CN115510847A - Code workload analysis method and device - Google Patents
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Abstract
The invention discloses a method and a device for analyzing code workload, which relate to the technical field of finance, wherein the method comprises the following steps: acquiring a code file to be analyzed; performing word segmentation processing on the code file to be analyzed to obtain a plurality of words; carrying out classification statistics on a plurality of participles, grouping the same participles into a group, and determining the number of each group of participles; respectively determining the number of code files containing each group of participles in a plurality of preset code files aiming at each group of participles; determining the weight value of each group of participles in the code file to be analyzed by using a TF-IDF algorithm according to the number of each group of participles in the code file to be analyzed and the number of code files containing each group of participles in a plurality of code files; and carrying out weighted calculation on the number of each group of participles in the code file to be analyzed and the weight value of each group of participles to obtain an analysis result of the code workload of the code file to be analyzed. The invention can improve the accuracy of the code workload analysis result.
Description
Technical Field
The invention relates to the technical field of finance, in particular to a code workload analysis method and device.
Background
This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
At present, when a business function is developed, the amount of workload required by the business function is measured, and indexes such as code number, blank number, code line number and the like in a code file of the business function are often analyzed, so that the analysis method is not objective and rigorous, the analysis result is inaccurate, and the actual workload of the code cannot be quantized.
Disclosure of Invention
The embodiment of the invention provides a code workload analysis method, which is used for improving the accuracy of a code workload analysis result and comprises the following steps:
acquiring a code file to be analyzed;
performing word segmentation processing on the code file to be analyzed to obtain a plurality of words;
carrying out classification statistics on a plurality of participles, grouping the same participles into a group, and determining the number of each group of participles in a code file to be analyzed;
aiming at each group of participles, respectively determining the number of code files containing each group of participles in a plurality of code files according to a plurality of preset code files;
determining the weight value of each group of participles in the code file to be analyzed by using a TF-IDF algorithm according to the number of each group of participles in the code file to be analyzed and the number of code files containing each group of participles in a plurality of code files;
and carrying out weighted calculation on the number of each group of participles in the code file to be analyzed and the weight value of each group of participles to obtain an analysis result of the code workload of the code file to be analyzed.
The embodiment of the invention also provides a device for analyzing the code workload, which is used for improving the accuracy of the analysis result of the code workload and comprises the following components:
the acquisition module is used for acquiring a code file to be analyzed;
the word segmentation module is used for carrying out word segmentation processing on the code file to be analyzed to obtain a plurality of words;
the first statistical module is used for carrying out classification statistics on a plurality of participles, grouping the same participles into one group and determining the number of each group of participles in the code file to be analyzed;
the second statistical module is used for respectively determining the number of the code files containing each group of participles in the plurality of code files according to the plurality of preset code files aiming at each group of participles;
the processing module is used for determining the weight value of each group of participles in the code file to be analyzed by using a TF-IDF algorithm according to the number of each group of participles in the code file to be analyzed and the number of the code files containing each group of participles in the plurality of code files;
and the weighting module is used for carrying out weighting calculation on the number of each group of participles in the code file to be analyzed and the weight value of each group of participles to obtain an analysis result of the code workload of the code file to be analyzed.
The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein when the processor executes the computer program, the analysis method of the code workload is realized.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the method for analyzing the workload of the code.
An embodiment of the present invention further provides a computer program product, where the computer program product includes a computer program, and when the computer program is executed by a processor, the computer program implements the method for analyzing the code workload.
In the embodiment of the invention, a code file to be analyzed is obtained; performing word segmentation processing on the code file to be analyzed to obtain a plurality of words; carrying out classification statistics on a plurality of participles, grouping the same participles into a group, and determining the number of each group of participles in a code file to be analyzed; aiming at each group of participles, respectively determining the number of code files containing each group of participles in a plurality of code files according to a plurality of preset code files; determining the weight value of each group of participles in the code file to be analyzed by using a TF-IDF algorithm according to the number of each group of participles in the code file to be analyzed and the number of code files containing each group of participles in a plurality of code files; and performing weighted calculation on the quantity of each group of participles in the code file to be analyzed and the weight value of each group of participles to obtain an analysis result of the code workload of the code file to be analyzed. Compared with the prior technical scheme of code workload analysis, the method has the advantages that the word segmentation processing is carried out on the code file to be analyzed, the weighted value of the word segmentation is determined by using the TF-IDF algorithm, and the code workload of the code file to be analyzed is calculated in a weighted calculation mode, so that the quantitative analysis of the actual workload of the code can be realized, and the accuracy of the code workload analysis result is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention 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 invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:
FIG. 1 is a flow chart of a method for analyzing code workload according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for determining a weight value of each group of participles in a code file to be analyzed by using a TF-IDF algorithm according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an apparatus for analyzing code workload according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a processing module provided in an embodiment of the invention;
fig. 5 is a schematic diagram of a computer device provided in an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
In the description of the present specification, the terms "comprising," "including," "having," "containing," and the like are used in an open-ended fashion, i.e., to mean including, but not limited to. Reference to the description of the terms "one embodiment," "a particular embodiment," "some embodiments," "for example," etc., means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. The sequence of steps involved in the embodiments is for illustrative purposes to illustrate the implementation of the present application, and the sequence of steps is not limited and can be adjusted as needed.
Research shows that when a business function is developed, the workload of the business function is measured, and indexes such as code number, blank number, code line number and the like in a code file of the business function are analyzed, so that the analysis method is not objective and rigorous, the analysis result is not accurate, and the actual workload of the code cannot be quantized.
In view of the above research, the embodiment of the present invention provides an analysis scheme for a code workload, which can quantify an actual workload of a code and improve accuracy of a code workload analysis result.
As shown in fig. 1, a flowchart of a method for analyzing code workload according to an embodiment of the present invention is provided, where the method includes the following steps:
102, performing word segmentation processing on a code file to be analyzed to obtain a plurality of words;
103, carrying out classification statistics on a plurality of participles, grouping the same participles into one group, and determining the number of each group of participles in the code file to be analyzed;
104, aiming at each group of participles, respectively determining the number of code files containing each group of participles in a plurality of code files according to a plurality of preset code files;
105, determining the weight value of each group of participles in the code file to be analyzed by using a TF-IDF algorithm according to the number of each group of participles in the code file to be analyzed and the number of code files containing each group of participles in a plurality of code files;
and 106, performing weighted calculation on the number of each group of participles in the code file to be analyzed and the weight value of each group of participles to obtain an analysis result of the code workload of the code file to be analyzed.
In the embodiment of the invention, a code file to be analyzed is obtained; performing word segmentation processing on the code file to be analyzed to obtain a plurality of words; carrying out classification statistics on a plurality of participles, grouping the same participles into a group, and determining the number of each group of participles in a code file to be analyzed; aiming at each group of participles, respectively determining the number of code files containing each group of participles in a plurality of code files according to a plurality of preset code files; determining the weight value of each group of participles in the code file to be analyzed by using a TF-IDF algorithm according to the number of each group of participles in the code file to be analyzed and the number of code files containing each group of participles in a plurality of code files; and carrying out weighted calculation on the number of each group of participles in the code file to be analyzed and the weight value of each group of participles to obtain an analysis result of the code workload of the code file to be analyzed. Compared with the prior technical scheme of code workload analysis, the method has the advantages that the word segmentation processing is carried out on the code file to be analyzed, the weighted value of the word segmentation is determined by using the TF-IDF algorithm, and the code workload of the code file to be analyzed is calculated in a weighted calculation mode, so that the quantitative analysis of the actual workload of the code can be realized, and the accuracy of the code workload analysis result is improved.
The method of analyzing the code workload shown in fig. 1 will be described in detail below.
In the above step 101, first, a code file to be analyzed is acquired.
The code file to be analyzed is a code file corresponding to a service function. The code file to be analyzed comprises a pair of code segments.
In the step 102, a word segmentation process is performed on the code file to be analyzed to obtain a plurality of words.
In an embodiment of the present invention, the step 102 may specifically include:
and performing word segmentation processing on the code file to be analyzed by taking the space character as a basis to obtain a plurality of word segments.
In specific implementation, most programming languages have a space as a separator, so that word segmentation processing can be performed on a code file to be analyzed according to the space.
It should be noted that before the word segmentation processing is performed on the code file to be analyzed, noise symbols (e.g., ") and distracters in the code file to be analyzed may also be removed, and then the code file to be analyzed is divided into a single word.
In the step 103, since there may be a plurality of same participles in the plurality of participles obtained in the step 102, the plurality of participles may be classified and counted, the same participles are grouped into one group, and the number of each group of participles in the code file to be analyzed is determined.
In step 104, in order to further determine the importance of each group of participles, the number of code files containing each group of participles in the plurality of code files may be determined according to a plurality of preset code files for each group of participles.
The preset code files can be code files with historical service functions collected and added into the corpus.
In the above step 105, a weight value of each group of participles in the code file to be analyzed is determined by using a TF-IDF algorithm according to the number of each group of participles in the code file to be analyzed and the number of code files containing each group of participles in the plurality of code files.
It should be noted that, the TF-IDF algorithm: (term frequency-inverse document frequency) is a commonly used weighting technique for information retrieval and data mining. TF is Term Frequency (Term Frequency) and IDF is Inverse text Frequency index (Inverse Document Frequency). TF-IDF is a statistical method used to evaluate the importance of a word to one of a set of documents or a corpus.
TF = number of occurrences of term in the document/number of terms of all of the document;
IDF = log (N/d), N being the total number of all documents; d is the total number of documents in which a word has occurred.
TF-IDF＝TF×IDF。
In an embodiment of the present invention, as shown in fig. 2, the step 105 may specifically include:
When the method is specifically implemented, the TF-IDF algorithm is utilized, keywords in a plurality of participles can be extracted, and the weight of each keyword can be determined. That is, the importance of a word segmentation increases in direct proportion to the number of times it appears in the code file to be analyzed, but at the same time decreases in inverse proportion to the frequency with which it appears in the corpus.
In the embodiment of the present invention, if a word segmentation occurs in each code file in the corpus, the word segmentation may be defined as an invalid word segmentation, and the weight value of the invalid word segmentation is 0. Therefore, after the step 105, the method may further include:
and removing the participles with the weight value of 0 according to the weight value of each group of participles in the code file to be analyzed.
In step 106, the number of each group of participles in the code file to be analyzed and the weight value of each group of participles may be subjected to weighted calculation to obtain an analysis result of the code workload of the code file to be analyzed.
Therefore, word segmentation processing is carried out on the code file to be analyzed, keyword extraction is carried out on each word segmentation by using the TF-IDF algorithm, the weight value of the keyword is determined, and then the code workload of the code file to be analyzed is calculated in a weighting calculation mode, so that quantitative analysis of the actual workload of the code can be realized, and the accuracy of the code workload analysis result is improved.
The embodiment of the invention also provides a device for analyzing the code workload, which is described in the following embodiment. Because the principle of the device for solving the problems is similar to the analysis method of the code workload, the implementation of the device can refer to the implementation of the analysis method of the code workload, and repeated details are not repeated.
As shown in fig. 3, a schematic diagram of an apparatus for analyzing code workload according to an embodiment of the present invention is provided, where the apparatus includes:
an obtaining module 301, configured to obtain a code file to be analyzed;
the word segmentation module 302 is configured to perform word segmentation processing on the code file to be analyzed to obtain a plurality of words;
the first statistical module 303 is configured to perform classification statistics on the multiple participles, group the same participles into one group, and determine the number of each group of participles in the code file to be analyzed;
a second statistical module 304, configured to determine, for each group of participles, the number of code files containing each group of participles in the plurality of code files, according to a plurality of preset code files, respectively;
a processing module 305, configured to determine, according to the number of each group of participles in the code file to be analyzed and the number of code files containing each group of participles in the multiple code files, a weight value of each group of participles in the code file to be analyzed by using a TF-IDF algorithm;
the weighting module 306 is configured to perform weighting calculation on the number of each group of participles in the code file to be analyzed and the weight value of each group of participles to obtain an analysis result of the code workload of the code file to be analyzed.
In the embodiment of the present invention, the word segmentation module may be specifically configured to:
and performing word segmentation processing on the code file to be analyzed by taking the space character as a basis to obtain a plurality of word segments.
In the embodiment of the present invention, the apparatus further includes a removing module, configured to, after the processing module determines, according to the number of each group of participles in the code file to be analyzed and the number of code files containing each group of participles in the plurality of code files, a weight value of each group of participles in the code file to be analyzed by using a TF-IDF algorithm:
and removing the participles with the weight value of 0 according to the weight value of each group of participles in the code file to be analyzed.
In the embodiment of the present invention, as shown in fig. 4, the processing module includes:
a probability value calculating unit 401, configured to determine a probability value of each group of participles appearing in the code file to be analyzed according to the number of each group of participles in the code file to be analyzed and the total number of the plurality of participles in the code file to be analyzed;
an inverse text frequency index calculation unit 402, configured to substitute the total number of the plurality of code files and the number of code files containing each group of participles in the plurality of code files into a logarithmic function formula, and determine an inverse text frequency index of each group of participles;
the weight calculating unit 403 is configured to multiply a probability value of each group of participles appearing in the code file to be analyzed by the inverse text frequency index of each group of participles to obtain a weight value of each group of participles in the code file to be analyzed.
An embodiment of the present invention further provides a computer device, as shown in fig. 5, which is a schematic diagram of the computer device in the embodiment of the present invention, where the computer device 500 includes a memory 510, a processor 520, and a computer program 530 stored in the memory 510 and capable of being executed on the processor 520, and when the processor 520 executes the computer program 530, the method for analyzing the code workload is implemented.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the method for analyzing the workload of the code.
An embodiment of the present invention further provides a computer program product, where the computer program product includes a computer program, and when the computer program is executed by a processor, the computer program implements the method for analyzing the code workload.
In the embodiment of the invention, a code file to be analyzed is obtained; performing word segmentation processing on the code file to be analyzed to obtain a plurality of words; carrying out classification statistics on a plurality of participles, grouping the same participles into a group, and determining the number of each group of participles in a code file to be analyzed; aiming at each group of participles, respectively determining the number of code files containing each group of participles in a plurality of code files according to a plurality of preset code files; determining the weight value of each group of participles in the code file to be analyzed by using a TF-IDF algorithm according to the number of each group of participles in the code file to be analyzed and the number of code files containing each group of participles in a plurality of code files; and carrying out weighted calculation on the number of each group of participles in the code file to be analyzed and the weight value of each group of participles to obtain an analysis result of the code workload of the code file to be analyzed. Compared with the prior technical scheme of code workload analysis, the method has the advantages that the word segmentation processing is carried out on the code file to be analyzed, the weighted value of the word segmentation is determined by using the TF-IDF algorithm, and the code workload of the code file to be analyzed is calculated in a weighted calculation mode, so that the quantitative analysis of the actual workload of the code can be realized, and the accuracy of the code workload analysis result is improved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (11)
1. A method for analyzing code workload, comprising:
acquiring a code file to be analyzed;
performing word segmentation processing on the code file to be analyzed to obtain a plurality of words;
carrying out classification statistics on a plurality of participles, grouping the same participles into a group, and determining the number of each group of participles in a code file to be analyzed;
aiming at each group of participles, respectively determining the number of code files containing each group of participles in a plurality of code files according to a plurality of preset code files;
determining the weight value of each group of participles in the code file to be analyzed by using a TF-IDF algorithm according to the number of each group of participles in the code file to be analyzed and the number of code files containing each group of participles in a plurality of code files;
and carrying out weighted calculation on the number of each group of participles in the code file to be analyzed and the weight value of each group of participles to obtain an analysis result of the code workload of the code file to be analyzed.
2. The method of claim 1, wherein performing a word segmentation process on the code file to be analyzed to obtain a plurality of words, comprises:
and performing word segmentation processing on the code file to be analyzed by taking the space character as a basis to obtain a plurality of word segments.
3. The method of claim 1, wherein after determining the weight value of each group of participles in the code file to be analyzed using a TF-IDF algorithm according to the number of each group of participles in the code file to be analyzed and the number of code files containing each group of participles in the plurality of code files, further comprising:
and removing the participles with the weight value of 0 according to the weight value of each group of participles in the code file to be analyzed.
4. The method of claim 1, wherein determining a weighted value for each group of participles in the code file to be analyzed using a TF-IDF algorithm based on the number of each group of participles in the code file to be analyzed, the total number of the plurality of code files, and the number of code files containing each group of participles in the plurality of code files comprises:
determining a probability value of each group of participles appearing in the code file to be analyzed according to the number of each group of participles in the code file to be analyzed and the total number of the plurality of participles in the code file to be analyzed;
substituting the total number of the plurality of code files and the number of the code files containing each group of participles in the plurality of code files into a logarithmic function formula to determine the inverse text frequency index of each group of participles;
and multiplying the probability value of each group of participles in the code file to be analyzed by the inverse text frequency index of each group of participles to obtain the weight value of each group of participles in the code file to be analyzed.
5. An apparatus for analyzing a code workload, comprising:
the acquisition module is used for acquiring a code file to be analyzed;
the word segmentation module is used for carrying out word segmentation on the code file to be analyzed to obtain a plurality of words;
the first statistical module is used for carrying out classification statistics on the multiple participles, grouping the same participles into one group, and determining the number of each group of participles in the code file to be analyzed;
the second statistical module is used for respectively determining the number of the code files containing each group of participles in the plurality of code files according to the plurality of preset code files aiming at each group of participles;
the processing module is used for determining the weight value of each group of participles in the code file to be analyzed by using a TF-IDF algorithm according to the number of each group of participles in the code file to be analyzed and the number of the code files containing each group of participles in the plurality of code files;
and the weighting module is used for carrying out weighting calculation on the number of each group of participles in the code file to be analyzed and the weight value of each group of participles to obtain an analysis result of the code workload of the code file to be analyzed.
6. The apparatus of claim 5, wherein the word segmentation module is specifically configured to:
and performing word segmentation processing on the code file to be analyzed by taking the space character as a basis to obtain a plurality of word segments.
7. The apparatus of claim 5, further comprising a removal module, configured to, after the processing module determines the weight value of each group of participles in the code file to be analyzed using a TF-IDF algorithm according to the number of each group of participles in the code file to be analyzed and the number of code files containing each group of participles in the plurality of code files:
and removing the participles with the weight value of 0 according to the weight value of each group of participles in the code file to be analyzed.
8. The apparatus of claim 5, wherein the processing module comprises:
the probability value calculating unit is used for determining the probability value of each group of participles appearing in the code file to be analyzed according to the number of each group of participles in the code file to be analyzed and the total number of the participles in the code file to be analyzed;
the device comprises an inverse text frequency index calculation unit, a log function formula calculation unit and a word segmentation unit, wherein the inverse text frequency index calculation unit is used for substituting the total number of a plurality of code files and the number of the code files containing each group of participles in the plurality of code files into the log function formula to determine the inverse text frequency index of each group of participles;
and the weight calculation unit is used for multiplying the probability value of each group of participles appearing in the code file to be analyzed by the inverse text frequency index of each group of participles to obtain the weight value of each group of participles in the code file to be analyzed.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 4 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the method of any of claims 1 to 4.
11. A computer program product, characterized in that the computer program product comprises a computer program which, when being executed by a processor, carries out the method of any one of claims 1 to 4.
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