CN113537781A

CN113537781A - Mobile terminal software evaluation method, device, storage medium and equipment

Info

Publication number: CN113537781A
Application number: CN202110813595.2A
Authority: CN
Inventors: 王瑞
Original assignee: Jianxin Rongtong Co ltd
Current assignee: Jianxin Rongtong Co ltd
Priority date: 2021-07-19
Filing date: 2021-07-19
Publication date: 2021-10-22

Abstract

The application discloses a mobile terminal software evaluation method, a mobile terminal software evaluation device, a storage medium and equipment. And constructing a hierarchical architecture model based on each primary index and each secondary index associated with each primary index. And respectively calculating the weight of each primary index in the index level to which the primary index belongs and the weight of each secondary index in the index level to which the secondary index belongs. And scoring each secondary index associated with the primary index to obtain the evaluation score of each secondary index associated with the primary index, and obtaining the evaluation score of the primary index according to the evaluation score of each secondary index associated with the primary index. And carrying out weighted summation on the evaluation score of each primary index to obtain the total evaluation score of the mobile terminal software. Therefore, by using the scheme of the application, the evaluation result of the mobile terminal software can be effectively provided for the software developer, so that the developer can improve the quality of the mobile terminal software according to the evaluation result.

Description

Mobile terminal software evaluation method, device, storage medium and equipment

Technical Field

The present application relates to the field of software development, and in particular, to a method, an apparatus, a storage medium, and a device for evaluating mobile-side software.

Background

With the rapid development of the information age, the pace of mobile internet is also continuously advancing, and the technological revolution is changing people's lives little by little. Mobile terminal software (APP for short) has become an indispensable product in people's daily life as a carrier and an important component of mobile internet. Therefore, how to develop and how to develop a high-quality mobile phone APP with high quality have great practical significance for the development of the mobile internet. Currently, mobile phone APP is generally evaluated, so as to determine the quality of the mobile phone APP.

The current mainstream software evaluation theory and method, such as ISO/IEC 9126, is proposed and established in 1993 before the age of mobile internet, and is mainly used for evaluating whether an early large computer system can achieve expected effects, while for mobile-end software in an emerging age, the evaluation result obtained by using the existing evaluation method has no reference value, and cannot provide any effective help for software developers.

Therefore, how to effectively evaluate the mobile terminal software becomes a problem which needs to be solved in the field.

Disclosure of Invention

The application provides a mobile terminal software evaluation method, a mobile terminal software evaluation device, a storage medium and equipment, and aims to provide effective evaluation results of mobile terminal software for software developers, so that the developers can improve the quality of the mobile terminal software according to the evaluation results.

In order to achieve the above object, the present application provides the following technical solutions:

a mobile terminal software evaluation method comprises the following steps:

generating an evaluation index set according to a preset index generation rule; the evaluation index set comprises a plurality of first-level indexes and each second-level index associated with each first-level index;

constructing a hierarchical architecture model based on each primary index and each secondary index associated with each primary index, wherein the hierarchical architecture model is used for indicating the index level of each index in the evaluation index set; each first-level index belongs to the same index level, and each second-level index associated with each first-level index belongs to the same index level;

respectively calculating the weight of each primary index in the index level to which the primary index belongs and the weight of each secondary index in the index level to which the secondary index belongs;

for each primary index, when the weight of each secondary index associated with the primary index passes consistency verification, scoring each secondary index associated with the primary index to obtain an evaluation score of each secondary index associated with the primary index, and obtaining the evaluation score of the primary index according to the evaluation score of each secondary index associated with the primary index;

and when the weight of each primary index passes consistency verification, carrying out weighted summation on the evaluation score of each primary index to obtain the total evaluation score of the mobile terminal software.

Optionally, the calculating the weight of each primary indicator in the indicator level to which the primary indicator belongs and the weight of each secondary indicator in the indicator level to which the secondary indicator belongs respectively includes:

aiming at each first-level index, comparing the first-level index with other first-level indexes to obtain a first judgment matrix; the other first-level indexes and the first-level indexes belong to the same index level;

calculating a quotient value of each element in the first judgment matrix and a first numerical value to obtain a first standard judgment matrix; the first value is: the cumulative sum of all elements in the column in which the element is located;

calculating the arithmetic mean value of each element contained in each row in the first standard judgment matrix to obtain the weight of the first-level index and the weight of the other first-level indexes;

aiming at each secondary index, comparing the secondary index with other secondary indexes to obtain a second judgment matrix; the other secondary indexes and the secondary indexes belong to the same index level;

calculating a quotient value of each element in the second judgment matrix and a second numerical value to obtain a second standard judgment matrix; the second value is: the cumulative sum of all elements in the column in which the element is located;

and calculating the arithmetic mean value of each element contained in each row in the second standard judgment matrix to obtain the weight of the secondary index and the weight of the other secondary indexes.

Optionally, for each primary index, when the weight of each secondary index associated with the primary index passes consistency verification, scoring each secondary index associated with the primary index to obtain an evaluation score of each secondary index associated with the primary index, including:

for each secondary index associated with the primary index, comparing the secondary index with other secondary indexes to obtain a second judgment matrix; the other secondary indexes and the secondary indexes belong to the same index level;

analyzing the second judgment matrix to obtain the column vector of the second-level index and the column vectors of the other second-level indexes;

carrying out weighted summation on the column vectors of the second-level indexes and the column vectors of the other second-level indexes to obtain weighted vectors;

analyzing the weighted vector to obtain the weighted value of the secondary index and the weighted values of the other secondary indexes;

calculating the weighted value and the ratio of the weighted values of the secondary indexes to obtain a first characteristic value;

aiming at the other secondary indexes, calculating the weighted value and the weighted ratio of the other secondary indexes to obtain a second characteristic value;

calculating an arithmetic mean value of the first eigenvalue and the second eigenvalue to obtain a maximum characteristic root of the second judgment matrix;

calculating a consistency index of the second judgment matrix by using the maximum feature root;

taking the ratio of the consistency index to an average random consistency index as the consistency ratio of the second judgment matrix; the average random consistency index is determined based on the total number of elements included in the second judgment matrix;

judging whether the value of the consistency ratio is smaller than a preset threshold value or not;

under the condition that the value of the consistency ratio is smaller than the preset threshold value, determining that the weight of each secondary index associated with the primary index passes consistency verification;

and scoring each secondary index associated with the primary index to obtain the evaluation score of each secondary index associated with the primary index.

Optionally, the method further includes:

and under the condition that the value of the consistency ratio is not less than the preset threshold value, recalculating the weight of each secondary index associated with the primary index in the index level to which the secondary index belongs.

Optionally, the secondary indicator includes a quantitative indicator and a qualitative indicator;

the scoring of each secondary index associated with the primary index to obtain the evaluation score of each secondary index associated with the primary index includes:

calculating the evaluation score of the quantitative index by using a calculation formula corresponding to the quantitative index aiming at each quantitative index associated with the primary index;

and aiming at each qualitative index associated with the primary index, calculating the evaluation score of the qualitative index by adopting an expert evaluation mode corresponding to the qualitative index.

Optionally, the obtaining the evaluation score of the primary indicator according to the evaluation score of each secondary indicator associated with the primary indicator includes:

and carrying out weighted summation on the evaluation score of each secondary index associated with the primary index to obtain the evaluation score of the primary index.

Optionally, when the weight of each primary index passes consistency verification, performing weighted summation on the evaluation score of each primary index to obtain an evaluation total score of the mobile terminal software, including:

for each first-level index, comparing the first-level index with other first-level indexes to obtain a first judgment matrix; the other first-level indexes and the first-level indexes belong to the same index level;

analyzing the first judgment matrix to obtain the column vector of the first-level index and the column vectors of the other first-level indexes;

carrying out weighted summation on the column vector of the first-level index and the column vectors of the other first-level indexes to obtain a weighted vector;

analyzing the weighting vector to obtain the weighting value of the first-level index and the weighting values of the other first-level indexes;

calculating the weighted value and the weighted ratio of the primary index aiming at the primary index to obtain a third characteristic value;

calculating the weighted value and the weighted ratio of the other first-level indexes aiming at the other first-level indexes to obtain a fourth characteristic value;

calculating an arithmetic mean value of the third eigenvalue and the fourth eigenvalue to obtain a maximum characteristic root of the first judgment matrix;

calculating a consistency index of the first judgment matrix by using the maximum feature root;

taking the ratio of the consistency index to the average random consistency index as the consistency ratio of the first judgment matrix; the average random consistency index is determined based on the total number of elements contained in the first judgment matrix;

under the condition that the value of the consistency ratio is smaller than the preset threshold value, determining that the weight of each primary index passes consistency verification;

and carrying out weighted summation on the evaluation score of each primary index to obtain the total evaluation score of the mobile terminal software.

A mobile terminal software evaluation device comprises:

the generating unit is used for generating an evaluation index set according to a preset index generating rule; the evaluation index set comprises a plurality of first-level indexes and each second-level index associated with each first-level index;

a building unit, configured to build a hierarchical architecture model based on each of the primary indexes and each of the secondary indexes associated with each of the primary indexes, where the hierarchical architecture model is used to indicate an index level to which each of the indexes in the evaluation index set belongs; each first-level index belongs to the same index level, and each second-level index associated with each first-level index belongs to the same index level;

the calculation unit is used for calculating the weight of each primary index in the index level to which the primary index belongs and the weight of each secondary index in the index level to which the secondary index belongs;

the scoring unit is used for scoring each secondary index associated with the primary index to obtain an evaluation score of each secondary index associated with the primary index when the weight of each secondary index associated with the primary index passes consistency verification, and obtaining the evaluation score of the primary index according to the evaluation score of each secondary index associated with the primary index;

and the evaluation unit is used for weighting and summing the evaluation scores of the primary indexes when the weight of each primary index passes consistency verification to obtain the total evaluation score of the mobile terminal software.

A computer-readable storage medium including a stored program, wherein the program executes the mobile-side software evaluation method.

A mobile-side software evaluation apparatus, comprising: a processor, a memory, and a bus; the processor and the memory are connected through the bus;

the memory is used for storing programs, and the processor is used for running the programs, wherein the programs execute the mobile terminal software evaluation method when running.

According to the technical scheme, an evaluation index set is generated according to a preset index generation rule; the evaluation index set comprises a plurality of primary indexes and each secondary index associated with each primary index. Constructing a hierarchical architecture model based on each primary index and each secondary index associated with each primary index, wherein the hierarchical architecture model is used for indicating the index level of each index in the evaluation index set; wherein, each first-level index belongs to the same index level, and each second-level index associated with each first-level index belongs to the same index level. And respectively calculating the weight of each primary index in the index level to which the primary index belongs and the weight of each secondary index in the index level to which the secondary index belongs. And for each primary index, when the weight of each secondary index associated with the primary index passes consistency verification, scoring each secondary index associated with the primary index to obtain the evaluation score of each secondary index associated with the primary index, and obtaining the evaluation score of the primary index according to the evaluation score of each secondary index associated with the primary index. And when the weight of each primary index passes consistency verification, carrying out weighted summation on the evaluation score of each primary index to obtain the total evaluation score of the mobile terminal software. The mobile terminal software is quantitatively evaluated, so that the problems existing in the current development process can be visually exposed to a software developer while the quality of a product is evaluated, and a benchmarking is expected to be made for the subsequent development process. Therefore, by using the scheme of the application, the evaluation result of the mobile terminal software can be effectively provided for the software developer, so that the developer can improve the quality of the mobile terminal software according to the evaluation result.

Drawings

In order to more clearly illustrate the embodiments of the present application 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, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1a is a schematic diagram of a method for evaluating mobile software according to an embodiment of the present disclosure;

FIG. 1b is a schematic diagram of an APP evaluation model tree provided in an embodiment of the present application;

fig. 2 is a schematic diagram of another method for evaluating mobile software according to an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of a mobile software evaluation apparatus according to an embodiment of the present disclosure.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, 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 application.

As shown in fig. 1a, a schematic diagram of a method for evaluating mobile terminal software provided in an embodiment of the present application includes the following steps:

s101: and generating an evaluation index set according to a preset index selection rule.

The evaluation index set comprises a plurality of first-level indexes and each second-level index associated with each first-level index.

Specifically, the preset index selection principle includes:

1. correlation: the selected index can really reflect the related attributes of the APP and the evaluation purpose which is finally needed to be achieved;

2. completeness: the selected indexes need to comprehensively and systematically reflect various characteristics of the APP in all dimensions;

3. layering: the selected index can clearly and correctly reflect the attribution relationship among all levels in the evaluation dimension, and finally a multi-level evaluation index tree is established according to the progressive relationship among the levels;

4. independence: the selected indexes need to be independent from each other and do not influence each other, so that various relations between the indexes are avoided, and the final evaluation result is prevented from being disordered;

5. easy to measure: the meaning expressed by the selected index should be clear and easy to understand, and the quantitative evaluation of the selected index should be easy.

Based on the index selection principle, the characteristics of the APP in the current mobile Internet environment are integrated, and the first-level index and the second-level index are screened out. In the embodiment of the present application, the primary index may be: "requirements & documentation", "interface interaction", "design & development", and "product".

Specifically, the secondary indicators associated with "requirements & documents" include, but are not limited to:

a1, integrity: namely, whether the required document is completely compiled or not is evaluated in APP development;

a2, normative: aiming at whether the compiling of the required document is evaluated according to the current standard rule and whether the content arrangement is unified or not in the APP development;

a3, rationality: the method comprises the steps of evaluating whether the compiling content of a required document and the provision of a business process in the document meet the rules or not in APP development;

a4, reusability: namely, evaluating whether the required content is easy to be repeatedly used or not in APP development;

a5, correctness: namely, whether the expression content of the requirement document is correct or not is evaluated in APP development;

a6, readability: namely, whether the expression of the requirement document has ambiguity or not and whether the expression content is clear or not are evaluated in APP development.

Specifically, the second-level indicators associated with the "interface interaction" include, but are not limited to:

b1, integrity: namely, whether the main content presentation in each interface is complete or not is evaluated in the APP interface interactive design;

b2, normative: namely, evaluating whether the APP interface meets the existing interactive design specifications in the interactive design;

b3, structural layout: in the interactive design of the APP interface, whether navigation structure layout, function entry and help guidance are obvious or not and whether logic between pages is clear or not are evaluated;

b4, artistic style: namely, whether the artistic design style is attractive or not in APP interface design is evaluated;

b5, consistency: namely, evaluating whether the theme colors, the font layout and the interaction modes of each interface are unified or not in the APP interface interaction design;

b6, reusability: namely, whether design content can be incorporated into an interactive design specification or not in the interactive design of the APP interface is convenient for repeated use to evaluate.

Specifically, the secondary indicators associated with "design & development" include, but are not limited to:

c1, integrity: namely, whether the writing of each code and the realized function are complete or not is evaluated in the APP development;

c2, normative: the method aims at whether the design of a database and various names in the database table, and the compiling of codes, comments and indents are standardized or not in APP development;

c3, correctness: namely, whether the compiling of each code is correct and the number of generated bugs are evaluated in the APP development;

c4, maintainability: namely, evaluating the understanding, correcting, changing and improving difficulty of each code in APP development;

c5, reusability: namely, whether each component and code are easy to be repeatedly used or not is evaluated in APP design and development;

c6, expansibility: that is, whether more functions are allowed in various designs of APP can be inserted into an appropriate position for evaluation if necessary;

c7, safety: in the design and development of APP, whether APP information can be modified and the possibility of information illegal leakage can be evaluated only under the authorization of a specific authorized user;

c8, innovativeness: namely, whether the implementation modes of code writing and functions are innovative in APP design and development is evaluated.

Specifically, the secondary indicators associated with the "product" include, but are not limited to:

d1, integrity: whether the finally realized function is complete or not in the product on-line of the APP is evaluated;

d2, consistency: whether the contents such as theme colors, text layout, navigation setting, interaction modes and the like in the final online product of the APP are uniformly evaluated;

d3, ease of use: whether operation guidance and feedback are clear or not and whether the APP is easy to use or not are evaluated in a product on which the APP is finally put on line;

d4, reliability: whether the appointed specific function can be executed without failure in a product on which the APP is finally on line is evaluated within a certain time and under certain conditions;

d5, efficiency: namely, the efficiency of response speed and performance finally realized in the product on line of APP is evaluated.

It should be noted that the above specific implementation process is only for illustration.

S102: and constructing a hierarchical architecture model based on each primary index and each secondary index associated with each primary index.

The hierarchical structure model is used for indicating the index level to which each index belongs in the evaluation index set, each first-level index belongs to the same index level, and each second-level index associated with each first-level index belongs to the same index level.

It should be noted that, the specific structure of the hierarchical model, including but not limited to the tree model, can be referred to the APP evaluation model tree shown in fig. 1 b.

S103: and aiming at each first-level index, comparing the first-level index with other first-level indexes to obtain a first judgment matrix.

Wherein, other first-level indexes and first-level index belong to same index level, and first judgement matrix includes a plurality of elements, and every element all characterizes: the comparison result of the first-level index with other first-level indexes. And (4) characterization of a comparison result: the importance of the primary index compared to other primary indices.

The comparison result of the first-level index and other first-level indexes can be obtained by calculating by adopting a 'ninth method' in an analytic hierarchy process. Specifically, the evaluation manner of "ninth method" is shown in table 1.

TABLE 1

In Table 1 above, element i represents the primary index, element j represents the other primary index, and a_ijRepresenting elements of the first decision matrix.

Specifically, in order to facilitate visual understanding of each comparison result, the first determination matrix is abstracted to table 2.

TABLE 2

	Demand for&Document	Interface interaction	Design of&Development of	Product(s)
					Demand for&Document	1	2	1/5	1/7
Interface interaction	1/2	1	1/7	1/7
					Design of&Development of	5	7	1	1/3
Product(s)	7	7	3	1

It should be noted that the contents shown in table 2 are only for illustration.

S104: and calculating the quotient of each element in the first judgment matrix and the first numerical value to obtain a first standard judgment matrix.

Wherein the first value is the cumulative sum of each element in the column in which the element is located.

Specifically, taking the content shown in table 2 as an example, for each element in the first determination matrix corresponding to table 2, a quotient between the element and the first numerical value is calculated to obtain a first standard determination matrix, and the first standard determination matrix is abstracted as shown in table 3.

TABLE 3

It should be noted that the contents shown in table 3 are only for illustration.

S105: and calculating the arithmetic mean value of each element contained in each row in the first standard judgment matrix to obtain the weight of the first-level index and the weight of other first-level indexes.

The calculation process of the arithmetic mean of each element included in each row is common knowledge familiar to those skilled in the art, and is not described herein again.

Specifically, taking the contents shown in table 3 as an example, the arithmetic mean of each element included in each row in the first criterion decision matrix corresponding to table 3 is calculated to obtain the weight of the first-level indicator and the weights of the other first-level indicators, as shown in table 4.

TABLE 4

	Demand for&Document	Interface interaction	Design of&Development of	Product(s)	Weight of
						Demand for&Document	0.0741	0.1176	0.0641	0.0882	0.0815
Interface interaction	0.0370	0.0588	0.0329	0.0882	0.0542
						Design of&Development of	0.3704	0.4118	0.2303	0.2059	0.3046
Product(s)	0.5185	0.4118	0.6908	0.6176	0.5597

It should be noted that the contents shown in table 4 are only for illustration.

S106: and aiming at each secondary index, comparing the secondary index with other secondary indexes to obtain a second judgment matrix.

Wherein, other second grade index and second grade index belong to same index level, and the second decision matrix includes a plurality of elements, and every element all characterizes: and comparing the secondary indexes with other secondary indexes. And (4) characterization of a comparison result: the importance of the secondary index compared to other secondary indexes.

It should be noted that the specific implementation process and implementation principle of S106 are consistent with the specific implementation process and implementation principle of S103, and are not described herein again.

S107: and calculating the quotient of the element and the second numerical value aiming at each element in the second judgment matrix to obtain a second standard judgment matrix.

Wherein the second value is: the cumulative sum of all elements in the column in which the element is located.

It should be noted that the specific implementation process and implementation principle of S107 are consistent with the specific implementation process and implementation principle of S104, and are not described herein again.

S108: and calculating the arithmetic mean value of each element contained in each row in the second standard judgment matrix to obtain the weight of the second-level index and the weight of other second-level indexes.

It should be noted that the specific implementation process and implementation principle of S108 are consistent with the specific implementation process and implementation principle of S105, and are not described herein again.

S109: and carrying out consistency verification on the weight of each primary index.

The specific process of performing consistency verification on the weight of each primary index comprises the following steps:

1. and analyzing the first judgment matrix to obtain the column vector of the first-level index and the column vectors of other first-level indexes.

Wherein elements in the column vector characterize: the comparison result of other first-level indexes and the first-level index.

Specifically, taking the contents shown in table 2 as an example, the judgment matrix corresponding to table 2 is analyzed to obtain "demand&The column vector of the document is

The column vector of "interface interaction" is

' design&Column vectors of "are developed as

The column vector of "product" is

2. And carrying out weighted summation on the column vector of the first-level index and the column vectors of other first-level indexes to obtain a weighted vector.

The specific implementation of the weighted summation is well known to those skilled in the art.

Specifically, taking the contents shown in table 2 and table 4 as an example, the column vectors of the first-level indexes are weighted and summed, and the specific calculation process is shown in formula (1).

3. And analyzing the weighting vector to obtain the weighted value of the first-level index and the weighted value of other first-level indexes.

Specifically, taking the weighting vector shown in formula (1) as an example, the weighting vector is analyzed to obtain a weighting value of 0.3309 for "demand & document", a weighting value of 0.2185 for "interface interaction", a weighting value of 1.2784 for "design & development", and a weighting value of 2.4236 for "product".

4. And calculating the weighted value and the weighted ratio of the primary index aiming at the primary index to obtain a third characteristic value.

5. And calculating the weighted value and the weighted ratio of the other first-level indexes aiming at the other first-level indexes to obtain a fourth characteristic value.

6. And calculating the arithmetic mean value of the third eigenvalue and the fourth eigenvalue to obtain the maximum characteristic root of the first judgment matrix.

The specific calculation method of the arithmetic mean value is common knowledge familiar to those skilled in the art.

Specifically, taking the contents shown in the above formula (1), table 2, and table 4 as examples, the specific calculation process is shown in formula (2).

In the formula (2), λ_maxRepresenting the largest feature root of the first decision matrix.

7. And calculating the consistency index of the first judgment matrix by using the maximum characteristic root.

The specific process of calculating the consistency index of the first judgment matrix by using the maximum feature root is shown in formula (3).

In formula (3), CI represents a consistency index, n represents a matrix order of the first determination matrix, and the matrix order represents a total number of elements included in the first determination matrix.

Specifically, taking the maximum feature root shown in the above formula (2) as an example, the consistency index of the first determination matrix is calculated by using the maximum feature root, and the calculation result is shown in formula (4).

8. And taking the ratio of the consistency index to the average random consistency index as the consistency ratio of the first judgment matrix.

The value of the average random consistency index may be determined by the total number of elements included in the first determination matrix (which may also be understood as a matrix order), and specifically, a corresponding relationship between the value of the average random consistency index and the matrix order of the first determination matrix is shown in table 5 below.

TABLE 5

n	1	2	3	4	5	6	7	8	9
										RI	0	0	0.58	0.9	1.12	1.24	1.32	1.41	1.45

In table 5, n represents the matrix order of the first decision matrix, and RI represents the average random consistency index.

Specifically, the calculation procedure of the consistency ratio of the first determination matrix is as shown in equation (5) by taking the contents shown in equation (4) and table 5 as examples.

9. And if the value of the consistency ratio of the first judgment matrix is smaller than a preset threshold value, determining that the weight of each primary index passes consistency verification.

10. If the value of the consistency ratio of the first judgment matrix is not less than the preset threshold, determining that the weight of each first-level index does not pass consistency verification, and recalculating the weight of each first-level index in the index level to which the first-level index belongs to ensure the reasonability of weight distribution of each first-level index.

S110: and carrying out consistency verification on the weight of each secondary index associated with the primary index.

The specific process of carrying out consistency verification on the weight of each secondary index associated with the primary index comprises the following steps:

1. and analyzing the second judgment matrix to obtain the column vector of the second-level index and the column vectors of other second-level indexes.

2. And carrying out weighted summation on the column vectors of the second-level indexes and the column vectors of other second-level indexes to obtain weighted vectors.

3. And analyzing the weighted vector to obtain the weighted value of the secondary index and the weighted values of other secondary indexes.

4. And calculating the weighted value and the weighted ratio of the secondary indexes according to the secondary indexes to obtain a first characteristic value.

5. And calculating the weighted value and the ratio of the weighted values of other secondary indexes aiming at other secondary indexes to obtain a second characteristic value.

6. And calculating the arithmetic mean value of the first characteristic value and the second characteristic value to obtain the maximum characteristic root of the second judgment matrix.

7. And calculating the consistency index of the second judgment matrix by using the maximum characteristic root.

8. And taking the ratio of the consistency index to the average random consistency index as the consistency ratio of the second judgment matrix.

Wherein the average random consistency index is determined based on the total number of elements included in the second judgment matrix

9. And if the value of the consistency ratio of the second judgment matrix is smaller than the preset threshold value, determining that the weight of each secondary index associated with the primary index passes consistency verification.

10. If the value of the consistency ratio of the second judgment matrix is not less than the preset threshold, determining that the weight of each secondary index associated with the primary index does not pass consistency verification, and recalculating the weight of each secondary index associated with the primary index in the index level to which the secondary index belongs to ensure the reasonability of weight distribution of each secondary index associated with the primary index.

It should be noted that the implementation principle of performing consistency verification on the weights of the secondary indexes associated with the primary indexes is the same as the implementation principle of performing consistency verification on the weights of the primary indexes, and reference may be made to the implementation principle.

S111: and for each primary index, when the weight of each secondary index associated with the primary index passes consistency verification, scoring each secondary index associated with the primary index to obtain the evaluation score of each secondary index associated with the primary index.

Wherein, the secondary indexes comprise quantitative indexes and qualitative indexes.

Optionally, for each quantitative index associated with the primary index, calculating an evaluation score of the quantitative index by using a calculation formula corresponding to the quantitative index; and aiming at each qualitative index associated with the primary index, calculating the evaluation score of the qualitative index by adopting an expert evaluation mode corresponding to the qualitative index.

And (4) scoring the quantitative index, and calculating to obtain the numerical value of the quantitative index through a specific calculation formula. Taking the quantitative index "correctness" included in "design & development" as an example, in the final test document of APP, 107 defects are found, as shown in table 6, 2 urgent defects, 25 high-level defects, 80 medium-level defects, and 0 low-level defects. In addition, as shown in table 6, the weight corresponding to the urgent defect is set to 0.5, the weight corresponding to the high-level defect is set to 0.3, the weight corresponding to the medium-level defect is set to 0.1, and the weight corresponding to the low-level defect is set to 0.05. And (4) as shown in the formula (6), carrying out weighted summation on the number of each type of defects to obtain the evaluation score of the quantitative index 'correctness'.

TABLE 6

Type of defect	Number of	Weight value
			Emergency system	2	0.5
Advanced	25	0.3
			Middle stage	80	0.1
Low grade	0	0.05

2×0.5+25×0.3+80×0.1+0×0.05＝83.5≈85 (6)

The qualitative index is scored by adopting an expert judgment mode, namely, the qualitative index is divided into a plurality of grades, each grade is scored by a specific numerical value, and the specific expert judgment mode is shown in table 7.

TABLE 7

Note that the contents shown in table 7 are for illustration only.

S112: and carrying out weighted summation on the evaluation scores of each secondary index associated with the primary indexes to obtain the evaluation score of the primary index.

The weight of each secondary index associated with the primary index is calculated through the above steps, and a specific implementation manner of the weighted summation is common knowledge familiar to those skilled in the art, and is not described herein again.

S113: and when the weight of each primary index passes consistency verification, carrying out weighted summation on the evaluation score of each primary index to obtain the total evaluation score of the mobile terminal software.

The weight of each primary index is calculated through the above steps, and the specific implementation manner of weighted summation is common knowledge familiar to those skilled in the art, and is not described herein again.

Specifically, the mobile terminal software was evaluated, and the evaluation results are shown in table 8.

TABLE 8

Note that the weighted score mentioned in table 8 above, i.e., the product of the evaluation score and the weight. In addition, the total evaluation scores shown in table 8 belong to good ratings in practical applications, meet the expectations of software developers for the mobile software, and through the evaluation scores of each evaluation index, it can be found that the mobile software has a few problems in the two aspects of "expansibility at the" design & development "stage and" efficiency of the "product", so that a reference idea is provided for subsequently perfecting the mobile software and developing new mobile software.

In conclusion, the mobile terminal software is quantitatively evaluated, so that the problems existing in the current development process can be intuitively exposed to a software developer while the quality of a product is evaluated, and a benchmarking is expected to be made for the subsequent development process. Therefore, by using the scheme of the application, the evaluation result of the mobile terminal software can be effectively provided for the software developer, so that the developer can improve the quality of the mobile terminal software according to the evaluation result.

It should be noted that, in the above embodiment, the step S103 is an optional implementation manner of the mobile terminal software evaluation method described in this application. In addition, S104 mentioned in the above embodiment is also an optional implementation manner of the mobile terminal software evaluation method described in this application. For this reason, the flow mentioned in the above embodiment can be summarized as the method shown in fig. 2.

As shown in fig. 2, a schematic diagram of a method for evaluating mobile terminal software provided in an embodiment of the present application includes the following steps:

s201: and generating an evaluation index set according to a preset index generation rule.

S202: and constructing a hierarchical architecture model based on each primary index and each secondary index associated with each primary index.

The hierarchical structure model is used for indicating the index level of each index in the evaluation index set; wherein, each first-level index belongs to the same index level, and each second-level index associated with each first-level index belongs to the same index level.

S203: and respectively calculating the weight of each primary index in the index level to which the primary index belongs and the weight of each secondary index in the index level to which the secondary index belongs.

S204: and for each primary index, when the weight of each secondary index associated with the primary index passes consistency verification, scoring each secondary index associated with the primary index to obtain the evaluation score of each secondary index associated with the primary index, and obtaining the evaluation score of the primary index according to the evaluation score of each secondary index associated with the primary index.

S205: and when the weight of each primary index passes consistency verification, carrying out weighted summation on the evaluation score of each primary index to obtain the total evaluation score of the mobile terminal software.

Corresponding to the mobile terminal software evaluation method provided by the embodiment of the application, the embodiment of the application also provides a mobile terminal software evaluation device.

As shown in fig. 3, a schematic architecture diagram of a mobile software evaluation apparatus provided in an embodiment of the present application includes:

a generating unit 100, configured to generate an evaluation index set according to a preset index generation rule; the evaluation index set comprises a plurality of primary indexes and each secondary index associated with each primary index.

A constructing unit 200, configured to construct a hierarchical architecture model based on each primary index and each secondary index associated with each primary index, where the hierarchical architecture model is used to indicate an index level to which each index in the evaluation index set belongs; wherein, each first-level index belongs to the same index level, and each second-level index associated with each first-level index belongs to the same index level.

A calculating unit 300, configured to calculate a weight of each primary indicator in an indicator level to which the primary indicator belongs, and a weight of each secondary indicator in an indicator level to which the secondary indicator belongs, respectively.

Wherein, the calculating unit 300 is specifically configured to: aiming at each first-level index, comparing the first-level index with other first-level indexes to obtain a first judgment matrix; other first-level indexes and the first-level indexes belong to the same index level; calculating a quotient value of each element in the first judgment matrix and the first numerical value to obtain a first standard judgment matrix; the first value is: the cumulative sum of all elements in the column in which the element is located; calculating the arithmetic mean value of each element contained in each row in the first standard judgment matrix to obtain the weight of the first-level index and the weight of other first-level indexes; aiming at each secondary index, comparing the secondary index with other secondary indexes to obtain a second judgment matrix; other secondary indexes and the secondary indexes belong to the same index level; calculating a quotient value of each element in the second judgment matrix and the second numerical value to obtain a second standard judgment matrix; the second value is: the cumulative sum of all elements in the column in which the element is located; and calculating the arithmetic mean value of each element contained in each row in the second standard judgment matrix to obtain the weight of the second-level index and the weight of other second-level indexes.

The scoring unit 400 is configured to, for each primary index, score each secondary index associated with the primary index when the weight of each secondary index associated with the primary index passes consistency verification, obtain an evaluation score of each secondary index associated with the primary index, and obtain an evaluation score of the primary index according to the evaluation score of each secondary index associated with the primary index.

Wherein, the scoring unit 400 is specifically configured to: for each secondary index associated with the primary index, comparing the secondary index with other secondary indexes to obtain a second judgment matrix; other secondary indexes and the secondary indexes belong to the same index level; analyzing the second judgment matrix to obtain a column vector of the second-level index and column vectors of other second-level indexes; carrying out weighted summation on the column vectors of the second-level indexes and the column vectors of other second-level indexes to obtain weighted vectors; analyzing the weighted vector to obtain the weighted value of the second-level index and the weighted values of other second-level indexes; aiming at the secondary indexes, calculating the weighted value and the weighted ratio of the secondary indexes to obtain a first characteristic value; aiming at other secondary indexes, calculating weighted values of the other secondary indexes and a ratio of the weighted values to obtain a second characteristic value; calculating an arithmetic mean value of the first characteristic value and the second characteristic value to obtain a maximum characteristic root of the second judgment matrix; calculating a consistency index of the second judgment matrix by using the maximum characteristic root; taking the ratio of the consistency index to the average random consistency index as the consistency ratio of the second judgment matrix; the average random consistency index is determined based on the total number of elements contained in the second judgment matrix; judging whether the value of the consistency ratio is smaller than a preset threshold value or not; under the condition that the value of the consistency ratio is smaller than a preset threshold value, determining that the weight of each secondary index associated with the primary index passes consistency verification; scoring each secondary index associated with the primary index to obtain an evaluation score of each secondary index associated with the primary index; and under the condition that the value of the consistency ratio is not less than the preset threshold value, recalculating the weight of each secondary index associated with the primary index in the index level to which the secondary index belongs.

In addition, the secondary indexes include a quantitative index and a qualitative index, and the scoring unit 400 is configured to score each secondary index associated with the primary index to obtain an evaluation score of each secondary index associated with the primary index, and includes: calculating the evaluation score of the quantitative index by using a calculation formula corresponding to the quantitative index aiming at each quantitative index associated with the primary index; and aiming at each qualitative index associated with the primary index, calculating the evaluation score of the qualitative index by adopting an expert evaluation mode corresponding to the qualitative index.

The scoring unit 400 is configured to obtain an evaluation score of the primary index according to the evaluation score of each secondary index associated with the primary index, and includes:

and carrying out weighted summation on the evaluation scores of each secondary index associated with the primary indexes to obtain the evaluation score of the primary index.

And the evaluation unit 500 is configured to perform weighted summation on the evaluation score of each primary index when the weight of each primary index passes consistency verification, so as to obtain an evaluation total score of the mobile terminal software.

Wherein, the evaluation unit 500 is specifically configured to: for each first-level index, comparing the first-level index with other first-level indexes to obtain a first judgment matrix; other first-level indexes and the first-level indexes belong to the same index level; analyzing the first judgment matrix to obtain a column vector of the first-level index and column vectors of other first-level indexes; carrying out weighted summation on the column vectors of the first-level indexes and the column vectors of other first-level indexes to obtain weighted vectors; analyzing the weighting vector to obtain a weighted value of the first-level index and weighted values of other first-level indexes; calculating the weighted value and the weighted ratio of the primary index aiming at the primary index to obtain a third characteristic value; aiming at other first-level indexes, calculating weighted values and weighted ratios of the other first-level indexes to obtain a fourth characteristic value; calculating an arithmetic mean value of the third eigenvalue and the fourth eigenvalue to obtain a maximum characteristic root of the first judgment matrix; calculating a consistency index of the first judgment matrix by using the maximum characteristic root; taking the ratio of the consistency index to the average random consistency index as the consistency ratio of the first judgment matrix; the average random consistency index is determined based on the total number of elements contained in the first judgment matrix; judging whether the value of the consistency ratio is smaller than a preset threshold value or not; under the condition that the value of the consistency ratio is smaller than a preset threshold value, determining that the weight of each primary index passes consistency verification; and carrying out weighted summation on the evaluation score of each primary index to obtain the total evaluation score of the mobile terminal software.

In conclusion, the mobile terminal software is quantitatively evaluated, so that the problems existing in the current development process can be intuitively exposed to a software developer while the quality of a product is evaluated, and a benchmarking is expected to be made for the subsequent development process. Therefore, by the scheme, the evaluation result of the mobile terminal software can be effectively provided for the software developer, so that the developer can improve the quality of the mobile terminal software according to the evaluation result.

The application also provides a computer-readable storage medium, which includes a stored program, wherein the program executes the mobile terminal software evaluation method provided by the application.

The application also provides a mobile terminal software evaluation device, which comprises: a processor, a memory, and a bus. The processor is connected with the memory through a bus, the memory is used for storing programs, and the processor is used for running the programs, wherein the programs execute the mobile terminal software evaluation method provided by the application when running.

The functions described in the method of the embodiment of the present application, if implemented in the form of software functional units and sold or used as independent products, may be stored in a storage medium readable by a computing device. Based on such understanding, part of the contribution to the prior art of the embodiments of the present application or part of the technical solution may be embodied in the form of a software product stored in a storage medium and including several instructions for causing a computing device (which may be a personal computer, a server, a mobile computing device or a network device) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A mobile terminal software evaluation method is characterized by comprising the following steps:

2. The method according to claim 1, wherein said calculating the weight of each primary index in the index hierarchy to which the primary index belongs and the weight of each secondary index in the index hierarchy to which the secondary index belongs respectively comprises:

3. The method according to claim 1, wherein for each primary index, when the weight of each secondary index associated with the primary index passes consistency verification, scoring each secondary index associated with the primary index to obtain an evaluation score of each secondary index associated with the primary index, comprises:

4. The method of claim 3, further comprising:

5. The method of claim 1, wherein the secondary indicators comprise a quantitative indicator and a qualitative indicator;

6. The method of claim 1, wherein obtaining the evaluation score of the primary index according to the evaluation score of each secondary index associated with the primary index comprises:

7. The method according to claim 1, wherein when the weight of each primary index passes consistency verification, performing weighted summation on the evaluation score of each primary index to obtain an evaluation total score of the mobile terminal software, comprises:

8. A mobile terminal software evaluation device is characterized by comprising:

9. A computer-readable storage medium, characterized in that the computer-readable storage medium includes a stored program, wherein the program executes the mobile terminal software evaluation method according to any one of claims 1 to 7.

10. A mobile terminal software evaluation device is characterized by comprising: a processor, a memory, and a bus; the processor and the memory are connected through the bus;

the memory is used for storing a program, and the processor is used for executing the program, wherein the program executes the mobile terminal software evaluation method according to any one of claims 1 to 7 when running.