1. An automatic evaluation method for intelligent white electricity products is characterized by comprising the following steps:

respectively designing corresponding test cases aiming at least one control function of a preset white power product;

executing the test case corresponding to each control function by adopting a plurality of clients of the preset white power products of different brands, and recording the execution process of each test case;

and analyzing the evaluation condition of each control function of the preset white electricity products of different brands on a preset index according to the recorded execution process of each test case.

2. The method according to claim 1, wherein said recording the execution process of each of the test cases comprises: and recording the execution process of executing each test case by the client in a mobile phone screen recording mode.

3. The method of claim 2,

the preset index comprises a control success rate;

the method for executing the test case corresponding to each control function by adopting the client of the preset white power products of different brands comprises the following steps: executing preset times by adopting a plurality of clients of the preset white power products of different brands aiming at the test case corresponding to each control function;

the analyzing the evaluation condition of each control function of the preset white electricity products of different brands on a preset index according to the recorded execution process of each test case comprises the following steps:

determining each execution result of each test case in an image recognition mode, wherein the execution results comprise control success and control failure;

counting execution results of preset times of test cases of each control function aiming at preset white power products of each brand to obtain corresponding first statistical data;

determining a first bidding competitive product corresponding to each control function according to the first statistical data, wherein the first bidding competitive product is a bidding competitive product aiming at the control success rate of the corresponding control function;

and determining the difference of the preset white electricity product of the brand and each first bidding post bidding article aiming at the control success rate of the corresponding control function.

4. The method of claim 3, wherein the determining the result of each execution of each test case by image recognition comprises:

if the interface of the client side is changed after the client side executes the test case, the control is successful; and if the interface of the client does not change after the client executes the test case, the control fails.

5. The method of claim 2,

the preset index comprises control response time;

the analyzing the evaluation condition of each control function of the preset white electricity products of different brands on a preset index according to the recorded execution process of each test case comprises the following steps:

determining control response time corresponding to each test case according to the recorded execution process of each test case;

counting the control response time of the client of the preset white power product of each brand aiming at the test case corresponding to each control function respectively to obtain corresponding second statistical data;

determining a second bidding competitive product corresponding to each control function according to the second statistical data, wherein the second bidding competitive product is a bidding competitive product aiming at the corresponding control function in the control response time; the shorter the control response time is, the better the performance of the preset white power product is;

and determining the difference of the preset white electricity product of the brand and each second bidding post competitive product in the control response time for the corresponding control function.

6. The method of claim 5, wherein the determining the control response time corresponding to each of the test cases comprises:

writing case analysis scripts, and adopting the case analysis scripts to embed points of the starting point and the end point of each test case respectively; calculating the control response time of each test case according to the embedded points corresponding to the starting point and the end point of each test case respectively;

or analyzing the execution process of each test case in an image recognition mode, and determining a starting frame and an ending frame of the execution process; and converting the frame number difference between the starting frame and the ending frame into corresponding time, and taking the time as the control response time of each test case.

7. The method of claim 5, wherein determining a second bid amount for each control function based on the second statistical data comprises:

writing a data import plug-in, importing the second statistical data into data analysis equipment by using the data import plug-in, so that the data analysis equipment determines the difference of preset white power products of different brands in control response time for each control function in a 2-second traversal mode;

and determining the second bidding target bidding competitive products corresponding to the control functions respectively according to the difference of the preset white electricity products of different brands on the control response time of the control functions.

8. The method of claim 1, wherein the smart white electricity appliance is an air conditioner and the control function comprises temperature control, voice control, wind speed control and/or mode switching.

9. The method according to claim 8, wherein the control function includes mode switching, and the executing the test case corresponding to each control function by the client using the preset white electricity products of different brands comprises:

and executing a corresponding test case by adopting a plurality of clients of the preset white electricity products of different brands to switch modes, so that the test case determines a corresponding target control according to the identity and the name, calling a function method corresponding to mode switching to generate a mode switching instruction, and sending the mode switching instruction to the target control.

10. The utility model provides an automatic evaluation device of intelligence white electricity product which characterized in that includes:

the case design module is used for respectively designing corresponding test cases aiming at least one control function of a preset white power supply product;

the case execution erasing is used for executing the test case corresponding to each control function by adopting the client sides of the preset white electricity products of a plurality of different brands and recording the execution process of each test case;

and the case analysis module is used for analyzing the evaluation condition of each control function of the preset white electricity products of different brands on a preset index according to the recorded execution process of each test case.

Background

With the development of companies, the business of companies is continuously expanded, the product series is more and more, the control success rate and the control response time of the intelligent white power supply product can greatly influence the user experience, in order to improve the user experience, a test experiment needs to be carried out on the control success rate and the control response time of the intelligent white power supply product, then data analysis is carried out, the performance gap between the intelligent white power supply product and the like products in the same industry is found, and therefore the performance of the product per se is improved and perfected according to the performance gap so as to improve the user experience effect. Specifically, the same functions of a certain product of different companies in the same industry are evaluated and analyzed, so that the control success rate and the control response time are contrastively analyzed, the bid bar competitive products are screened out, the key success factors leading the bid bar competitive products in the aspect of user experience are analyzed, the key links and the influence factors which restrict the user experience of the intelligent white power products of the company are found, and the key links and the influence factors are improved and perfected.

In the prior art, when user experience of a software product needs to be determined, a certain device is often controlled through manual operation, operation related data is recorded, data is analyzed manually or by combining tools, too many people are needed to participate, efficiency is reduced, subjective factors are easily brought in, and objective accuracy of evaluation and analysis is reduced.

Disclosure of Invention

One or more embodiments of the specification describe an automatic evaluation method and device for an intelligent white electricity product.

According to a first aspect, an automatic evaluation method for intelligent white electricity products is provided, which comprises the following steps:

respectively designing corresponding test cases aiming at least one control function of a preset white power product;

executing the test case corresponding to each control function by adopting a plurality of clients of the preset white power products of different brands, and recording the execution process of each test case;

and analyzing the evaluation condition of each control function of the preset white electricity products of different brands on a preset index according to the recorded execution process of each test case.

According to a second aspect, an automatic evaluation device for intelligent white electricity products is provided, which comprises:

the case design module is used for respectively designing corresponding test cases aiming at least one control function of a preset white power supply product;

the case execution erasing is used for executing the test case corresponding to each control function by adopting the client sides of the preset white electricity products of a plurality of different brands and recording the execution process of each test case;

and the case analysis module is used for analyzing the evaluation condition of each control function of the preset white electricity products of different brands on a preset index according to the recorded execution process of each test case.

According to the automatic evaluation method and device for the intelligent white power products, the corresponding test cases are designed according to different control functions, then the test cases are executed by adopting the client sides of the preset white power products of different brands, the execution process is recorded, and the evaluation conditions of the preset white power products of different brands on different control functions can be analyzed according to the execution process. In the process, the preset white power products are not manually controlled, and the operation of the white power products is not manually evaluated, so that the participation of personnel is reduced, subjective factors brought by the participation of too many personnel can be reduced or avoided, the objective accuracy of evaluation analysis is improved, and the evaluation efficiency is improved.

Drawings

In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, 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 some embodiments of the present specification, and other drawings can be obtained by those skilled in the art without creative efforts.

Fig. 1 is a schematic flowchart of an automated evaluation method for an intelligent white electricity product in one embodiment of the present specification.

Detailed Description

The scheme provided by the specification is described below with reference to the accompanying drawings.

As shown in fig. 1, an embodiment of the present application provides an automated evaluation method for an intelligent white power product, including the following steps S100 to S300:

s100, respectively designing corresponding test cases aiming at least one control function of a preset white power product;

the preset white electricity product can be a household appliance such as a refrigerator and an air conditioner.

The control function may be temperature control, voice control, wind speed control and/or mode switching.

In specific implementation, the UI package of airtest tool can be used for developing the test case. And developing a corresponding test case for each control function.

S200, executing the test case corresponding to each control function by adopting a plurality of clients of the preset white power products of different brands, and recording the executing process of each test case;

for example, for a white electricity product, air conditioners, which are similar in function, are selected to execute test cases, and apps corresponding to the air conditioners of the companies specifically execute the test cases corresponding to temperature control and mode switching, so that the two functions of temperature control and mode switching are evaluated.

It can be understood that the client sends the control instruction to the corresponding preset white power supply product when executing the test case, and then the preset white power supply product executes the control instruction and returns corresponding feedback data to the client.

In specific implementation, the execution process of each test case executed by the client can be recorded in a screen recording mode of a mobile phone. Certainly, an app corresponding to a brand of preset white electricity product can be logged in by one mobile phone, the test case is executed through the app, and the execution process of the app is shot by the other mobile phone, so that the execution process of each test case is recorded. After the test case is executed, the recorded video is obtained, and the video recorded by the mobile phone is imported to data analysis equipment, such as a notebook computer, a desktop computer, an ipad and the like. And then, analyzing the video on the data analysis equipment by adopting a video analysis tool which is downloaded in advance, namely analyzing the execution process of the test case.

S300, analyzing the evaluation condition of each control function of the preset white electricity products of different brands on a preset index according to the recorded execution process of each test case.

The preset indexes can include a control success rate and a control response time, the control success rate refers to the success rate of control over the preset white power supply product when the app executes the test case, and the control response time refers to the response time from sending a control instruction to the preset white power supply product to receiving feedback data returned by the preset white power supply product when the app executes the test case.

That is to say, in S300, the video of the test case executed according to the app of the preset white electricity product of each brand can be obtained, and the relevant data of the execution process can be obtained, so that the evaluation condition can be obtained.

In specific implementation, the preset index includes a control success rate, and at this time, the S200 may specifically include: and executing preset times by adopting a plurality of clients of the preset white electricity products of different brands aiming at the test case corresponding to each control function.

The preset number of times may be set as needed, for example, the preset number of times is set to 100. That is, the app of each brand of preset white electricity product is executed 100 times for each test case of the control function. For example, the control function includes temperature control and wind speed control, a total of 3 brands of air-conditioning products are selected for evaluation, and the app of each of the 3 air-conditioning products is executed 100 times for the test case of temperature control and 100 times for the test case corresponding to wind speed control. That is, the recorded execution procedure is 600 execution procedures.

Correspondingly, S300 may include the following S310 to S340:

s310, determining each execution result of each test case in an image recognition mode, wherein the execution results comprise control success and control failure;

wherein, aiming at the control success rate, the corresponding execution results have two types: control success and control failure. When the control succeeds in executing the test case through the app, a control instruction is sent to the corresponding white power supply product, the white power supply product successfully executes the control instruction, and when the control fails, the white power supply product does not receive the control instruction sent by the app, or the control instruction is executed in error.

During specific implementation, the app sends a corresponding control instruction to a corresponding white power supply product when executing a test case, the white power supply product receives the control instruction and executes the control instruction, and returns feedback data, if the feedback data are results of successful execution such as successful temperature setting and successful mode switching, the original data are modified into successfully set data by the interface of the app, for example, the original air conditioner temperature on the interface of the app is-2 ℃, and after executing a temperature-controlled test case, the air conditioner temperature is set to 0 ℃, so that the interface of the app becomes 0 ℃, and a visible interface changes. However, if the white power supply does not receive the control instruction, the control instruction will not be executed and feedback data will not be returned, or if the white power supply has an error in executing the control instruction, a result of execution failure such as failure in temperature setting and failure in mode switching will be returned, and the original data on the interface of the app will remain unchanged and will not change. Based on this, S310 may specifically include: if the interface of the client side is changed after the client side executes the test case, the control is successful; and if the interface of the client does not change after the client executes the test case, the control fails.

It can be understood that, on the data analysis device, a video analysis tool may be used to perform frame-by-frame analysis on the video, for example, clicking a video reading button may browse a first frame of the video, and then clicking once again may browse a second frame of the video, that is, the video may be browsed frame-by-frame by clicking, and then the video may be analyzed frame-by-frame to determine whether the interface changes.

S320, counting execution results of preset times of the test cases of the preset white power products of all brands for all control functions to obtain corresponding first statistical data;

for each brand of preset white power products, for each control function, one test case is executed for a preset number of times, some execution results are successful in control, and some execution results are failed in control, so that the control success rate of the test case of the brand of preset white power products for the control function can be obtained. By the method, the control success rate of the preset white power products of each brand aiming at the test cases of each control function can be obtained, and first statistical data can be obtained. Specifically, an excell table may be set, and the control success rate of the preset white power products of each brand corresponding to the test case of each control function is recorded in the excell table.

S330, determining a first bid pole bidding article corresponding to each control function according to the first statistical data, wherein the first bid pole bidding article is a bid pole bidding article aiming at the control success rate of the corresponding control function;

it can be understood that, for each control function, different brands of preset white power products have different control success rates, and the preset white power product with the highest control success rate is used as a bidding post competitive product corresponding to the control function. For example, there are a total of 4 control functions, so that 4 bid bids can be screened from the first statistical data.

Of course, besides selecting a first bid bar competition product for each control function, a comprehensive bid bar competition product can be screened for all the control functions, and the comprehensive control success rate of the comprehensive bid bar competition product on each control function is highest.

S340, determining the difference of the preset white power products of the brand and each first bidding post bidding article aiming at the corresponding control function in the control success rate.

Through comparing the preset white electricity product of the brand with each first bid bar bidding article on the control success rate, the difference of the preset white electricity product of the brand and each first bid bar bidding article on different control functions can be known. Therefore, key influence factors leading each first bid post competitive product in the corresponding control function can be analyzed subsequently, and then the preset white power products of the brand are improved according to the key factors, so that the product performance of the brand is improved, and the user experience is improved.

Certainly, the preset white electricity product of the brand and the comprehensive bid bar competitive products can be compared on each control function, so that the leading key influence factors of the comprehensive bid bar competitive products are analyzed, the preset white electricity product of the brand is improved according to the key factors, the product performance of the brand is improved, and the user experience is improved.

In a specific implementation, the preset indicator may include a control response time. At this time, S300 may specifically include the following steps S350 to S390:

s350, determining control response time corresponding to each test case according to the recorded execution process of each test case;

in a specific implementation, S350 may specifically include: writing case analysis scripts, and adopting the case analysis scripts to embed points of the starting point and the end point of each test case respectively; and calculating the control response time of each test case according to the embedded points corresponding to the starting point and the end point of each test case respectively.

The use case analysis script can be specifically written by adopting a stagesepx tool. The case analysis script can analyze the starting point and the end point of the test case and can embed points on the starting point and the end point, wherein the embedding points are formed by punching one point on each of the two positions of the starting point and the end point. The control response time can be obtained by calculating the difference in the number of frames between these two points.

In a specific implementation, S350 may also specifically include: analyzing the execution process of each test case in an image recognition mode, and determining a starting frame and an ending frame of the execution process; and converting the frame number difference between the starting frame and the ending frame into corresponding time, and taking the time as the control response time of each test case.

Here, the start frame and the end frame of the execution process of each test case are identified by an image recognition technique, and the difference in frame number between the two frames is calculated, so that the difference in frame number is converted into time, thereby obtaining the control response time. The image recognition technology can specifically intercept two frames of images before and after the change through automatic comparison analysis of image changes before and after the test case is executed, and takes the former frame of image as a starting frame and the latter frame of image as an ending frame.

S360, counting the control response time of the client of each brand of the preset white power product aiming at the test case corresponding to each control function respectively to obtain corresponding second statistical data;

it can be understood that for each brand of preset white electricity product, there is one control response time for each control function. For example, for 5 white power products, 4 control functions, 20 control response times can be calculated, and the second statistical data can be obtained.

In specific implementation, each calculated control response time may be recorded in an excell table. For example, the column indicates the control response time of one white power product corresponding to each control function, and the row indicates the control response time of each white power product corresponding to each control function.

S370, determining a second bid bar bidding product corresponding to each control function according to the second statistical data, wherein the second bid bar bidding product is a bid bar bidding product aiming at the corresponding control function in the control response time; the shorter the control response time is, the better the performance of the preset white power product is;

it can be understood that, for each control function, different brands of preset white power products have different control response times, and the preset white power product with the smallest control response time is used as the bidding post competitive product corresponding to the control function. For example, there are 4 control functions in total, so that 4 second bid items can be screened from the second statistical data.

Of course, in addition to selecting a second bid bar bid for each control function, a comprehensive bid bar bid can be screened for all control functions, and the comprehensive control response time of the comprehensive bid bar bid on each control function is the minimum.

It can be understood that the smaller the control response time, the more excellent the performance of the white electricity product.

In a specific implementation, S370 may specifically include the following steps S371 to S372:

s371, compiling a data import plug-in, importing the second statistical data into data analysis equipment by using the data import plug-in, and enabling the data analysis equipment to determine the difference of preset white power products of different brands in control response time for each control function in a 2-second traversal mode;

specifically, a Python language can be adopted to write a data import plug-in, then the plug-in is adopted to import the second statistical data in the excell table into the data analysis equipment in batch, and the data analysis equipment is utilized to perform difference analysis.

The 2-second traversal mode is a mode of traversing each line in 2 seconds and comparing data of the line.

And S372, determining the second bidding post competitive products corresponding to the control functions respectively according to the difference of the preset white electricity products of different brands on the control response time of the control functions.

Therefore, the second bidding competitive product can be analyzed through the steps S371-S372.

And S380, determining the difference of the preset white electricity product of the brand and each second bidding post bidding article aiming at the corresponding control function in the control response time.

Through comparing the preset white electricity product of the brand with each second bid bar bidding article on the control response time, the difference of the preset white electricity product of the brand and each second bid bar bidding article on different control functions can be known. Therefore, key influence factors leading each second bid post competitive product in the corresponding control function can be analyzed subsequently, and then the preset white power products of the brand are improved according to the key factors, so that the product performance of the brand is improved, and the user experience is improved.

Certainly, the preset white electricity product of the brand and the comprehensive bid bar competitive products can be compared on each control function, so that the leading key influence factors of the comprehensive bid bar competitive products are analyzed, the preset white electricity product of the brand is improved according to the key factors, the product performance of the brand is improved, and the user experience is improved.

For example, the intelligent white power supply is an air conditioner, the control function includes mode switching, and the process of executing the test case in S200 may include: and executing a corresponding test case by adopting a plurality of clients of the preset white electricity products of different brands to switch modes, so that the test case determines a corresponding target control according to the identity and the name, calling a function method corresponding to mode switching to generate a mode switching instruction, and sending the mode switching instruction to the target control.

That is to say, the test case can position the target control according to the name and the identity, and then generate the control instruction by using a function method, and send the control instruction to the target control, that is, to the preset white power product, so that the white power product executes the control instruction.

According to the automatic evaluation method of the intelligent white power supply product, the corresponding test cases are designed according to different control functions, then the test cases are executed by adopting the client sides of the preset white power supply products of different brands, the execution process is recorded, and the evaluation conditions of the preset white power supply products of different brands on different control functions can be analyzed according to the execution process. In the process, the preset white power products are not manually controlled, and the operation of the white power products is not manually evaluated, so that the participation of personnel is reduced, subjective factors brought by the participation of too many personnel can be reduced or avoided, the objective accuracy of evaluation analysis is improved, and the evaluation efficiency is improved. Namely, the human intervention is reduced, so that the evaluation result is more objective.

In a second aspect, the present invention provides an automatic evaluation device for intelligent white power products, comprising:

the case design module is used for respectively designing corresponding test cases aiming at least one control function of a preset white power supply product;

the case execution erasing is used for executing the test case corresponding to each control function by adopting the client sides of the preset white electricity products of a plurality of different brands and recording the execution process of each test case;

and the case analysis module is used for analyzing the evaluation condition of each control function of the preset white electricity products of different brands on a preset index according to the recorded execution process of each test case.

It is understood that, for the device provided in the embodiment of the present invention, for the explanation, examples, and beneficial effects of the related contents, reference may be made to the corresponding parts in the foregoing method, and details are not described here.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

Those skilled in the art will recognize that, in one or more of the examples described above, the functions described in this disclosure may be implemented in hardware, software, hardware, or any combination thereof. When implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium.

The above-mentioned embodiments, objects, technical solutions and advantages of the present invention are further described in detail, it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made on the basis of the technical solutions of the present invention should be included in the scope of the present invention.