CN113806223A - Software evaluation method and device - Google Patents
Software evaluation method and device Download PDFInfo
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- CN113806223A CN113806223A CN202111058421.6A CN202111058421A CN113806223A CN 113806223 A CN113806223 A CN 113806223A CN 202111058421 A CN202111058421 A CN 202111058421A CN 113806223 A CN113806223 A CN 113806223A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3692—Test management for test results analysis
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F11/36—Preventing errors by testing or debugging software
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Abstract
The invention discloses a software evaluation method and device. Wherein, the method comprises the following steps: acquiring a first software parameter; generating a second software parameter according to a preset rule and the first software parameter; inputting the second software parameter into an evaluation model to generate a software evaluation parameter; and generating a software evaluation result according to the software evaluation parameters. The invention solves the technical problems that the software testing and evaluating mode in the prior art often directly evaluates the parameters of the software, and the analysis mode and the rule used for evaluation are also fixed, so that the historical data cannot be flexibly changed in the software testing and evaluating process, and the accuracy of the testing and evaluating result is not high.
Description
Technical Field
The invention relates to the field of software test evaluation, in particular to a software evaluation method and device.
Background
Along with the continuous development of intelligent science and technology, people use intelligent equipment more and more among life, work, the study, use intelligent science and technology means, improved the quality of people's life, increased the efficiency of people's study and work.
At present, when software evaluation work is carried out, various direct parameters of software are tested according to the performance and indexes of the software, and an evaluation result generation operation is carried out according to a test result and a comparison result, but the traditional software test evaluation mode often directly evaluates the parameters of the software, and the analysis mode and the rule used for evaluation are fixed, so that the software cannot flexibly change with reference to historical data in the software test and evaluation process, and the accuracy of the test evaluation result is low.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides a software evaluation method and device, which at least solve the technical problems that software parameters are often directly evaluated in a software test evaluation mode in the prior art, and analysis modes and rules used for evaluation are fixed, so that the software test and evaluation process cannot flexibly change with reference to historical data, and the test evaluation result is not high in accuracy.
According to an aspect of an embodiment of the present invention, there is provided a software evaluation method including: acquiring a first software parameter; generating a second software parameter according to a preset rule and the first software parameter; inputting the second software parameter into an evaluation model to generate a software evaluation parameter; and generating a software evaluation result according to the software evaluation parameters.
Optionally, the generating a second software parameter according to a preset rule and the first software parameter includes: acquiring the preset rule; and comparing the rule elements in the preset rule with the elements in the first software parameters one by one to obtain a comparison result.
Optionally, after comparing the rule elements in the preset rule with the elements in the first software parameter one by one to obtain a comparison result, the method further includes: and generating the second software parameter according to the comparison result.
Optionally, before the second software parameter is input into the evaluation model to generate the software evaluation parameter, the method further includes: and training the evaluation model.
According to another aspect of the embodiments of the present invention, there is also provided a software evaluation apparatus including: the acquisition module is used for acquiring a first software parameter; the generating module is used for generating a second software parameter according to a preset rule and the first software parameter; the evaluation module is used for inputting the second software parameters into an evaluation model to generate software evaluation parameters; and the result module is used for generating a software evaluation result according to the software evaluation parameters.
Optionally, the generating module includes: an obtaining unit, configured to obtain the preset rule; and the comparison unit is used for comparing the rule elements in the preset rule with the elements in the first software parameters one by one to obtain a comparison result.
Optionally, the apparatus further comprises: and the generating module is further used for generating the second software parameter according to the comparison result.
Optionally, the apparatus further comprises: and the training module is used for training the evaluation model.
According to another aspect of the embodiments of the present invention, there is also provided a non-volatile storage medium, which includes a stored program, wherein the program controls a device in which the non-volatile storage medium is located to execute a software evaluation method when running.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including a processor and a memory; the memory has stored therein computer readable instructions, and the processor is configured to execute the computer readable instructions, wherein the computer readable instructions when executed perform a software evaluation method.
In the embodiment of the invention, a first software parameter is obtained; generating a second software parameter according to a preset rule and the first software parameter; inputting the second software parameter into an evaluation model to generate a software evaluation parameter; the method for generating the software evaluation result according to the software evaluation parameters solves the technical problems that the software evaluation method in the prior art often directly evaluates the parameters of the software, and the analysis mode and the rule used for evaluation are fixed, so that the software test and evaluation process cannot flexibly change with reference to historical data, and the accuracy of the test evaluation result is low.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a flow chart of a software evaluation method according to an embodiment of the invention;
fig. 2 is a block diagram of a software evaluation apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, 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 only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In accordance with an embodiment of the present invention, there is provided a method embodiment of a software evaluation method, it should be noted that the steps illustrated in the flowchart of the accompanying drawings may be performed in a computer system such as a set of computer executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than that herein.
Example one
Fig. 1 is a flow chart of a software evaluation method according to an embodiment of the present invention, as shown in fig. 1, the method including the steps of:
step S102, a first software parameter is obtained.
Specifically, in order to evaluate the target software and obtain a final software evaluation result according to the output processing of the model, the embodiment of the present invention first needs to obtain a first software parameter, where the first software parameter directly represents each direct parameter of the software to be evaluated, and the evaluation parameter is converted by the parameter.
And step S104, generating a second software parameter according to a preset rule and the first software parameter.
Optionally, the generating a second software parameter according to a preset rule and the first software parameter includes: acquiring the preset rule; and comparing the rule elements in the preset rule with the elements in the first software parameters one by one to obtain a comparison result.
Specifically, after obtaining the first software parameter, the embodiment of the present invention needs to generate a second software parameter according to whether the first software parameter meets a preset rule, where the second software parameter is directly used for being input into a software evaluation model, and outputting an evaluation result, for example, obtaining the preset rule; and comparing the rule elements in the preset rule with the elements in the first software parameters one by one to obtain a comparison result.
Optionally, after comparing the rule elements in the preset rule with the elements in the first software parameter one by one to obtain a comparison result, the method further includes: and generating the second software parameter according to the comparison result.
And S106, inputting the second software parameter into an evaluation model to generate a software evaluation parameter.
Specifically, after the second software parameter is obtained, the embodiment of the present invention inputs the second software parameter into a pre-trained evaluation model, and the evaluation model is constructed by using a DNN deep neural network and outputs a software evaluation parameter.
Since the second software parameter is information of software to be evaluated, the operation efficiency of using the second software parameter as input data and the software evaluation parameter as output data can be greatly increased by using the deep neural network model or the confrontation network model, as compared with the case where the evaluation parameter is directly calculated by the evaluation rule. For example, when the software evaluation is performed on the chat software a, the software information of the chat software a is subjected to parameter processing and extraction to obtain the software parameters to be evaluated: chat delay, login security. Then the processor generates an evaluation model calling instruction, calls the neural network evaluation model stored in the database, inputs the chatting delay and login security parameter data into the neural network evaluation model according to the input requirements of the model, simultaneously collects model output data at the output end of the model, the output data are evaluation parameters of the A-style chatting software, wherein the output data comprise millisecond-level data values of the chatting delay, risk items of login security and scoring conditions, and finally, a summarizing processing module of the processor summarizes the millisecond-level data values of the chatting delay, the risk items of login security and the scoring conditions to generate a software evaluation parameter (A).
Optionally, before the second software parameter is input into the evaluation model to generate the software evaluation parameter, the method further includes: and training the evaluation model.
Specifically, since the DNN deep neural network model needs to be trained through historical data, before the software evaluation is performed by using the evaluation model, the software evaluation model needs to be trained, and the trained evaluation model is used as a carrier for inputting the second software parameter.
And S108, generating a software evaluation result according to the software evaluation parameters.
Specifically, after the software evaluation parameters are acquired by the evaluation model, a software evaluation result which is finally displayed to a user for viewing and analysis needs to be further generated according to the software evaluation parameters, wherein the software evaluation result may be generated in the form of a software evaluation report.
By the embodiment, the technical problems that the software testing and evaluating mode in the prior art often directly evaluates the parameters of the software, and the analysis mode and the rule used for evaluation are fixed, so that the historical data cannot be flexibly changed in the software testing and evaluating process, and the accuracy of the testing and evaluating result is low are solved.
Example two
Fig. 2 is a block diagram of a software evaluation apparatus according to an embodiment of the present invention, and as shown in fig. 2, the method includes:
the obtaining module 20 is configured to obtain a first software parameter.
Specifically, in order to evaluate the target software and obtain a final software evaluation result according to the output processing of the model, the embodiment of the present invention first needs to obtain a first software parameter, where the first software parameter directly represents each direct parameter of the software to be evaluated, and the evaluation parameter is converted by the parameter.
And the generating module 22 is configured to generate a second software parameter according to a preset rule and the first software parameter.
Optionally, the generating module includes: an obtaining unit, configured to obtain the preset rule; and the comparison unit is used for comparing the rule elements in the preset rule with the elements in the first software parameters one by one to obtain a comparison result.
Specifically, after obtaining the first software parameter, the embodiment of the present invention needs to generate a second software parameter according to whether the first software parameter meets a preset rule, where the second software parameter is directly used for being input into a software evaluation model, and outputting an evaluation result, for example, obtaining the preset rule; and comparing the rule elements in the preset rule with the elements in the first software parameters one by one to obtain a comparison result.
Since the second software parameter is information of software to be evaluated, the operation efficiency of using the second software parameter as input data and the software evaluation parameter as output data can be greatly increased by using the deep neural network model or the confrontation network model, as compared with the case where the evaluation parameter is directly calculated by the evaluation rule. For example, when the software evaluation is performed on the chat software a, the software information of the chat software a is subjected to parameter processing and extraction to obtain the software parameters to be evaluated: chat delay, login security. Then the processor generates an evaluation model calling instruction, calls the neural network evaluation model stored in the database, inputs the chatting delay and login security parameter data into the neural network evaluation model according to the input requirements of the model, simultaneously collects model output data at the output end of the model, the output data are evaluation parameters of the A-style chatting software, wherein the output data comprise millisecond-level data values of the chatting delay, risk items of login security and scoring conditions, and finally, a summarizing processing module of the processor summarizes the millisecond-level data values of the chatting delay, the risk items of login security and the scoring conditions to generate a software evaluation parameter (A).
Optionally, the apparatus further comprises: and the generating module is further used for generating the second software parameter according to the comparison result.
And the evaluation module 24 is used for inputting the second software parameter into an evaluation model to generate a software evaluation parameter.
Specifically, after the second software parameter is obtained, the embodiment of the present invention inputs the second software parameter into a pre-trained evaluation model, and the evaluation model is constructed by using a DNN deep neural network and outputs a software evaluation parameter.
Optionally, the apparatus further comprises: and the training module is used for training the evaluation model.
Specifically, since the DNN deep neural network model needs to be trained through historical data, before the software evaluation is performed by using the evaluation model, the software evaluation model needs to be trained, and the trained evaluation model is used as a carrier for inputting the second software parameter.
And the result module 26 is used for generating a software evaluation result according to the software evaluation parameters.
Specifically, after the software evaluation parameters are acquired by the evaluation model, a software evaluation result which is finally displayed to a user for viewing and analysis needs to be further generated according to the software evaluation parameters, wherein the software evaluation result may be generated in the form of a software evaluation report.
According to another aspect of the embodiments of the present invention, there is also provided a non-volatile storage medium, which includes a stored program, wherein the program controls a device in which the non-volatile storage medium is located to execute a software evaluation method when running.
Specifically, the method comprises the following steps: acquiring a first software parameter; generating a second software parameter according to a preset rule and the first software parameter; inputting the second software parameter into an evaluation model to generate a software evaluation parameter; and generating a software evaluation result according to the software evaluation parameters.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including a processor and a memory; the memory has stored therein computer readable instructions, and the processor is configured to execute the computer readable instructions, wherein the computer readable instructions when executed perform a software evaluation method.
Specifically, the method comprises the following steps: acquiring a first software parameter; generating a second software parameter according to a preset rule and the first software parameter; inputting the second software parameter into an evaluation model to generate a software evaluation parameter; and generating a software evaluation result according to the software evaluation parameters.
By the embodiment, the technical problems that the software testing and evaluating mode in the prior art often directly evaluates the parameters of the software, and the analysis mode and the rule used for evaluation are fixed, so that the historical data cannot be flexibly changed in the software testing and evaluating process, and the accuracy of the testing and evaluating result is low are solved.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A software evaluation method, comprising:
acquiring a first software parameter;
generating a second software parameter according to a preset rule and the first software parameter;
inputting the second software parameter into an evaluation model to generate a software evaluation parameter;
and generating a software evaluation result according to the software evaluation parameters.
2. The method of claim 1, wherein the generating second software parameters according to the preset rules and the first software parameters comprises:
acquiring the preset rule;
and comparing the rule elements in the preset rule with the elements in the first software parameters one by one to obtain a comparison result.
3. The method according to claim 2, wherein after comparing the rule elements in the preset rule with the elements in the first software parameter one by one to obtain a comparison result, the method further comprises:
and generating the second software parameter according to the comparison result.
4. The method of claim 1, wherein prior to said inputting said second software parameter into an evaluation model to generate a software evaluation parameter, said method further comprises:
and training the evaluation model.
5. A software evaluation apparatus, comprising:
the acquisition module is used for acquiring a first software parameter;
the generating module is used for generating a second software parameter according to a preset rule and the first software parameter;
the evaluation module is used for inputting the second software parameters into an evaluation model to generate software evaluation parameters;
and the result module is used for generating a software evaluation result according to the software evaluation parameters.
6. The apparatus of claim 5, wherein the generating module comprises:
an obtaining unit, configured to obtain the preset rule;
and the comparison unit is used for comparing the rule elements in the preset rule with the elements in the first software parameters one by one to obtain a comparison result.
7. The apparatus of claim 6, further comprising:
and the generating module is further used for generating the second software parameter according to the comparison result.
8. The apparatus of claim 5, further comprising:
and the training module is used for training the evaluation model.
9. A non-volatile storage medium, comprising a stored program, wherein the program, when executed, controls an apparatus in which the non-volatile storage medium is located to perform the method of any one of claims 1 to 4.
10. An electronic device comprising a processor and a memory; the memory has stored therein computer readable instructions for execution by the processor, wherein the computer readable instructions when executed perform the method of any one of claims 1 to 4.
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| CN202111058421.6A CN113806223A (en) | 2021-09-10 | 2021-09-10 | Software evaluation method and device |
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| CN109491709A (en) * | 2018-10-29 | 2019-03-19 | 北京计算机技术及应用研究所 | A kind of software code degree of controllability integrated evaluating method based on AHP and neural network |
| US20200183811A1 (en) * | 2018-12-06 | 2020-06-11 | Microsoft Technology Licensing, Llc | Automatically Performing and Evaluating Pilot Testing of Software |
| CN113313615A (en) * | 2021-06-23 | 2021-08-27 | 北京鼎泰智源科技有限公司 | Method and device for quantitatively grading and grading enterprise judicial risks |
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- 2021-09-10 CN CN202111058421.6A patent/CN113806223A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109117380A (en) * | 2018-09-28 | 2019-01-01 | 中国科学院长春光学精密机械与物理研究所 | A kind of method for evaluating software quality, device, equipment and readable storage medium storing program for executing |
| CN109491709A (en) * | 2018-10-29 | 2019-03-19 | 北京计算机技术及应用研究所 | A kind of software code degree of controllability integrated evaluating method based on AHP and neural network |
| US20200183811A1 (en) * | 2018-12-06 | 2020-06-11 | Microsoft Technology Licensing, Llc | Automatically Performing and Evaluating Pilot Testing of Software |
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