With the development of electronic technology, electronic devices such as mobile phones, tablet computers, smart televisions and the like have become indispensable tools in daily life of people. The electronic device may provide a user with various functions such as browsing a web page, working, playing games, listening to music online, watching videos, and the like by installing an application program. In order to ensure that the application program can provide stable and reliable service for the user, the running stability of the application program is usually required to be tested in the development process of the application program.

The weak network environment test is a crucial part in the application test because the actual network where the electronic device is located may be unstable or have a low network speed, and the harsh network environment may cause the operation of the application to fail. At present, in a weak network environment test of an application program, an effect of simulating a weak network is usually achieved by configuring current limiting through a tool on line, namely configuring network characteristic parameters such as bandwidth, uploading rate, downloading rate, time delay, packet loss, bit error rate and the like of the weak network. However, since the real network environment is complex and variable, the simulated network environment may have a large difference from the real network environment, which may result in the accuracy of the weak network environment test of the application program being reduced.

Therefore, the problem of low test accuracy exists in the weak network environment test of the application program at present.

Disclosure of Invention

The embodiment of the invention provides a test method and related equipment of an application program, and aims to solve the problem of low test accuracy in the existing weak network environment test of the application program.

In order to solve the technical problem, the invention is realized as follows:

in a first aspect, an embodiment of the present invention provides a method for testing an application program, where the method is applied to an electronic device, and the method includes:

acquiring a network characteristic parameter set of a real network where the electronic device is located, wherein each data in the network characteristic parameter set comprises: parameter values of the target network characteristic parameters and time points of the parameter values;

determining a target parameter value of a target network characteristic parameter at a test time point based on the network characteristic parameter set;

and calling the target parameter value to test the simulation network of the application program at the test time point.

In a second aspect, an embodiment of the present invention further provides an electronic device, including:

a parameter set obtaining module, configured to obtain a network feature parameter set of a real network where the electronic device is located, where each piece of data in the network feature parameter set includes: parameter values of the target network characteristic parameters and time points of the parameter values;

the parameter value determining module is used for determining a target parameter value of a target network characteristic parameter at a testing time point based on the network characteristic parameter set;

and the testing module is used for calling the target parameter value to test the simulation network of the application program at the testing time point.

In a third aspect, an embodiment of the present invention further provides an electronic device, which includes a processor, a memory, and a computer program stored on the memory and capable of running on the processor, where the computer program, when executed by the processor, implements the steps of the method for testing the application program.

In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements the steps of the method for testing the application program.

In the embodiment of the present invention, a network feature parameter set of a real network where an electronic device is located is obtained, where each data in the network feature parameter set includes: parameter values of the target network characteristic parameters and time points of the parameter values; determining a target parameter value of a target network characteristic parameter at a test time point based on the network characteristic parameter set; and calling the target parameter value to test the simulation network of the application program at the test time point. Therefore, the difference between the network environment of the simulation network and the network environment of the real network can be reduced, and the testing accuracy of the application program is further improved.

Drawings

Fig. 1 is a schematic flowchart of a method for testing an application according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of an actual application of the test method for the application program according to the embodiment of the present invention;

FIG. 3 is a graph illustrating a fitting function provided by an embodiment of the present invention;

FIG. 4 is a second graph of a fitting function provided by an embodiment of the present invention;

FIG. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention;

FIG. 6 is a schematic structural diagram of a parameter value determining module according to an embodiment of the present invention;

fig. 7 is a second schematic structural diagram of an electronic device according to an embodiment of the invention;

fig. 8 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.

Referring to fig. 1, which is a schematic flow chart of a method for testing an application according to an embodiment of the present invention, an electronic device includes a display screen, and as shown in fig. 1, the method for testing an application includes the following steps:

step 101, obtaining a network feature parameter set of a real network where the electronic device is located, wherein each data in the network feature parameter set includes: parameter values of the target network characteristic parameters and time points of the parameter values;

102, determining a target parameter value of a target network characteristic parameter at a test time point based on the network characteristic parameter set;

and 103, calling the target parameter value to test the simulation network of the application program at the test time point.

The electronic device can determine the target parameter value of the target network characteristic parameter at the test time point according to the parameter value of the target network characteristic parameter of the real network, and test the simulation network of the application program through the target parameter value at the test time point, so that the network environment of the simulation network and the network environment of the real network in the test process of the application program have higher association degree, the difference between the network environment of the simulation network and the network environment of the real network can be reduced, and the test accuracy of the application program is further improved.

Instep 101, the obtaining of the network feature parameter set of the real network where the electronic device is located may be that the electronic device continuously records and caches parameter values of target network feature parameters of the real network connected in the use process of the electronic device, and in a case that a first instruction for instructing the obtained network feature parameter set is received, extracts a part or all of the stored parameter values of the target network feature parameters as the network feature parameter set; or, in the using process, when receiving a second instruction for instructing to acquire the network feature parameter set, the electronic device may record, in real time, the parameter value of the target network feature parameter of the real network to which the electronic device is connected, and generate the network feature parameter set from the parameter value recorded in real time.

Wherein the first instruction and the second instruction may be: and the first instruction and the second instruction can be instructions input by a user.

For example, a user may input an operation (i.e., the above-mentioned first instruction or second instruction) in the electronic device for instructing to acquire the network feature parameter set of 19-00, and the electronic device acquires the parameter values of the target network feature parameters of the real network in which it is located within a time period of 19-00.

Of course, the first instruction and the second instruction may be instructions that are automatically triggered by the electronic device according to a certain rule, and are not limited herein.

In some embodiments, the obtaining of the network feature parameter set of the real network where the electronic device is located includes:

and when the preset interval duration is detected to be reached, acquiring a network characteristic parameter set of a real network where the electronic equipment is located.

Here, the electronic device may obtain the network feature parameter set of the real network where the electronic device is located at a certain time interval, so as to implement dynamic update of the network feature parameter set, and further may reduce a difference between a network environment of the simulated network and a network environment of the real network, so that the test accuracy of the application program is higher.

For example, the preset interval duration may be one day, the electronic device may acquire the network feature parameter set of the real network once a day, for example, the electronic device may acquire the parameter value of the target network feature parameter in two hours every other day, and update the previous network feature parameter set by using the newly acquired network feature parameter set.

In this embodiment, the real network is any network connected in the operation process of the electronic device, and may be a mobile data network, a wired network, or a wireless access network, and so on.

In addition, the target network characteristic parameter may be any characteristic parameter of a network to which the electronic device is connected, and in some embodiments, the target characteristic network parameter may include at least one of a bandwidth, an upload rate, a download rate, a delay, a packet loss rate, and an error rate, so that the target network characteristic parameter may be flexibly selected according to actual needs.

It should be noted that, in the case that the target network characteristic parameter includes a plurality of items of bandwidth, upload rate, download rate, delay time, packet loss, and error rate, each of the parameter values is an array composed of a plurality of values, for example, in the case that the target network characteristic parameter includes bandwidth, upload rate, download rate, delay time, packet loss, and error rate, each of the parameter values = (bandwidth value, upload rate value, download rate value, delay time value, packet loss value, error rate value), and the like.

In addition, after the electronic device obtains the network characteristic parameter set, the network characteristic parameter set may be stored, so as to facilitate operations such as querying and modifying parameter values in the network characteristic parameter set, which is not described herein again.

Instep 102, in a case that the electronic device acquires the network feature parameter set, the electronic device may determine, based on the network feature parameter set, a target parameter value of a target network feature parameter at a test time point, where the test time point is a time point in an application program test process, that is, the electronic device may predict a parameter value at the test time point based on the network feature parameter set.

In this embodiment, the determining the target parameter value of the target network characteristic parameter at the test time point based on the network characteristic parameter set may be determining a parameter value of the target network characteristic parameter associated with the time point and the test time point in the network characteristic parameter set as the target parameter value.

For example, in the case where the above-mentioned network characteristic parameter values include parameter values of 19-00 on a certain date, and in the case where the above-mentioned test time point is 20 on another date, the electronic device may determine the parameter values at the time point of the network characteristic parameter set 20 as the above-mentioned target parameter values.

In some embodiments, thestep 102 may include:

constructing a time distribution model of the target network characteristic parameter based on the network characteristic parameter set;

and acquiring parameter values of the target network characteristic parameters of the test time points based on the time distribution model.

Here, the terminal may construct a time distribution model of the target network characteristic parameter based on the network characteristic parameter set, and obtain the parameter value at the test time point through calculation of the time distribution model, so that the parameter set at any test time may be obtained through the acquired partial data, and the correlation between the network environment of the simulated network and the network environment of the real network is higher, thereby further improving the test accuracy.

In this embodiment, the time distribution model of the target network characteristic parameter, which is constructed based on the network characteristic parameter set, may be constructed by the electronic device through a construction method of an arbitrary time distribution model, for example, the time distribution model may be constructed by using the network characteristic parameter set as a training data set of a deep learning model, training the deep learning model to obtain the target network characteristic parameter, using a time point in a training process as a parameter of an input layer, and using a parameter value of the target network characteristic parameter as a parameter of an output layer.

In other embodiments, the constructing a time distribution model of the target network characteristic parameter includes:

and fitting the parameter values in the network characteristic parameter set to generate a time distribution model of the target network characteristic parameters.

The electronic equipment can perform fitting processing on the data in the network characteristic parameter set through a fitting algorithm to generate a time distribution model of the target network characteristic parameters, so that the electronic equipment can not only quickly construct the time distribution model, but also ensure the test accuracy.

It should be noted that the fitting algorithm may be any algorithm capable of implementing the building of the time distribution model, for example, the fitting function of the fitting algorithm may be a quadratic function, and the like, and is not limited herein.

When the time distribution model is constructed through a fitting algorithm, the time points of the parameter values of the target network characteristic parameters can be used as the independent variables of the fitting function, and the parameter values are used as the dependent variables, so that the adjustable parameters of the fitting function are obtained through calculation.

In addition, in the case that the target network characteristic parameter includes a plurality of parameters, the time distribution model may be a matrix function including a plurality of fitting functions, and each fitting function corresponds to one parameter, that is, one fitting function only represents an association relationship between a value of one parameter and a time point; of course, the time distribution model may be formed by only one fitting function, and the one fitting function may represent the association relationship between the array of parameter values of the target network characteristic parameter and the time point, which is not limited herein.

In some embodiments, before the constructing the time distribution model of the target network feature parameter based on the network feature parameter set, the method further includes:

filtering the data in the network characteristic parameter set to obtain a filtered network characteristic parameter set;

the constructing a time distribution model of the target network characteristic parameter based on the network characteristic parameter set comprises:

and constructing a time distribution model of the network characteristic parameters based on the network characteristic parameter set after filtering processing.

Here, after the electronic device acquires the network characteristic parameter set, the electronic device may perform filtering processing on the data in the network characteristic parameter set through a denoising algorithm, so as to remove discrete data (i.e., noise data) in the network characteristic parameter set, improve the accuracy of the time distribution model, and further improve the accuracy of the application program test.

It should be noted that the denoising algorithm may be any algorithm capable of removing discrete data in the network characteristic parameter set, for example, the denoising algorithm may be any one of filtering algorithms such as logical judgment filtering, median filtering, mean filtering, weighted average filtering, and moving filtering, and is not limited herein.

Instep 103, after the electronic device obtains the target parameter value of the target network characteristic parameter at the test time point, the electronic device may call the target parameter value to perform a network simulation test on the application program at the test time point.

It should be noted that, the above-mentioned electronic device may perform the network simulation test on the Application program by calling the target parameter value, where the electronic device calls an Application Programming Interface (API) of the network simulation test tool according to the test time point through a network simulation test tool, such as an ATC (authenticated Traffic Control) tool, so as to enable the configuration to take effect in real time, so as to implement the test on the Application program, where a process of calling the parameter value of the network characteristic parameter at the time point through the network simulation test tool is well known in the art, and is not described herein again.

In addition, the electronic device may call a target parameter value to perform a network simulation test on the application program at a test time point, where the electronic device may determine a target parameter value within a period of test time (including the test time point) in advance through the time distribution model, and call the target parameter value at the test time point in a test process; alternatively, the electronic device may calculate a target parameter value through the time distribution model at each test time point during the test process, and directly call the target parameter value for testing, which is not limited herein.

In this embodiment, in order to facilitate understanding of the processing procedure of the method for testing the application program, an example of practical application of the method is provided here for explanation, and as shown in fig. 2, the processing procedure includes:

1) Firstly, recording a network for a long time by using a tool (the sampling frequency can be infinite and accurate to seconds, minutes and the like), and recording parameters such as bandwidth, time delay, packet loss rate, data packet error codes, time points and the like into a database and the like;

2) Optimizing data, analyzing and denoising the sampled data to obtain a time distribution model;

3) When a network needs to be simulated, acquiring network characteristic parameters in the model through a network simulation tool according to time point information, and dynamically updating the network parameter configuration of the simulation network to realize a dynamically changing network and achieve the aim of high simulation;

in addition, the processing procedure may further include:

4) Periodic data rectification, such as performed weekly 1), 2) to achieve dynamic updates to the time distribution model;

1) The specific treatment process to 3) is as follows:

step1, acquiring a network characteristic parameter set of a real network, namely screening equivalent data of uplink and downlink bandwidths, time delay, packet loss rate and data packet error rate from the network characteristic parameter;

the screened quantized data can be stored in a database, and is easy to query and modify.

Step2, removing discrete data (namely filtering the data in the network characteristic parameter set) through a digital filtering algorithm;

wherein, filtering is the spatial domain filtering technique of low frequency enhancement, and the purpose has two: firstly, blurring; secondly, noise is eliminated. Here, the discrete data may be removed by a digital filtering algorithm such as a decision filtering, a median filtering, a mean filtering, a weighted average filtering, or a moving filtering, and the corresponding filtering algorithm may be selected according to an actual scene.

Step3, performing mathematical modeling by using a fitting algorithm to obtain a matrix function (namely a time distribution model), wherein independent variables are natural time and adjustable parameters;

for example, the matrix function may include a fitting function of an uplink bandwidth, a downlink bandwidth, a delay, a packet loss rate, and an error rate, and the matrix function may be expressed as:

an uplink bandwidth fitting function UpRa (t, ea) = f1 (t, a);

downlink bandwidth fitting function downlink r (at, tb) e = f2 (t, b);

delay fit function Dela (t, yc) = f3 (t, c);

packet loss rate fitting function Los (ts, d) = f4 (t, d);

a bit error rate fitting function Corrup (tt, ieo) n = f5 (t, e);

wherein a, b, c, d and e represent the adjustable parameters of each fitting function respectively.

Exemplarily, the upper line bandwidth fitting function is f1 (t, a) = t² +2t + a as an example:

the argument t represents the test time point (the test time point is a natural time, such as 20;

a represents an adjustable parameter, which is generally a constant and is not a variable;

the dependent variable f1 (t, a) represents the upstream bandwidth value corresponding to the testing time point, such as the arc shown in fig. 3 is the fitting curve of the upstream bandwidth fitting function, the abscissa is the time axis, the ordinate is the upstream bandwidth value, and discrete data in the filtering process of unconnected points in fig. 3 (where each point represents an upstream bandwidth value).

Step4, the algorithm module realizes the relevant functions, takes the field time as input, and continuously calculates the real-time network parameters (namely, the target parameter values of the target network characteristic parameters at the testing time point are determined based on the network characteristic parameter set);

for example, the electronic device may calculate, according to the test time point t, the matrix function to obtain corresponding network parameters (uplink bandwidth, downlink bandwidth, delay, packet loss rate, and bit error rate), and form a data matrix as shown in table 1 below:

TABLE 1

In addition, the electronic device may divide a curve formed by the parameter values calculated by the fitting functions into infinite sections according to a differential principle, and convert the continuously changing curve into a step curve when each region tends to be infinitesimal, for example, as shown in fig. 4, convert the curve formed by the fitting function f1 (t, a) into a step curve, thereby making the simulated network closer to the real network.

And Step5, analyzing the data matrix, continuously calling an API (application programming interface) of the ATC tool according to the time point, and configuring real-time effect (namely calling the target parameter value to test the simulation network of the application program at the test time point).

In the embodiment of the present invention, a network feature parameter set of a real network where an electronic device is located is obtained, where each piece of data in the network feature parameter set includes: parameter values of the target network characteristic parameters and time points of the parameter values; determining a target parameter value of a target network characteristic parameter at a test time point based on the network characteristic parameter set; and calling the target parameter value to test the simulation network of the application program at the test time point. Therefore, the difference between the network environment of the simulation network and the network environment of the real network can be reduced, and the testing accuracy of the application program is further improved.

Referring to fig. 5, fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, where theelectronic device 500 includes:

a parameter set obtainingmodule 501, configured to obtain a network feature parameter set of a real network where the electronic device is located, where each data in the network feature parameter set includes: parameter values of the target network characteristic parameters and time points of the parameter values;

a parametervalue determining module 502, configured to determine a target parameter value of a target network feature parameter at a test time point based on the network feature parameter set;

thetesting module 503 is configured to invoke the target parameter value to perform a test on the simulation network of the application program at the testing time point.

Optionally, as shown in fig. 6, the parametervalue determining module 502 includes:

amodel construction unit 5021, configured to construct a time distribution model of the target network feature parameter based on the network feature parameter set;

a parametervalue obtaining unit 5022, configured to obtain a parameter value of the target network characteristic parameter at the test time point based on the time distribution model.

Optionally, themodel building unit 5021 is specifically configured to:

and fitting the data in the network characteristic parameter set to generate a time distribution model of the target network characteristic parameters.

Optionally, as shown in fig. 7, theelectronic device 500 further includes:

afiltering module 504, configured to perform filtering processing on the data in the network feature parameter set to obtain a filtered network feature parameter set;

themodel construction unit 5021 is specifically configured to:

and constructing a time distribution model of the network characteristic parameters based on the network characteristic parameter set after filtering processing.

Optionally, the parameter set obtainingmodule 501 is specifically configured to:

and when the preset interval duration is detected to be reached, acquiring a network characteristic parameter set of a real network where the electronic equipment is located.

Theelectronic device 500 can implement the processes implemented by the electronic device in the foregoing embodiments and achieve the same beneficial effects, and in order to avoid repetition, the details are not repeated here.

Fig. 8 is a schematic diagram of a hardware structure of an electronic device for implementing various embodiments of the present invention, where theelectronic device 800 includes, but is not limited to: aradio frequency unit 801, anetwork module 802, anaudio output unit 803, aninput unit 804, asensor 805, adisplay unit 806, auser input unit 807, aninterface unit 808, amemory 809, aprocessor 810, and apower supply 811. Thedisplay unit 806 is a display screen. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 8 does not constitute a limitation of electronic devices, which may include more or fewer components than shown, or some components may be combined, or a different arrangement of components. In the embodiment of the present invention, the electronic device includes, but is not limited to, a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle-mounted electronic device, a wearable device, a pedometer, and the like.

Wherein theprocessor 810 is configured to:

acquiring a network characteristic parameter set of a real network where the electronic device is located, wherein each data in the network characteristic parameter set comprises: parameter values of the target network characteristic parameters and time points of the parameter values;

determining a target parameter value of a target network characteristic parameter at a test time point based on the network characteristic parameter set;

and calling the target parameter value to test the simulation network of the application program at the test time point.

Aprocessor 810 further configured to:

constructing a time distribution model of the target network characteristic parameter based on the network characteristic parameter set;

and acquiring parameter values of the target network characteristic parameters of the test time points based on the time distribution model.

Optionally, theprocessor 810 is further configured to:

and fitting the data in the network characteristic parameter set to generate a time distribution model of the target network characteristic parameters.

Optionally, theprocessor 810 is further configured to:

filtering the data in the network characteristic parameter set to obtain a filtered network characteristic parameter set;

and constructing a time distribution model of the network characteristic parameters based on the network characteristic parameter set after filtering processing.

Optionally, theprocessor 810 is further configured to:

and when the preset interval duration is detected to be reached, acquiring a network characteristic parameter set of a real network where the electronic equipment is located.

Theelectronic device 800 can implement the processes implemented by the electronic device in the foregoing embodiments and achieve the same beneficial effects, and for avoiding repetition, the details are not repeated here.

It should be understood that, in the embodiment of the present invention, theradio frequency unit 801 may be used for receiving and sending signals during a message sending and receiving process or a call process, and specifically, receives downlink data from a base station and then processes the received downlink data to theprocessor 810; in addition, uplink data is transmitted to the base station. In general,radio frequency unit 801 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like. Further, theradio frequency unit 801 may also communicate with a network and other devices through a wireless communication system.

The electronic device provides wireless broadband internet access to the user via thenetwork module 802, such as to assist the user in sending and receiving e-mails, browsing web pages, and accessing streaming media.

Theaudio output unit 803 may convert audio data received by theradio frequency unit 801 or thenetwork module 802 or stored in thememory 809 into an audio signal and output as sound. Also, theaudio output unit 803 may also provide audio output related to a specific function performed by the electronic apparatus 800 (e.g., a call signal reception sound, a message reception sound, etc.). Theaudio output unit 803 includes a speaker, a buzzer, a receiver, and the like.

Theinput unit 804 is used for receiving an audio or video signal. Theinput Unit 804 may include a Graphics Processing Unit (GPU) 8041 and amicrophone 8042, and theGraphics processor 8041 processes image data of still pictures or video obtained by an image capturing device (such as a camera) in a video capturing mode or an image capturing mode. The processed image frames may be displayed on thedisplay unit 806. The image frames processed by thegraphics processor 8041 may be stored in the memory 809 (or other storage medium) or transmitted via theradio unit 801 or thenetwork module 802. Themicrophone 8042 can receive sound, and can process such sound into audio data. The processed audio data may be converted into a format output transmittable to a mobile communication base station via theradio frequency unit 801 in case of the phone call mode.

Theelectronic device 800 also includes at least onesensor 805, such as light sensors, motion sensors, and other sensors. Specifically, the light sensor includes an ambient light sensor that can adjust the brightness of thedisplay panel 8061 according to the brightness of ambient light and a proximity sensor that can turn off thedisplay panel 8061 and/or the backlight when theelectronic device 800 is moved to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), detect the magnitude and direction of gravity when stationary, and can be used to identify the posture of the electronic device (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration identification related functions (such as pedometer, tapping), and the like; thesensors 805 may also include fingerprint sensors, pressure sensors, iris sensors, molecular sensors, gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., which are not described in detail herein.

Thedisplay unit 806 is used to display information input by the user or information provided to the user. TheDisplay unit 806 may include aDisplay panel 8061, and theDisplay panel 8061 may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like.

Theuser input unit 807 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic apparatus. Specifically, theuser input unit 807 includes atouch panel 8071 andother input devices 8072. Thetouch panel 8071, also referred to as a touch screen, may collect touch operations by a user on or near the touch panel 8071 (e.g., operations by a user on or near thetouch panel 8071 using a finger, a stylus, or any other suitable object or accessory). Thetouch panel 8071 may include two portions of a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to theprocessor 810, receives a command from theprocessor 810, and executes the command. In addition, thetouch panel 8071 can be implemented by various types such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. In addition to thetouch panel 8071, theuser input unit 807 can includeother input devices 8072. In particular,other input devices 8072 may include, but are not limited to, a physical keyboard, function keys (e.g., volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which are not described in detail herein.

Further, thetouch panel 8071 can be overlaid on thedisplay panel 8061, and when thetouch panel 8071 detects a touch operation on or near thetouch panel 8071, the touch operation is transmitted to theprocessor 810 to determine the type of the touch event, and then theprocessor 810 provides a corresponding visual output on thedisplay panel 8061 according to the type of the touch event. Although in fig. 8, thetouch panel 8071 and thedisplay panel 8061 are two independent components to implement the input and output functions of the electronic device, in some embodiments, thetouch panel 8071 and thedisplay panel 8061 may be integrated to implement the input and output functions of the electronic device, and the implementation is not limited herein.

Theinterface unit 808 is an interface through which an external device is connected to theelectronic apparatus 800. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input/output (I/O) port, a video I/O port, an earphone port, and the like. Theinterface unit 808 may be used to receive input (e.g., data information, power, etc.) from external devices and transmit the received input to one or more elements within theelectronic device 800 or may be used to transmit data between theelectronic device 800 and external devices.

Thememory 809 may be used to store software programs as well as various data. Thememory 809 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, thememory 809 can include high speed random access memory, and can also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

Theprocessor 810 is a control center of the electronic device, connects various parts of the whole electronic device by using various interfaces and lines, performs various functions of the electronic device and processes data by operating or executing software programs and/or modules stored in thememory 809 and calling data stored in thememory 809, thereby integrally monitoring the electronic device.Processor 810 may include one or more processing units; preferably, theprocessor 810 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated intoprocessor 810.

Theelectronic device 800 may also include a power supply 811 (e.g., a battery) for powering the various components, and preferably, thepower supply 811 may be logically coupled to theprocessor 810 via a power management system to manage charging, discharging, and power consumption management functions via the power management system.

In addition, theelectronic device 800 includes some functional modules that are not shown, and are not described in detail herein.

Preferably, an embodiment of the present invention further provides an electronic device, which includes aprocessor 810, amemory 809, and a computer program that is stored in thememory 809 and can be run on theprocessor 810, and when the computer program is executed by theprocessor 810, the processes of the embodiment of the testing method for an application program are implemented, and the same technical effect can be achieved, and in order to avoid repetition, details are not described here again.

The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the above-mentioned test method embodiment of the application program, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a component of' 8230; \8230;" does not exclude the presence of another like element in a process, method, article, or apparatus that comprises the element.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention or portions thereof contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling an electronic device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method of the embodiments of the present invention.

While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (6)

1. A test method of an application program is applied to electronic equipment, and is characterized by comprising the following steps:

acquiring a network characteristic parameter set of a real network where the electronic device is located, wherein each data in the network characteristic parameter set comprises: parameter values of the target network characteristic parameters and time points of the parameter values;

determining parameter values of target network characteristic parameters at the test time point based on the network characteristic parameter set, including: constructing a time distribution model of the target network characteristic parameter based on the network characteristic parameter set; acquiring parameter values of target network characteristic parameters of the test time points based on the time distribution model; the constructing a time distribution model of the target network characteristic parameter based on the network characteristic parameter set comprises: fitting the data in the network characteristic parameter set to generate a time distribution model of the target network characteristic parameter, wherein the time point of the parameter value of the target network characteristic parameter is an independent variable of a fitting function, and the parameter value is used as a dependent variable; before the constructing the time distribution model of the target network characteristic parameter based on the network characteristic parameter set, the method further includes: filtering the data in the network characteristic parameter set to obtain a filtered network characteristic parameter set; the constructing a time distribution model of the target network characteristic parameter based on the network characteristic parameter set comprises: constructing a time distribution model of the network characteristic parameters based on the filtered network characteristic parameter set;

and calling the parameter values of the target network characteristic parameters to test the simulation network of the application program at the test time point.

2. The method of claim 1, wherein the obtaining of the set of network feature parameters of the real network where the electronic device is located comprises:

and when the preset interval duration is detected to be reached, acquiring a network characteristic parameter set of a real network where the electronic equipment is located.

3. An electronic device, comprising:

a parameter set obtaining module, configured to obtain a network feature parameter set of a real network where the electronic device is located, where each piece of data in the network feature parameter set includes: parameter values of the target network characteristic parameters and time points of the parameter values;

a parameter value determining module, configured to determine a parameter value of a target network feature parameter at a test time point based on the network feature parameter set, including: the model construction unit is used for constructing a time distribution model of the target network characteristic parameter based on the network characteristic parameter set; a parameter value obtaining unit, configured to obtain a parameter value of a target network characteristic parameter at the test time point based on the time distribution model; the constructing a time distribution model of the target network characteristic parameter based on the network characteristic parameter set comprises: fitting the data in the network characteristic parameter set to generate a time distribution model of the target network characteristic parameter, wherein the time point of the parameter value of the target network characteristic parameter is an independent variable of a fitting function, and the parameter value is used as a dependent variable; further comprising: the filtering module is used for filtering the data in the network characteristic parameter set to obtain a filtered network characteristic parameter set; the model building unit is specifically configured to: constructing a time distribution model of the network characteristic parameters based on the filtered network characteristic parameter set;

and the test module is used for calling the parameter value of the target network characteristic parameter to test the simulation network of the application program at the test time point.

4. The electronic device of claim 3, wherein the parameter set obtaining module is specifically configured to:

and when the preset interval duration is detected to be reached, acquiring a network characteristic parameter set of a real network where the electronic equipment is located.

5. An electronic device, comprising a processor, a memory and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the method for testing an application program according to any one of claims 1 to 2.

6. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of a method for testing an application program according to any one of claims 1 to 2.

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