CN113821213A - Front-end code detection and restoration method, device and equipment based on artificial intelligence - Google Patents
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Abstract
The invention discloses a front-end code detection and restoration method based on artificial intelligence, which is applied to the technical field of artificial intelligence and used for detecting and restoring front-end codes. The method provided by the invention comprises the following steps: acquiring a first configuration file and saving a saving position path to a global configuration file of the front-end project; analyzing the first configuration file and generating a second configuration file by combining the global configuration information of the front-end project; detecting the codes in the front-end project according to the second configuration file and a predefined detection method, and repairing the codes in the front-end project according to the second configuration file and a predefined repair method; counting the detection result data and the repair result data for visual display; and after the code submission history is matched with the detection result data and the repair result data, acquiring the information of submitters of error codes and sending the information to the related personnel of the front-end project.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a front-end code detection and repair method and device based on artificial intelligence, a computer device and a storage device.
Background
In the current front-end engineering project, the engineering project is more complex due to more complex service and functions, and the whole line number of codes is multiplied. Therefore, the method is required to be applied to improve the code quality and maintainability of the front-end project, improve the robustness of the code, improve the project development efficiency and reduce the problems in the project testing link.
The method of the traditional technology at present is to unify the code style and the specification in the early stage of project development and then generate a unified specification document, and developers can consciously make a custom to abide by the specification in the development process. But there are other situations in the actual project development process: firstly, in the process of actually developing and writing codes, a developer can write codes and specifications with certain difference due to various reasons; secondly, a new person who newly joins a project can neglect the content of the project development specification document, and can develop the project according to the original personal code writing habit in the actual development process.
In the two situations, the code style in the engineering project is difficult to unify, and the integral readability and maintainability of the front-end project are reduced; when a problem occurs and code checking is carried out, not only is the difficulty increased, but also much time is consumed, and source tracing and responsibility tracing management are not carried out on the information of the submitter of the problem code; meanwhile, the progress of project development and the quality of the project are also seriously affected.
Disclosure of Invention
The embodiment of the invention provides a front-end code detection and repair method and device based on artificial intelligence, computer equipment and a storage medium, and aims to solve the problems of low code quality and maintainability and low development efficiency caused by non-standard codes in front-end codes.
A front-end code detection and repair method based on artificial intelligence comprises the following steps:
acquiring a first configuration file to a front-end project, and saving a position path for saving the first configuration file to a global configuration file of the front-end project;
searching and analyzing the first configuration file according to the global configuration file, and generating a second configuration file by combining the global configuration information of the front-end project in the global configuration file;
detecting the codes in the front-end project according to the second configuration file and a predefined detection method, and repairing the codes in the front-end project according to the second configuration file and a predefined repair method;
counting detection result data and repair result data for visual display, and storing the detection result data and the repair result data;
and acquiring a code submission history of the developer of the front-end project, matching the code submission history with the detection result data and the repair result data, acquiring the information of submitters of error codes and sending the information to the associated staff of the front-end project.
An artificial intelligence based front-end code detection and repair device, comprising:
the system comprises a first configuration file acquisition module, a first configuration file acquisition module and a second configuration file acquisition module, wherein the first configuration file acquisition module is used for acquiring a first configuration file to a front-end project and storing a position path for storing the first configuration file to a global configuration file of the front-end project;
the second configuration file generation module is used for searching and analyzing the first configuration file according to the global configuration file, and generating a second configuration file by combining the global configuration information of the front-end project in the global configuration file;
a detection and repair module, configured to detect a code in the front-end item according to the second configuration file and a predefined detection method, and repair the code in the front-end item according to the second configuration file and the predefined repair method;
the result counting module is used for counting the detection result data and the repair result data for visual display and storing the detection result data and the repair result data;
and the sending module is used for acquiring a code submission historical record of a developer of the front-end project, matching the code submission historical record with the detection result data and the repair result data, acquiring the information of submitters of error codes and sending the information to the related personnel of the front-end project.
A computer device comprising a memory, a processor and a computer program stored in said memory and executable on said processor, said processor implementing the steps of the artificial intelligence based front end code detection and repair method described above when executing said computer program.
A computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the artificial intelligence based front-end code detection and repair method described above.
According to the method and the device for detecting and repairing the front-end code based on the artificial intelligence, the computer equipment and the storage medium, the code content of the front-end project is detected and repaired according to the preset rules and the preset detection method and repair method, and meanwhile, the information of the submitter of the problem code is traced to the source, so that the code in the front-end project is enabled to be more in line with the standard, the responsibility management of technical developers is perfected, and the quality and the maintainability of the code are further improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
FIG. 1 is a schematic diagram of an application environment of an artificial intelligence-based method for detecting and repairing a front-end code according to an embodiment of the present invention;
FIG. 2 is a flowchart of an artificial intelligence based front-end code detection and repair method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an artificial intelligence based front-end code detection and repair apparatus according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a computer device according to an embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The artificial intelligence based front-end code detection and repair method provided by the present application can be applied in the application environment 100 as shown in fig. 1, wherein the computer device 102 communicates with the server 101 through the network 103. The computer device 102 may be, but is not limited to, various personal computers and notebook computers.
The server 101 may be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a web service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), and a big data and artificial intelligence platform.
The network 103 may be a wired connection network, a wireless connection network, a virtual private network, and the like.
At least one of the computer operating systems such as Windows, Linux, macOS, etc. is installed on the computer device 102. Various software development tools and software development environments, and application software such as browsers, for example Chrome, Visual Studio Code, Git, node. js, npm (node Package manager), etc., may be installed on the computer device 102.
It will be appreciated that the number of servers, networks and computer devices in fig. 1 is merely illustrative and that any number of extensions may be made depending on the actual needs.
In some embodiments, as shown in fig. 2, an artificial intelligence based front-end code detection and repair method is provided, which is described by taking the method as an example applied to the computer device 102 in fig. 1, and includes the following steps:
s201, acquiring a first configuration file to a front-end project, and saving a position path for saving the first configuration file to a global configuration file of the front-end project;
specifically, the present application provides a self-developed artificial intelligence based front-end code detection and repair tool, which includes code detection, code repair, data statistics, intelligent correction, history tracking, and other functions. The code detection function is to detect the codes of the front-end projects by using a preset custom rule and a preset custom method and output a detection result; the code repairing function is to repair the detected problem codes by using a preset custom rule and a preset method and output a repairing result; the data statistics function is to output the result statistics of code detection and code repair from various dimensions and by various methods in various forms; the intelligent correction function is to optimize the detection result and the repair result by using an artificial intelligence algorithm and a machine learning method; and the history tracking function is to search the problem code submission history record stored by the version control tool in the front-end project and track the information of the submitter of the problem code.
In this embodiment, the global profile is named packet.
Wherein the artificial intelligence based front end code detection and repair tool is released into the NPM repository deployed on the server 101 after being developed. The computer device 102 can access the code management service on the server 101, and download the project file (including all code files, configuration files, etc.) of the front-end project; the computer device 102 may also switch to a root path where the front-end project is located in a command line tool of a computer operating system, access an NPM resource library deployed on the server 101 through an install command of an NPM software development tool, and download the artificial intelligence-based front-end code detection and repair tool to the front-end project.
The parameters in the install command further include description information such as the name of the artificial intelligence-based front-end code detection and repair tool package, and/or the version number of the artificial intelligence-based front-end code detection and repair tool, and/or a package serving as a global object, and/or an application dependent attribute dependences in a package json which the installed package is written, and/or a development environment dependent attribute devdependences in a package json which the installed package is written, and/or an equivalent dependent attribute peerdependences in a package json which the installed package is written, and/or an optional dependent attribute optionaldependences in a package json which the installed package is written, and/or a package dependent attribute bundlenderdences in a package json which the installed package is written.
Optionally, the downloading of the artificial intelligence-based front-end code detection and repair tool may also be performed by directly specifying a root path of the front-end item in a parameter in the install command without switching to the root path of the front-end item in the command line tool.
Optionally, a relatively primary detection configuration and a relatively primary repair configuration are set by default in the artificial intelligence-based front-end code detection and repair tool, so that the method can be used for detecting and repairing the code of the front-end project when the first configuration file cannot be downloaded; meanwhile, the detection configuration and the repair configuration may also be performed by creating the first configuration file in the front-end item, and a relative path of the first configuration file in the front-end item or an absolute path in the computer device 102 after the configuration is completed will be saved in the global configuration file package.
S202, searching and analyzing the first configuration file according to the global configuration file, and generating a second configuration file by combining the global configuration information of the front-end project in the global configuration file;
in some embodiments, the step of searching for and analyzing the first configuration file according to the global configuration file package.json, and generating a second configuration file by combining the global configuration information of the front-end item in the package.json includes:
json finds the location path of the first configuration file in the global configuration file package;
json finds the software library referenced by the front-end project in the global configuration file package;
generating a second configuration file, generating a configuration rule according to the content of the first configuration file and a predefined configuration method, and storing the configuration rule in the second configuration file;
searching whether a target tool library required to be used by the escape target grammar specification exists in the software library; if the front-end item exists, configuring the front-end item in the second configuration file to support the target grammar specification, and if the front-end item does not exist, configuring the front-end item in the second configuration file to not support the target grammar specification.
In the present embodiment, ECMAScript6.0 syntax specification is explained as a target syntax specification; meanwhile, the babel tool library will be described as a target tool library.
Wherein babel is a software tool library that translates code written using the ECMAScript 5.0 syntax specification into a backwards compatible ECMAScript6.0 syntax specification so that the front-end code can run in both current and old versions of the browser or other environment.
In some embodiments, the second configuration file includes, but is not limited to, the following configuration content:
1) whether the ECMAScript6.0 grammar specification is supported or not, and the default setting is yes;
2) whether the ECMAScript6.0 grammar specification is detected to be correctly used or not, and the default setting is yes;
3) whether errors of the ECMAScript6.0 grammar specification are repaired or not is set to be no by default;
4) whether an encapsulated ajax request mode exists or not is set as no by default;
5) whether a cache processing method after encapsulation exists or not is set to be negative by default;
6) whether the var variable declares is detected or not, and the default setting is yes;
7) whether recursive calls are detected or not, and setting as yes by default;
8) and a white list file list is set as an empty list by default.
The global profile package json includes a dependency library already used in the front-end item, a dependency library only supporting the ECMAScript6.0 syntax specification exists in the dependency library, and a dependency library whether the global profile package json includes the ECMAScript6.0 syntax specification can be used as a basis for determining whether the configuration content supports the ECMAScript6.0 syntax specification.
It is to be noted that it is a reasonable setting that whether the ECMAScript6.0 syntax specification is supported in the configuration content is set to no, but whether the ECMAScript6.0 syntax specification is detected in the configuration content is set to yes; because support for a newer ECMAScript6.0 grammar specification is not added to some front-end projects which are relatively long, if a developer writes new code in the code of the front-end project by using the ECMAScript6.0 grammar specification, the new code cannot be normally executed in browser software with a lower version, and even other unknown serious errors occur; the arrangement mode provided by the embodiment can avoid the error.
In some embodiments, said detecting proper use of the ECMAScript6.0 grammar specification in said configuration content is set to no, and said detecting errors in the ECMAScript6.0 grammar specification and said detecting var variable declarations in said configuration content are both set to no; because errors of the ECMAScript6.0 grammar specification do not need to be repaired after the correct use of the ECMAScript6.0 grammar specification is not detected; because the var variable declaration is characteristic of the ECMAScript6.0 grammar specification, it is not necessary to detect the var variable declaration after not detecting proper use of the ECMAScript6.0 grammar specification.
For a large number of current front-end engineering projects, the largest difference is whether the ECMAScript6.0 grammar specification is supported, the largest difference in the configuration content is placed in the first item, and the existing front-end engineering projects are better supported, so that the method can be used for carrying out code detection and repair on the front-end projects which do not support the ECMAScript6.0 grammar specification, the problem of incompatibility and/or use is avoided, and seamless introduction and use are realized.
S203, detecting the codes in the front-end project according to the second configuration file and a predefined detection method, and repairing the codes in the front-end project according to the second configuration file and a predefined repair method;
in some embodiments, the step of detecting the code in the front-end item according to the second configuration file and a predefined detection method specifically includes:
when the front-end item is configured in the second configuration file and does not support the ECMAScript6.0 grammar specification, judging that a code using the ECMAScript6.0 grammar specification in the front-end item is an error code;
when the front-end item is configured in the second configuration file to support the ECMAScript6.0 grammar specification, if the front-end item does not contain a babel tool library required to be used by the escape ECMAScript6.0 grammar specification, throwing out first abnormal information; and if the front-end item contains a babel tool library required to be used by the escape ECMAScript6.0 grammar specification, detecting the code content according to the predefined detection method.
In some embodiments, if the front-end item includes a babel tool library required to be used by the escape ECMAScript6.0 syntax specification, the step of checking the code content according to the predefined checking method includes:
converting the code content into an AST syntax tree using an AST conversion library;
and analyzing the AST syntax tree by using the predefined detection method.
Wherein, AST (abstract Syntax Tree) is an abstract representation of the Syntax structure of the source code, which represents the Syntax structure of the programming language in the form of tree, and each node on the tree represents a structure in the source code; the method for generating the AST syntax tree is not described herein.
Optionally, the detecting the codes in the front-end project according to the second configuration file and the predefined detecting method, and the repairing the codes in the front-end project according to the second configuration file and the predefined repairing method may be that a single thread performs the detecting process first and then performs the repairing process, and may also perform the detecting process and the repairing process simultaneously after performing reasonable setting by using multiple threads, so as to improve the efficiency of detecting and repairing the entire codes, and the method of how to divide the process performed by the single thread into multiple threads to perform in parallel is not described herein.
In some embodiments, the method for detecting whether the front-end item supports the ECMAScript6.0 syntax specification differs as follows:
wherein, for the front-end item configured with a syntax that does not support ECMAScript6.0 syntax specification, the detected content includes the following content:
1) detecting an arrow function; detecting that a code block of { } is existed in the code of the front-end item, if the detection is failed, an error code exists;
2) detecting an asynchronous callback function; detecting that keywords of 'premium', 'async' and 'await' exist in the codes of the front-end items, if the detection is failed, an error code exists;
3) detecting variable declarations; detecting that the key words of 'let' and 'const' exist in the code of the front-end item, if the key words of 'let' and 'const' do not pass the detection, and an error code exists;
4) detecting an array method; if the keywords of 'from', 'find' and 'findIndex' exist in the codes matching the front-end item, the detection is failed, and an error code exists.
For the front-end item configured to support the ECMAScript6.0 syntax specification, the following detection contents are firstly executed:
1) json is configured with a base/core library; if the unconfigured detection does not pass;
2) json is configured with a babel/preset-env library; if not, the detection is not passed.
Wherein, if the front-end item is configured with the front-end item supporting the ECMAScript6.0 syntax specification, and the global profile package json is configured with a babel/core library and a babel/preset-env library, the following detection contents are continued:
1) detecting a const variable; when two or more than two identical const variables exist in a single front-end project code file, or the variable value is modified after the const variable is declared, the detection is failed, and an error code exists;
2) using this keyword detection in an arrow function; if this keyword is searched in the AST syntax tree analyzed by the arrow function, the detection is failed and an error code exists;
3) detecting the use of async/await; determining a function grammar block with an awake keyword in the AST grammar tree, if the index does not contain the async keyword before the function application, detecting that the function grammar block does not pass and an error code exists;
4) detecting absence of new keywords in an instantiated Class; in the AST syntax tree, judging whether an executed function contains a structural function class or not by an instanceof method, if so, continuously detecting whether a new keyword is contained in the front of a function name when the function is called, and if not, detecting that the function does not pass and an error code exists;
5) variable declaration non-use detection; and detecting that the declared variable exists in the code content, and judging that the detection fails and an error code exists if the operations such as reference, splicing, operation, modification and the like are not performed on the variable.
The babel/core is a core code library for realizing functions of a babel software tool library, the babel/preset-env is a translation rule library for converting an ECMAScript 5.0 grammar specification into an ECMAScript6.0 grammar specification realized by the babel software tool library, and one of the two libraries, namely the babel/core and the babel/preset-env, can not pass detection if the two libraries are lacked.
The variable declared by the const key is equivalent to a constant declared, repeated definition is not allowed or definition is defined and then modified in the ECMAScript6.0 grammar specification, and for the repeatedly declared const variable, because it cannot be clear whether a developer wants to modify the variable or incorrectly declares the same variable name, the second abnormal information is not repaired and thrown out; the arrow function is different from other types of functions, the this keyword defined in the arrow function is directed to the outer layer of the arrow function, but not to the arrow function itself, and a developer can be confused with the use method of other types of functions, so that the value judgment of the this keyword is abnormal; for the use of the await key words, the use must be carried out in the function decorated by the async key words, otherwise, the code reports an error in the execution process; the Class modified by the Class key is essentially a function, a developer can realize the Class by calling only when needing to instantiate the Class, and a new key is not added in front of the Class, so that only partial code is executed in the actual execution process, and the Class is not completely instantiated.
In some embodiments, the following detection is also performed on the code file of the front-end project:
1) detecting whether an encapsulated ajax request mode exists; if the configuration content is set to have secondary packaging on the ajax request mode, when detecting that the code content contains a code which directly uses $, the ajax or axios grammar to carry out interface request, throwing out second abnormal information, wherein the specific content of the second abnormal information is that the interface request code is not used normally, and prompting the file name, the storage path and the error code line number of the file where the error code is located;
2) detecting whether a packaged cache processing method exists; if the packaged cache processing method is set in the configuration content, when the code content is detected to contain localStorage keywords, judging that a developer uses an original browser cache operation method, and throwing out the second abnormal information;
3) detection is declared using the var variable; if the configuration content is provided with a syntax specification supporting ECMAScript6.0 and the code content is detected to contain a variable declared by a var keyword, the second abnormal information is thrown out;
4) detecting that use of recursive calls is prohibited; and if the configuration content sets that the recursive call is prohibited from being used, and a function in the code content contains the function call with the same name as the current function, and the recursive call is determined to be used, throwing the second abnormal information.
The method comprises the following steps that an original ajax request of a front-end project is divided into two modes, one mode is to carry out interface request through a $. ajax function of a jquery library, the other mode is to carry out interface request through an axios library, and if the ajax request mode is packaged for the second time in the project, codes for carrying out the interface request by directly using $. ajax or axios grammar should not be included; the front-end project basically uses a localStorage method of a browser to store and read the cache, so if the cache method of the data is packaged secondarily in the front-end project, a developer must use the cache storage and reading method of secondary packaging to write codes, and no localStorage keyword should appear; because the var keyword is a variable declaration method before the birth of the ECMAScript6.0 grammar specification, but the var keyword has the problems of variable lifting, temporary dead zones and the like, if the front-end item already supports the ECMAScript6.0 grammar specification, a let or a const keyword is used for performing variable declaration operation; finally, because the recursive call is not used properly, the memory leakage is easily caused, and the front-end item is directly crashed, so the recursive call is not used in the item.
In some embodiments, the detecting the code in the front-end item according to the second configuration file and a predefined detection method, and the repairing the code in the front-end item according to the second configuration file and a predefined repair method specifically includes:
analyzing the second configuration file to obtain the configuration rule in the second configuration file;
scanning the front-end project according to the configuration rule, and acquiring code contents in files in all file directories of the front-end project;
sequentially judging whether the code content in the files under the file directory needs to be detected or not according to the configuration rules;
if the code content needs to be detected, detecting the corresponding code content according to the predefined detection method;
if the code content is detected to have error codes, judging whether the error codes need to be repaired according to the configuration rule;
and if the error code needs to be repaired, repairing the corresponding code content according to the predefined repairing method.
Wherein, the configuration content also comprises a white list file list; because in code specification detection, some special application scenes may exist and do not need to write codes according to the code specification; if a white list is not configured in the application scene, the code content cannot pass the detection; when a white list file list is configured, the code detection process cannot detect the code content of the white list file in the white list file list.
In some embodiments, after the step of repairing the corresponding code content according to the predefined repair method if the error code needs to be repaired, the method further includes:
if the detected error code can not be repaired according to the predefined repairing method, throwing out second abnormal information of the error code and interrupting the detecting and repairing process;
and receiving a correction code for the error code input by a developer, detecting the correction code according to the second configuration file and a predefined detection method, and repairing the correction code according to the second configuration file and a predefined repair method.
S204, counting detection result data and repair result data for visual display, and storing the detection result data and the repair result data;
in some embodiments, similarity matching is performed on the code content of the front-end item and an ECMAScript6.0 grammar specification by using a similarity matching algorithm in artificial intelligence to generate a first similarity matching result, and similarity matching is performed on the code content of the front-end item and historical error codes in a preset typical error example and detection result to generate a second similarity matching result; the result of the first similarity match is that the front-end item conforms to reference data of the ECMAScript6.0 grammar specification; the second similarity matching result can help developers to find more suspected error codes for further analysis; the first similarity matching result and the second similarity matching result can be used as reference data for judging the code quality and maintainability of the front-end item.
Optionally, a skilled technician has a higher level of authority on the front-end project, can label and change the detection result and the repair result, and perform manual intervention on the first similarity matching result and the second similarity matching result, so as to ensure that the detection and repair of the code content of the front-end project are more accurate, and ensure that the first similarity matching result and the second similarity matching result generated after the similarity matching algorithm is run can more accurately reflect the code quality and maintainability of the front-end project.
In the process of detecting and repairing the front-end item, if the first abnormal information or the second abnormal information is thrown out, the detection and repair process is interrupted, and at the moment, the detected result data and the repaired result data are visually displayed, so that the quality condition of the current front-end code is conveniently analyzed; meanwhile, a time period can be selected according to the time node when the detection and repair process is interrupted, and statistics of the detection and repair conditions of the front-end items in the selected time period can be checked.
S205, obtaining a code submission history of a developer of the front-end project, matching the code submission history with the detection result data and the repair result data, obtaining information of a submitter of an error code, and sending the information to a related person of the front-end project.
Wherein the code submission history is obtained via a version management tool, the version management tool including but not limited to: git, SVN (Subversion), CVS (Current Versions System), and Mercurial.
In some embodiments, the step of obtaining the code submission history of the developer of the front-end project, matching the code submission history with the detection result data and the repair result data, and obtaining the submitter information of the error code and sending the submitter information to the associated person of the front-end project specifically includes:
acquiring a code submission history of a developer of the front-end project;
according to the error codes in the detection result data, the submitting personnel information of the error codes is searched in the code submitting historical record;
searching the repair result data of the error code in the repair result data, and grading the error degree of the error code according to the repair result data;
and sending the error code, the repair result data, the submitting personnel information and the error degree to the related personnel of the front-end project in a grading manner according to a predefined mail sending rule.
Wherein the error level of the error code comprises: general errors, fatal errors, and particularly fatal errors; the error code segment is classified as a general error if it has been automatically repaired, as a serious error if it has been repaired manually by a developer, and as a particularly serious error if it has not been repaired.
Optionally, it is to be particularly pointed out that the code of the front-end project is not only stored in the personal computer of the developer, but also stored in a code server, that is, the artificial intelligence based front-end code checking and repairing method provided in this embodiment may be executed not only on the personal computer of the developer, but also on the code server; the method for checking and repairing the front-end code based on the artificial intelligence is executed on a personal computer of a developer, so that the developer can be helped to better further standardize the code before the written code is submitted to the code server and eliminate errors in the code; the front-end code checking and repairing method based on artificial intelligence is executed in the code server, the latest codes submitted by all developers are detected and repaired, meanwhile, the formed statistical information is more comprehensive, the similarity matching algorithm of the artificial intelligence also occupies more hardware resources during the operation, and the problem of insufficient performance of personal computers of the developers can be effectively relieved by placing the operation of the similarity matching algorithm at the server side.
The embodiment provides an artificial intelligence based front-end code checking and repairing method, the code content of a front-end project is detected and repaired according to a preset rule and a predefined detection method and repair method, so that the codes in the front-end project are more in accordance with the specification, the quality and maintainability of the codes are further improved, the detection and repair execution result is analyzed by using a similarity matching algorithm in artificial intelligence, the detection and repair result is manually intervened and corrected by using skilled technicians, the detection and repair accuracy and execution efficiency are improved, the detection and repair result can be graphically displayed, and the detection and repair result data is used as data support for other management work.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
In some embodiments, an artificial intelligence based front-end code detection and repair apparatus 30 is provided, and the artificial intelligence based front-end code detection and repair apparatus 30 corresponds to the artificial intelligence based front-end code detection and repair method in the above embodiments one to one. As shown in fig. 3, the apparatus 30 for artificial intelligence based front-end code detection and repair includes a first configuration file obtaining module 301, a second configuration file generating module 302, a detection and repair module 303, a result counting module 304, and a sending module 305. The functional modules are explained in detail as follows:
a first configuration file obtaining module 301, configured to obtain a first configuration file into a front-end project, and store a location path for storing the first configuration file into a global configuration file of the front-end project;
a second configuration file generating module 302, configured to search and analyze the first configuration file according to the global configuration file, and generate a second configuration file in combination with the global configuration information of the front-end project in the global configuration file;
a detection and repair module 303, configured to detect a code in the front-end item according to the second configuration file and a predefined detection method, and repair the code in the front-end item according to the second configuration file and a predefined repair method;
a result counting module 304, configured to count detection result data and repair result data for visual display, and store the detection result data and the repair result data;
a sending module 305, configured to obtain a code submission history of a developer of the front-end project, match the code submission history with the detection result data and the repair result data, obtain information of a submitter of an error code, and send the information to a relevant employee of the front-end project.
The second configuration file generating module 302 further includes the following sub-modules:
a file path search sub-module, configured to search the location path of the first configuration file in the global configuration file;
the software library query submodule is used for searching the software library referenced by the front-end project in the global configuration file;
the file generation submodule is used for generating a second configuration file, generating a configuration rule according to the content of the first configuration file and a predefined configuration method and storing the configuration rule into the second configuration file;
the grammar specification judging submodule is used for searching whether a target tool library which is required to be used by the escape target grammar specification exists in the software library; if the front-end item exists, configuring the front-end item in the second configuration file to support the target grammar specification, and if the front-end item does not exist, configuring the front-end item in the second configuration file to not support the target grammar specification.
The detection and repair module 303 further includes the following sub-modules:
a syntax specification support judgment sub-module, configured to, when the front-end item configured in the second configuration file does not support the target syntax specification, judge that a code using the target syntax specification in the front-end item is an error code;
a syntax specification exception judgment sub-module, configured to, when the front-end item is configured in the second configuration file to support the target syntax specification, throw out first exception information if the front-end item does not include a target tool library that is required to be used by the escape target syntax specification; if the front-end item contains a target tool library required to be used by escape target grammar specification, detecting code content according to the predefined detection method;
the configuration rule obtaining sub-module is used for analyzing the second configuration file and obtaining the configuration rule in the second configuration file;
the code content acquisition sub-module is used for scanning the front-end project according to the configuration rule and acquiring the code content in the files in all the file directories of the front-end project;
the detection and repair judgment sub-module is used for sequentially judging whether the code content in the files under the file directories needs to be detected according to the configuration rules; if the code content needs to be detected, detecting the corresponding code content according to the predefined detection method; if the code content is detected to have error codes, judging whether the error codes need to be repaired according to the configuration rule; if the error code needs to be repaired, repairing the corresponding code content according to the predefined repairing method;
the second abnormal information throwing sub-module is used for throwing out the second abnormal information of the error code and interrupting the detection and repair process if the detected error code cannot be repaired according to the predefined repair method;
and the correction code detection and repair submodule is used for receiving the correction codes of the error codes input by developers, detecting the correction codes according to the second configuration file and a predefined detection method, and repairing the correction codes according to the second configuration file and a predefined repair method.
Wherein the syntax specification anomaly judgment sub-module is further configured to:
converting the code content into an AST syntax tree using an AST conversion library;
and analyzing the AST syntax tree by using the predefined detection method.
Wherein, the sending module 305 further includes the following sub-modules:
a history record obtaining submodule for obtaining a code submission history record of a developer of the front-end project;
a submitter information search sub-module which searches the submitter information of the error code in the code submission history record according to the error code in the detection result data;
the error grading submodule searches the repair result data of the error code in the repair result data and grades the error degree of the error code according to the repair result data;
and the mail sending submodule is used for sending the error code, the repair result data, the submitting personnel information and the error degree to the related personnel of the front-end project in a grading manner according to a predefined mail sending rule.
Optionally, it is to be noted that, some modules of the apparatus for detecting and repairing front-end code based on artificial intelligence may be operated in the computer device 102, or in the server 101. For example, the result statistics module 304 needs to analyze the result data to generate various statistical charts, has no strict requirement on real-time performance, and can run on the server 101 to avoid occupying too much hardware resources of the computer device 102; for example, the sending module 305 needs to use an artificial intelligence similarity matching algorithm to perform the calculation, which consumes a large amount of hardware resources, and also needs to invoke a mail sending service, which can be run on the server 101, so as to avoid excessive occupation of the hardware resources of the computer device 102.
Wherein the meaning of "first" and "second" in the above modules/units is only to distinguish different modules/units, and is not used to define which module/unit has higher priority or other defining meaning. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not explicitly listed or inherent to such process, method, article, or apparatus, and such that a division of modules presented in this application is merely a logical division and may be implemented in a practical application in a further manner.
For the specific limitations of the apparatus for detecting and repairing front-end codes based on artificial intelligence, reference may be made to the above limitations of the method for detecting and repairing front-end codes based on artificial intelligence, which are not described herein again. The modules in the artificial intelligence based front-end code detection and repair device can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In some embodiments, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing data involved in the artificial intelligence based front-end code detection and repair method. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement an artificial intelligence based front-end code detection and repair method.
In some embodiments, there is provided a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the artificial intelligence based front end code detection and repair method of the above embodiments, such as the steps S201 to S205 shown in fig. 2 and other extensions of the method and related steps. Alternatively, the processor, when executing the computer program, implements the functions of the modules/units of the artificial intelligence based front-end code detecting and repairing apparatus in the above embodiments, such as the functions of the modules 301 to 305 shown in fig. 3. To avoid repetition, further description is omitted here.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like which is the control center for the computer device and which connects the various parts of the overall computer device using various interfaces and lines.
The memory may be used to store the computer programs and/or modules, and the processor may implement various functions of the computer device by running or executing the computer programs and/or modules stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a text editing function, an image drawing function, etc.), and the like; the storage data area may store data (such as text data, image data, etc.) created according to the use of the computer program, and the like.
The memory may be integrated in the processor or may be provided separately from the processor.
In some embodiments, a computer readable storage medium is provided, on which a computer program is stored, which when executed by a processor implements the steps of the artificial intelligence based front end code detection and repair method of the above embodiments, such as the steps S201 to S205 shown in fig. 2 and extensions of other extensions and related steps of the method. Alternatively, the computer program, when executed by the processor, implements the functions of the modules/units of the artificial intelligence based front end code detection and repair apparatus in the above embodiments, such as the functions of the modules 301 to 305 shown in fig. 3. To avoid repetition, further description is omitted here.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. A front-end code detection and repair method based on artificial intelligence is characterized by comprising the following steps:
acquiring a first configuration file to a front-end project, and storing a position path for storing the first configuration file to a global configuration file of the front-end project;
searching and analyzing the first configuration file according to the global configuration file, and generating a second configuration file by combining the global configuration information of the front-end project in the global configuration file;
detecting the codes in the front-end project according to the second configuration file and a predefined detection method, and repairing the codes in the front-end project according to the second configuration file and a predefined repair method;
counting detection result data and repair result data for visual display, and storing the detection result data and the repair result data;
and acquiring a code submission history of the developer of the front-end project, matching the code submission history with the detection result data and the repair result data, acquiring the information of submitters of error codes and sending the information to the associated staff of the front-end project.
2. The artificial intelligence based front-end code detection and repair method according to claim 1, wherein the step of searching for and parsing the first configuration file according to the global configuration file, and generating a second configuration file in combination with global configuration information of the front-end item in the global configuration file comprises:
finding the position path of the first configuration file in the global configuration file;
finding the software library referenced by the front-end project in the global configuration file;
generating a second configuration file, generating a configuration rule according to the content of the first configuration file and a predefined configuration method, and storing the configuration rule in the second configuration file;
searching whether a target tool library required to be used by the escape target grammar specification exists in the software library; if the front-end item exists, configuring the front-end item in the second configuration file to support the target grammar specification, and if the front-end item does not exist, configuring the front-end item in the second configuration file to not support the target grammar specification.
3. The artificial intelligence based front-end code detection and repair method according to claim 2, wherein the step of detecting the code in the front-end project according to the second configuration file and a predefined detection method specifically comprises:
when the front-end item is configured in the second configuration file and does not support the target grammar specification, judging that a code using the target grammar specification in the front-end item is an error code;
when the front-end item is configured in the second configuration file to support the target grammar specification, if the front-end item does not contain a target tool library required to be used by the escape target grammar specification, throwing out first abnormal information; and if the front-end item contains a target tool library required to be used by the escape target grammar specification, detecting the code content according to the predefined detection method.
4. The method of claim 3, wherein if the front-end item includes a target tool library that is needed to be used by an escape target grammar specification, the step of detecting the code content according to the predefined detection method comprises:
converting the code content into an AST syntax tree using an AST conversion library;
and analyzing the AST syntax tree by using the predefined detection method.
5. The artificial intelligence based front-end code detection and repair method according to claim 2, wherein the detecting the code in the front-end project according to the second configuration file and a predefined detection method, and the repairing the code in the front-end project according to the second configuration file and a predefined repair method specifically comprises:
analyzing the second configuration file to obtain the configuration rule in the second configuration file;
scanning the front-end project according to the configuration rule, and acquiring code contents in files in all file directories of the front-end project;
sequentially judging whether the code content in the files under the file directory needs to be detected or not according to the configuration rules;
if the code content needs to be detected, detecting the corresponding code content according to the predefined detection method;
if the code content is detected to have error codes, judging whether the error codes need to be repaired according to the configuration rule;
and if the error code needs to be repaired, repairing the corresponding code content according to the predefined repairing method.
6. The artificial intelligence based front-end code detection and repair method according to claim 5, wherein after the step of repairing the corresponding code content according to the predefined repair method if the error code needs to be repaired, further comprising:
if the detected error code can not be repaired according to the predefined repairing method, throwing out second abnormal information of the error code and interrupting the detecting and repairing process;
and receiving a correction code for the error code input by a developer, detecting the correction code according to the second configuration file and a predefined detection method, and repairing the correction code according to the second configuration file and a predefined repair method.
7. The artificial intelligence based front-end code detection and repair method according to claim 6, wherein the step of obtaining a code submission history of a developer of the front-end project, matching the code submission history with the detection result data and the repair result data, obtaining submitter information of an error code, and sending the submitter information to a person associated with the front-end project specifically comprises:
acquiring a code submission history of a developer of the front-end project;
according to the error codes in the detection result data, the submitting personnel information of the error codes is searched in the code submitting historical record;
searching the repair result data of the error code in the repair result data, and grading the error degree of the error code according to the repair result data;
and sending the error code, the repair result data, the submitting personnel information and the error degree to the related personnel of the front-end project in a grading manner according to a predefined mail sending rule.
8. The utility model provides a front end code detects and prosthetic devices based on artificial intelligence which characterized in that includes:
the system comprises a first configuration file acquisition module, a first configuration file acquisition module and a second configuration file acquisition module, wherein the first configuration file acquisition module is used for acquiring a first configuration file to a front-end project and storing a position path for storing the first configuration file to a global configuration file of the front-end project;
the second configuration file generation module is used for searching and analyzing the first configuration file according to the global configuration file, and generating a second configuration file by combining the global configuration information of the front-end project in the global configuration file;
a detection and repair module, configured to detect a code in the front-end item according to the second configuration file and a predefined detection method, and repair the code in the front-end item according to the second configuration file and the predefined repair method;
the result counting module is used for counting the detection result data and the repair result data for visual display and storing the detection result data and the repair result data;
and the sending module is used for acquiring a code submission historical record of a developer of the front-end project, matching the code submission historical record with the detection result data and the repair result data, acquiring the information of submitters of error codes and sending the information to the related personnel of the front-end project.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the steps of the artificial intelligence based front end code detection and repair method according to any one of claims 1 to 7 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out the steps of the artificial intelligence based front-end code detection and repair method according to any one of claims 1 to 7.
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