WO2023179578A1

WO2023179578A1 - Code metric method and apparatus, device, and medium

Info

Publication number: WO2023179578A1
Application number: PCT/CN2023/082650
Authority: WO
Inventors: 刘勇; 严春霞
Original assignee: 中兴通讯股份有限公司
Priority date: 2022-03-21
Filing date: 2023-03-21
Publication date: 2023-09-28
Also published as: CN116820912A

Abstract

The present invention provides a code metric method. The method comprises: obtaining metric indexes of a software code to be subjected to metrics, the metric indexes comprising metric indexes of at least two characteristic dimensions; respectively calculating scores of the characteristic dimensions according to first weights of the metric indexes in the characteristic dimensions and score values of the characteristic dimensions; and calculating a metric score according to the scores of the characteristic dimensions and second weights of the characteristic dimensions, the metric score being used for performing metric of the quality of said software code. According to embodiments of the present invention, architecture quality of a code level is quantified from multiple characteristic dimensions, the scores of the characteristic dimensions and the overall metric score of the code quality can be generated, the metric score can visually reflect the quality level and the decay degree of a current software architecture, and automatic identification is achieved on the software code quality, thereby facilitating related personnel knowing a development trend of a code architecture quality condition to control the quality of the code. The present invention further provides a code metric apparatus, a computer device, and a readable medium. FIG. 2

Description

Code measurement methods, devices, equipment and media

Relevant public cross-references

This disclosure requires the priority of a Chinese patent application filed with the State Intellectual Property Office on March 21, 2022, with the publication number CN202210276975.1 and the invention name "Code Measurement Method, Device, Equipment and Medium". The entire content of the application incorporated by reference into this disclosure.

Technical field

The present disclosure relates to but is not limited to the field of computer technology, and specifically relates to a code measurement method, device, computer equipment and readable medium.

Background technique

The code architecture of software projects is extremely susceptible to corruption. Especially for large projects, without strict control mechanisms, the code structure will become chaotic. At this time, the complexity and maintenance difficulty of the system will skyrocket. To prevent this from happening, maintenance work based on architecture assessment needs to be added to the software life cycle. Therefore, a quantifiable code-level measurement method that can measure the overall code in multiple dimensions is needed.

Currently, there are many and complex tools for software code measurement. Most code measurement tools focus on measuring a certain aspect of the software, and cannot generate a quantifiable code-level overall architecture measurement result for the software.

Contents of the invention

The present disclosure provides a code measurement method, device, computer equipment and readable medium.

In a first aspect, an embodiment of the present disclosure provides a code measurement method. The method includes: obtaining a measurement index of a software code to be measured, where the measurement index includes measurement indicators of at least two characteristic dimensions; and according to the measurement index, The first weight in the characteristic dimension and the characteristic dimension The score of each characteristic dimension is calculated respectively; the measurement score is calculated according to the score of the characteristic dimension and the second weight of the characteristic dimension, and the measurement score is used to measure the software code to be measured. quality.

On the other hand, embodiments of the present disclosure also provide a code measurement device, including a metric index extraction module, a feature dimension score calculation module and a metric score calculation module. The metric index extraction module is configured to obtain the software code to be measured. Measurement indicators, the measurement indicators include measurement indicators of at least two characteristic dimensions; the characteristic dimension score calculation module is configured to, according to the first weight of the measurement indicator in the characteristic dimension and the score of each characteristic dimension , calculate the scores of the characteristic dimensions respectively; the metric score calculation module is configured to calculate the metric score according to the score of the characteristic dimension and the second weight of the characteristic dimension, and the metric score is used to measure the to-be- Measuring the quality of software code.

In another aspect, an embodiment of the present disclosure also provides a computer device, including: at least one processor; a storage device on which at least one program is stored; when the at least one program is executed by the at least one processor, such that The at least one processor implements the code measurement method as described above.

In another aspect, embodiments of the present disclosure also provide a computer-readable medium on which a computer program is stored, wherein when the program is executed, the code measurement method as described above is implemented.

Description of the drawings

Figure 1 is a schematic diagram of the system framework provided by an embodiment of the present disclosure;

Figure 2 is a schematic flowchart of a code measurement method provided by an embodiment of the present disclosure;

Figure 3 is a schematic flowchart of calculating functional scores provided by an embodiment of the present disclosure;

Figure 4 is a schematic flowchart of calculating maintainability scores provided by an embodiment of the present disclosure;

Figure 5 is a schematic flowchart of calculating scalability scores provided by an embodiment of the present disclosure;

Figure 6 is a schematic structural diagram of a code measurement device provided by an embodiment of the present disclosure.

Detailed ways

Example embodiments will be described more fully below with reference to the accompanying drawings, which may, however, be embodied in different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully understand the scope of the disclosure to those skilled in the art.

As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

The terminology used herein is used to describe particular embodiments only and is not intended to limit the disclosure. As used herein, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that when the terms "comprising" and/or "made of" are used in this specification, the presence of stated features, integers, steps, operations, elements and/or components is specified but does not exclude the presence or Add one or more other features, entities, steps, operations, elements, components, and/or groups thereof.

Embodiments described herein may be described with reference to plan and/or cross-sectional illustrations, with the aid of idealized schematic illustrations of the present disclosure. Accordingly, example illustrations may be modified based on manufacturing techniques and/or tolerances. Therefore, the embodiments are not limited to those shown in the drawings but include modifications of configurations formed based on the manufacturing process. Accordingly, the regions illustrated in the figures are of a schematic nature and the shapes of the regions shown in the figures are illustrative of the specific shapes of regions of the element and are not intended to be limiting.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be construed to have meanings consistent with their meanings in the context of the relevant art and the present disclosure, and will not be construed as having idealized or excessive formal meanings, Unless expressly so limited herein.

In order to achieve quantitative and multi-dimensional overall measurement of software code, embodiments of the present disclosure provide a code measurement solution. As shown in Figure 1, the embodiment of the present disclosure is based on the eight characteristics defined in the software quality model ISO25010, using the measurement tool set to extract the measurement indicators of each characteristic dimension, and based on the customized measurement algorithm formula, the absolute score is calculated based on the weight as Measure results. Among them, the weight can be configured or modified according to actual usage.

As shown in Figure 2, the code measurement method provided by the embodiment of the present disclosure includes the following steps:

Step 21: Obtain the measurement indicators of the software code to be measured. The measurement indicators include measurement indicators of at least two characteristic dimensions.

In this step, multiple feature dimensions and measurement indicators of each feature dimension may be determined based on the software quality model ISO25010, and each feature dimension includes at least one measurement indicator.

In some embodiments, feature dimensions may include any combination of the following: functionality, security, maintainability, scalability, efficiency, ease of use, reliability, and portability. It should be noted that portability can be reflected in scalability.

Step 22: Calculate the scores of the characteristic dimensions respectively based on the first weight of the measurement index in each of the characteristic dimensions and the score of the characteristic dimension.

Configure the second weight for each feature dimension in advance, and configure the first weight for each metric index within the feature dimension for each feature dimension. In this step, calculate each metric index based on the score of each feature dimension. score, and for each feature dimension, calculate the weighted sum of the score of each metric index and the first weight of each metric index to obtain the score of the corresponding feature dimension.

Step 23: Calculate a measurement score based on the score of the characteristic dimension and the second weight of the characteristic dimension. The measurement score is used to measure the quality of the software code to be measured.

In this step, the weighted sum of the scores of each feature dimension and the corresponding first weight is calculated to obtain the overall measurement score of the software code to be measured. The measurement score can reflect the quality of the software code to be measured. The higher the measurement score, the The higher the quality of the software code to be measured, and vice versa.

A code measurement method provided by an embodiment of the present disclosure, the method includes: obtaining measurement indicators of the software code to be measured, the measurement indicators include measurement indicators of at least two characteristic dimensions; according to the first of the measurement indicators in each characteristic dimension The weight and the score of the characteristic dimension are used to calculate the score of the characteristic dimension respectively; the measurement score is calculated according to the score of the characteristic dimension and the second weight of the characteristic dimension, and the measurement score is used to measure the software code to be measured. quality. The embodiments of the present disclosure can quantify code-level architecture quality from multiple feature dimensions, and can generate scores for each feature dimension and an overall metric score of code quality. The level of the metric score can intuitively reflect the quality level and quality of the current software architecture. Corruption degree, automatic identification of software code quality, This allows relevant personnel to understand the development trend of code architecture quality and control the quality of the code; improvements based on measurement results can also be quickly fed back. Through this continuous closed-loop improvement, the software quality level can ultimately be improved and the architecture can be effectively prevented from deteriorating. corrupt.

In the embodiment of the present disclosure, functionality (Functionality), security (Security), maintainability (Maintainability) and scalability (Scalability) are taken as examples for description. Functional metrics include one or any combination of the following: coverage, vulnerability level, first vulnerability impact level. The first vulnerability impact level is the impact level of quality and variety (quality+various) vulnerabilities; vulnerability levels can include the following Four types: critical (serious), error (error), warn (warning), review (code review); security metrics include the second vulnerability impact level, and the second vulnerability impact level is security and diversity (security+ The impact level of various) vulnerabilities; maintainability metrics include complexity; scalability metrics include duplication. The first vulnerability impact level and the second vulnerability impact level can include high, medium, and low respectively.

The measurement indicators, weights, scores of the characteristic dimensions and the tools for obtaining the measurement indicators of each feature dimension are shown in Table 1:

Table 1

It should be noted that the tools for obtaining each metric in Table 1 are only illustrative. For example, complexity can also be obtained through the code cyclomatic complexity scanning tool lizard.

In some embodiments, as shown in Figure 3, the step of calculating the functional score (Functionality_Score) includes:

Step 31: Calculate the scores of functional metrics.

In this step, the coverage score, the vulnerability level score, and the first vulnerability impact level score are calculated respectively.

In some embodiments, coverage is scored based on branch coverage (branch_Coverag) And the functional score is calculated, the calculation formula is: (branch_Coverage*100)3/functional score. Referring to Table 1, the functionality score can be 1000.

The vulnerability level score is calculated based on the number of vulnerabilities at each vulnerability level, the third weight of each vulnerability level, the first constant, the functionality score and the total number of lines of software code. The calculation formula is:
Vulnerability level score =
functional score
-(critical_num*P31+error_num*P32+warning_num*P33+review_num*P34)
*C1*Functional score/code_lines;

Among them, critical_num is the number of critical-level vulnerabilities, error_num is the number of error-level vulnerabilities, warning_num is the number of warning-level vulnerabilities, review_num is the number of review-level vulnerabilities, and P31, P32, P33, and P34 are the third of the four vulnerability levels respectively. For the weight, code_lines is the total number of lines of software code, and C1 is the first constant. For example, C1 can be 20.

The score of the first vulnerability impact level is calculated based on the number of vulnerabilities of each first vulnerability impact level, the fourth weight of each first vulnerability impact level, the functional score, the second constant and the total number of lines of software code. The calculation formula is: :
The first vulnerability impact level score =
functional score
-(quality['high_level_num']*P41+quality['medium_level_num']*P42+
quality['low_level_num']*P43)*C2*Functional score/code_lines;

Among them, quality['high_level_num'] is the number of vulnerabilities with the impact level of high for the first vulnerability type of quality\various vulnerability type, quality['medium_level_num'] is the number of vulnerabilities with the impact level of medium for the first vulnerability type of quality\various vulnerability type. quality['low_level_num'] is the number of vulnerabilities with low impact level for the first vulnerability type of quality\various vulnerability type; P41, P42, and P43 are the fourth weights of the three first vulnerability impact levels respectively, and code_lines is the total number of lines of software code , C2 is the second constant, for example, C2 can be 100.

Step 32: Calculate the weighted sum of the score of the metric index of functionality and the first weight of the metric index of functionality in functionality to obtain a score of functionality.

The calculation formula of functional score (Functionality_Score) is: functional score = coverage score * P11 + vulnerability level score * P12 + first vulnerability impact level score * P13; among them, P11, P12, and P13 are coverage rates respectively. The first weight in functionality, the first weight of vulnerability level in functionality, the first weight of vulnerability impact level in functionality.

In some embodiments, the step of calculating the security score (Security_Score) includes: the number of vulnerabilities according to each second vulnerability impact level, the fifth weight of each second vulnerability impact level, the security score, a third constant, and The total number of lines of software code is used to calculate the security score (Security_Score). The calculation formula of the security score (Security_Score) is:
Safety rating =
security score
-(security['high_level_num']*P51+security['medium_level_num']*P52
+security['low_level_num']*P53)C3*security score/code_lines;

Among them, security['high_level_num'] is the number of vulnerabilities with the impact level of the second vulnerability of the security\various vulnerability type being high, security['medium_level_num'] is the number of vulnerabilities with the impact level of the second vulnerability of the security\various vulnerability type that is medium, security['low_level_num'] is the number of vulnerabilities with low impact level of the second vulnerability type of security\various vulnerability type; P51, P52, and P53 are the fifth weights of the three secondary vulnerability impact levels respectively, and code_lines is the total number of lines of software code ;C3 is the third constant. For example, C3 can be 625.

Since the security dimension has only one metric (i.e., the second vulnerability impact level), the first weight P21 of the second vulnerability impact level in security is 1.

In some embodiments, as shown in Figure 4, the step of calculating the maintainability score (Maintainability_Score) includes:

Step 41: Obtain complexity parameters, which include one or any combination of the following parameters: cyclomatic complexity, code depth, and number of method statements.

Step 42: Calculate a complexity parameter score based on the complexity parameter, the sixth weight of the complexity parameter, the maintainability score, and the fourth constant.

In this step, you can obtain relevant fields directly from SourceMonitor-summary.xml. The obtained fields are shown in Table 2:

Table 2

The average cyclomatic complexity (average_complexity) and average code depth (average_block_depth) can be obtained directly from Table 2. The average number of method statements (average_statements) is calculated according to Table 2. The calculation formula is:
average_statements=function_statements/functions.

The complexity parameter score (average) is calculated according to the following formula:
average＝(average_complexity*P61+average_block_depth*P62+average_s
tatements*P63)*C4;

Among them, average_complexity is the average cyclomatic complexity, average_block_depth is the average code depth, average_statements is the average number of method statements, P61, P62, and P63 are the sixth weights of average cyclomatic complexity, average code depth, and average number of method statements respectively, and C4 is the sixth weight. Four Constant, for example, C4 can be 205.

It should be noted that if the complexity parameter score (average) > the maintainability score, the complexity parameter score (average) is the maintainability score; if the complexity parameter score (average) ≤ maintainability score, then the complexity parameter score (average) is the actual calculated value.

Step 43: Calculate the first score based on the first n maximum values of the complexity parameter, the seventh weight of the first n maximum values of the complexity parameter, the sixth weight and the fifth constant of the complexity parameter, n is an integer greater than 1.

In this step, the top n numbers with the largest number of each complexity parameter are counted according to Table 2, and Table 3 is obtained. In the embodiment of the present disclosure, n is 3, and Table 3 is as follows:

table 3

Calculate the first score (top) according to the following formula:
top＝(first_com*P711+second_com*P712+
third_com*P713)*P61+(first_depth*P721+second_depth*P722+third_depth*P723)*P62+(first_stat*P731+second_stat*P732+third_stat*P733)*P63)*C5;

Among them, first_com, second_com, and third_com are the top three circles with the largest number respectively. Complexity, first_stat, second_stat, and third_stat are the number of the top three method statements with the largest number, first_depth, second_depth, and third_depth are the top three code depths with the largest number, P61, P62, and P63 are the cyclomatic complexity, code depth, and method statement respectively. The sixth weight of the number, P711, P712, and P713 are respectively the seventh weight of the first three cyclomatic complexities with the largest number, P721, P722, and P723 are respectively the seventh weight of the first three method statements with the largest number, P731, P732 and P733 are respectively the seventh weights of the first three code depths with the largest number, and C5 is the fifth constant. For example, C5 can be 19.

It should be noted that if the first score (top) > the maintainability score, then the first score (top) is the maintainability score; if the first score (top) ≤ the maintainability score, Then the first score (top) is the actual calculated value.

Step 44: Determine the maintainability score based on the first score, the complexity parameter score and the maintainability score.

In some embodiments, determining the maintainability score (ie, step 44) based on the first score, the complexity parameter score and the maintainability score includes the following steps: based on the first score (top) and the complexity The parameter score (average) calculates the score value, score value = top*0.5+average*0.5; in response to the score value being greater than or equal to the maintainability score, the maintainability score (Maintainability_Score) is determined to be the maintainability score. ; In response to the score value being less than the maintainability score, the maintainability score (Maintainability_Score) is determined to be the score value.

In some embodiments, as shown in Figure 5, the step of calculating the scalability score (Scalability_Score) includes:

Step 51: Determine the number of top m repeated lines with the largest number of repeated lines in a statement, and calculate the second score based on the sixth constant, the number of m repeated lines, and the m eighth weights, where m is an integer greater than 1.

In this step, analyze the duplication.xml file generated by the code duplication scanning tool cpd. According to the results generated by the duplication.xml file, according to the value of duplication->lines, sort from largest to smallest and take the top m , and calculate the number of repetitions of each repeated statement. In the embodiment of the present disclosure, m=3, and the top three with the largest number of repeated rows are top1, top2, and top3 respectively.

Calculate the second score (tops) according to the following formula: tops= (top1*P81+top2*P82+top3*P83)*C6; among them, top1, top2, and top3 are the three largest numbers of repeated rows, and P81, P82, and P83 are the eighth weight corresponding to top1, top2, and top3 respectively. , C6 is the sixth constant, for example, C6 can be 2.5.

Step 52: Determine the repetition level of the repeated statement based on the number of repeated lines, and for each repetition level, calculate the score of each repetition level based on the number of repeated lines and the number of repetitions of the repeated statement under the repetition level.

If the number of repeated lines is >49, the repetition level is high. Multiply the number of repeated lines (ni) of each high-level repeated statement (i) by its number of repetitions (xi), and add them up to obtain the high-level score. If 25>Number of repeated lines>49, the repetition level is medium. Multiply the number of repeated lines (ni) of each repeated statement (i) at the medium level by its number of repetitions (xi), and add them up to obtain a medium-level score. normal. If the number of repeated lines is <25, the repetition level is low. Multiply the number of repeated lines (ni) of each low-level repeated statement (i) by its number of repetitions (xi), and add them up to obtain the low-level score low.

Step 53: Calculate a third score based on the score of the repetition level, the ninth weight of the repetition level, the seventh constant, the scalable score, and the total number of lines of software code.

The formula for calculating the third score (weights) is:
weights＝(high*P91+normal*P92+low*P93)*C7*scalable score
/code_lines;

Among them, high, normal, and low are the scores of high, medium, and low repetition levels respectively, P91, P92, and P93 are the ninth weights of high, medium, and low repetition levels respectively, code_lines is the total number of lines of software code, and C7 is the seventh Constant, for example, C7 can be 40.

Step 54: Determine a scalability score based on the second score, the third score and the preset threshold.

In some embodiments, determining the scalability score (ie, step 54) based on the second score, the third score, and a preset threshold includes the following steps: updating the second score (tops) and the third score based on the preset threshold. (weights); wherein, in response to the second score (tops) being greater than or equal to the threshold, the second score (tops) is the threshold, and in response to the third score (weights) being greater than or equal to the threshold, the third score (weights) is the threshold; Calculate the sum of the second score (tops) and the third score (weights) to obtain the scalability score (Scalability_Score). In some embodiments, the threshold may be set to 500. It should be noted that if the second score (tops) is less than the threshold, then the second score The number is the actual calculated value (ie, the value calculated in step 51). If the third score (weights) is less than the threshold, the third score is the actual calculated value (ie, the value calculated in step 53).

In the embodiment of the present disclosure, metric score (All_Score)=Functionality_Score*P21+Security_Score*P22+Maintainability_Score*P23+Scalability_Score*P24;

Among them, Functionality_Score is the score of functionality, Security_Score is the score of security, Maintainability_Score is the score of maintainability, Scalability_Score is the score of scalability, P21 is the second weight of functionality, and P22 is the second weight of security. P23 is the second weight of maintainability, and P24 is the second weight of scalability.

It should be noted that each constant (the first constant to the seventh constant) in the embodiment of the present disclosure is a fitting value, which is set to allow the score of a certain characteristic dimension to have more probability in the entire measurement result, so that it Falling more evenly within the score of the corresponding feature dimension (for example, 1000), the value of each constant can be adjusted according to the highest score of the software project to be measured.

The disclosed embodiments can be applied in a CI (Continuous Integration) continuous integration environment. It is called regularly every day, calculated through the solidified docker (application container engine), and the calculation results are written into the database for persistence. By analyzing the database data and Through interface display, etc., you can clearly see the development trend of the quality of the project code architecture and conduct quality control on the code. It should be noted that the embodiments of the present disclosure are not limited to applications in CI continuous integration environments, but can be used in all software development code measurement processes.

The embodiment of the present disclosure is a code-level architecture measurement solution generated to meet the actual status of quantifiable, multi-dimensional overall architecture measurement of code. Based on the eight characteristics of the software quality model defined in ISO25010, the measurement indicators of each characteristic dimension are extracted, calculated according to the weight according to the customized measurement algorithm formula, and finally the absolute score is obtained as the measurement result. Among them, the scores and weights of each feature dimension are not fixed values and can be configured or modified according to actual usage. The level of measurement scores can provide intuitive feedback on the quality level and degree of corruption of the current software architecture. Improvements based on measurement results can also be quickly fed back. Through this continuous closed-loop improvement, the software quality level can ultimately be improved and the architecture can be effectively prevented. of corruption.

Based on the same technical concept, embodiments of the present disclosure also provide a code measurement device, as shown in Figure As shown in 6, the code measurement device includes a metric index extraction module 101, a feature dimension score calculation module 102 and a metric score calculation module 103.

The metric index extraction module 101 is configured to obtain metric indexes of the software code to be measured, where the metric indexes include metric indexes of at least two characteristic dimensions.

The characteristic dimension score calculation module 102 is configured to respectively calculate the scores of the characteristic dimensions according to the first weight of each metric in the characteristic dimension and the score of the characteristic dimension.

The metric score calculation module 103 is configured to calculate a metric score according to the score of the characteristic dimension and the second weight of the characteristic dimension, where the metric score is used to measure the quality of the software code to be measured.

In some embodiments, the feature dimensions include any combination of the following: functionality, security, maintainability, scalability, efficiency, ease of use, reliability, and portability.

In some embodiments, the feature dimension score calculation module 102 is configured to calculate scores for functional metric indicators, where the functional metric indicators include one or any combination of the following: coverage, vulnerability level, first vulnerability impact Level, the first vulnerability impact level is the impact level of quality and diversity vulnerabilities; calculate the weighted sum of the scores of each metric index of the functionality and the first weight of each metric index of functionality in functionality, and obtain Functional rating.

In some embodiments, the coverage score is calculated based on branch coverage and functionality scores; the vulnerability level score is calculated based on the number of vulnerabilities at each vulnerability level, the third weight of each vulnerability level, the first constant, the functional The score and the total number of lines of software code are calculated; the score of the first vulnerability impact level is based on the number of vulnerabilities of each first vulnerability impact level, the fourth weight of each first vulnerability impact level, the functional score, the second constant and The total number of lines of software code is calculated.

In some embodiments, the security metric includes a second vulnerability impact level, and the second vulnerability impact level is the impact level of security and diversity vulnerabilities; the feature dimension score calculation module 102 is used to calculate the second vulnerability impact level according to the impact of each second vulnerability. The security score is calculated based on the number of vulnerabilities in the level, the fifth weight of each second vulnerability impact level, the security score, the third constant and the total number of lines of software code.

In some embodiments, the maintainability metric includes complexity, and the feature dimension score calculation module 102 is configured to obtain a complexity parameter, where the complexity parameter includes one of the following parameters: One or any combination: cyclomatic complexity, code depth, and number of method statements; calculate the complexity parameter score based on the complexity parameter, the sixth weight of the complexity parameter, the maintainability score, and the fourth constant; The first score is calculated based on the first n maximum values of the complexity parameter, the seventh weight of the first n maximum values of the complexity parameter, the sixth weight of the complexity parameter and the fifth constant, n is greater than an integer of 1; determine a maintainability score based on the first score, the complexity parameter score and the maintainability score.

In some embodiments, the feature dimension score calculation module 102 is configured to calculate a score value according to the first score and the complexity parameter score; in response to the score value being greater than or equal to the maintainability score , determining the maintainability score to be the maintainability score; in response to the score being less than the maintainability score, determining the maintainability score to be the score.

In some embodiments, the scalability metric includes duplication, and the feature dimension score calculation module 102 is configured to determine the number of top m repeated rows with the largest number of repeated rows of a statement, according to the sixth constant, the m Calculate the second score by weighting the number of repeated lines and m eighth weights, where m is an integer greater than 1; determine the repetition level of the repeated statement based on the number of repeated lines, and for each repetition level, according to each location under the repetition level Calculate the score of each repetition level based on the number of repeated lines and the number of repetitions of the repeated statements; based on the score of the repetition level, the ninth weight of each repetition level, the seventh constant, the scalability score and the total lines of software code number, calculate a third score; and determine a scalability score based on the second score, the third score and a preset threshold.

In some embodiments, the characteristic dimension score calculation module 102 is configured to update the second score and the third score according to a preset threshold; wherein in response to the second score being greater than or equal to the threshold, the The second score is the threshold, and in response to the third score being greater than or equal to the threshold, the third score is the threshold; calculating the sum of the second score and the third score, we can obtain Scalability rating.

Embodiments of the present disclosure also provide a computer device. The computer device includes: one or more processors and a storage device; wherein one or more programs are stored on the storage device. When the one or more programs are used by the above-mentioned one When executed by or multiple processors, the above one or more processors implement the code measurement method as provided in the foregoing embodiments.

Embodiments of the present disclosure also provide a computer-readable medium with a computer program stored thereon, When the computer program is executed, the code measurement method as provided in the foregoing embodiments is implemented.

Those of ordinary skill in the art can understand that all or some steps in the methods disclosed above and functional modules/units in the devices can be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware implementations, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may consist of several physical components. Components execute cooperatively. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit . Such software may be distributed on computer-readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). As is known to those of ordinary skill in the art, the term computer storage media includes volatile and nonvolatile media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. removable, removable and non-removable media. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disk (DVD) or other optical disk storage, magnetic cassettes, tapes, disk storage or other magnetic storage devices, or may Any other medium used to store the desired information and that can be accessed by a computer. Additionally, it is known to those of ordinary skill in the art that communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media .

Example embodiments have been disclosed herein, and although specific terms are employed, they are used and should be interpreted in a general illustrative sense only and not for purpose of limitation. In some instances, it will be apparent to those skilled in the art that features, characteristics and/or elements described in connection with a particular embodiment may be used alone, or may be used in conjunction with other embodiments, unless expressly stated otherwise. Features and/or components used in combination. Accordingly, it will be understood by those skilled in the art that various changes in form and details may be made without departing from the scope of the invention as set forth in the appended claims.

Claims

A code measurement method, the method includes:

Obtain measurement indicators of the software code to be measured, where the measurement indicators include measurement indicators of at least two characteristic dimensions;

Calculate the scores of the characteristic dimensions respectively according to the first weight of the measurement indicator in the characteristic dimension and the score of the characteristic dimension;

A measurement score is calculated according to the score of the characteristic dimension and the second weight of the characteristic dimension, and the measurement score is used to measure the quality of the software code to be measured.
The method of claim 1, wherein the characteristic dimensions include any combination of the following: functionality, security, maintainability, scalability, efficiency, ease of use, reliability, and portability.
The method of claim 2, wherein calculating the functional score includes:

Calculate the score of the functional metric, which includes one or any combination of the following: coverage, vulnerability level, first vulnerability impact level, where the first vulnerability impact level is quality and diversity The impact level of the vulnerability;

Calculate the weighted sum of the score of the metric index of the functionality and the first weight of the metric index of the functionality in functionality to obtain a score of functionality.
The method of claim 3, wherein the coverage score is calculated based on branch coverage and functionality scores;

The vulnerability level score is calculated based on the number of vulnerabilities in the vulnerability level, the third weight of the vulnerability level, the first constant, the functionality score and the total number of lines of software code;

The score of the first vulnerability impact level is based on the number of vulnerabilities of each first vulnerability impact level, the description The fourth weight of the first vulnerability impact level, the functional score, the second constant and the total number of lines of software code are calculated.
The method of claim 2, wherein the security measurement index includes a second vulnerability impact level, and the second vulnerability impact level is the impact level of security and diversity vulnerabilities; the step of calculating the security score includes:

A security score is calculated based on the number of vulnerabilities of the second vulnerability impact level, the fifth weight of the second vulnerability impact level, the security score, the third constant and the total number of lines of software code.
The method of claim 2, wherein the maintainability metric includes complexity, and the step of calculating the maintainability score includes:

Obtain complexity parameters, which include one or any combination of the following parameters: cyclomatic complexity, code depth, and number of method statements;

Calculate a complexity parameter score according to the complexity parameter, the sixth weight of the complexity parameter, the maintainability score and the fourth constant;

The first score is calculated according to the first n maximum values of each complexity parameter, the seventh weight of the first n maximum values of the complexity parameter, the sixth weight and the fifth constant of the complexity parameter, n is an integer greater than 1;

A maintainability score is determined based on the first score, the complexity parameter score, and a maintainability score.
The method of claim 6, wherein determining a maintainability score based on the first score, the complexity parameter score and a maintainability score includes:

Calculate a score value based on the first score and the complexity parameter score;

In response to the score value being greater than or equal to the maintainability score, determining the maintainability score to be the maintainability score;

In response to the score value being less than the maintainability score, the maintainability score is determined to be the score value.
The method of claim 2, wherein the scalability metric includes repeatability, and the step of calculating the scalability score includes:

Determine the number of the first m repeated rows with the largest number of repeated rows in the statement, and calculate the second score based on the sixth constant, the m repeated row numbers and m eighth weights, where m is an integer greater than 1;

Determine the repetition level of the repeated statement based on the number of repeated lines, and for each repetition level, calculate the score of each repetition level based on the number of repeated lines and the number of repetitions of the repeated statement under the repeated level;

Calculate a third score based on the score of the repetition level, the ninth weight of the repetition level, the seventh constant, the scalability score, and the total number of lines of software code;

A score of scalability is determined based on the second score, the third score and a preset threshold.
The method of claim 8, wherein determining the scalability score according to the second score, the third score and a preset threshold includes:

The second score and the third score are updated according to a preset threshold; wherein, in response to the second score being greater than or equal to the threshold, the second score is the threshold, and in response to the third score Greater than or equal to the threshold, the third score is the threshold;

The sum of the second score and the third score is calculated to obtain a scalability score.
A code measurement device, including a metric index extraction module, a feature dimension score calculation module and a metric score calculation module,

The metric index extraction module is configured to obtain metric indexes of the software code to be measured, where the metric indexes include metric indexes of at least two characteristic dimensions;

The characteristic dimension score calculation module is configured to calculate the score of the characteristic dimension according to the first weight of the measurement index in the characteristic dimension and the score of each characteristic dimension;

The metric score calculation module is configured to calculate a metric score according to the score of the characteristic dimension and the second weight of each characteristic dimension, where the metric score is used to measure the quality of the software code to be measured.
A computer device consisting of:

at least one processor;

a storage device having at least one program stored thereon;

When the one or more programs are executed by the at least one processor, the at least one processor is caused to implement the code measurement method according to any one of claims 1-9.
A computer-readable medium having a computer program stored thereon, wherein when the program is executed, the code measurement method according to any one of claims 1-9 is implemented.