CN114546876A

CN114546876A - Online programming learning auxiliary method, device, equipment and storage medium

Info

Publication number: CN114546876A
Application number: CN202210190126.4A
Authority: CN
Inventors: 刘煊
Original assignee: Beijing Gaotu Yunji Education Technology Co Ltd
Current assignee: Beijing Gaotu Yunji Education Technology Co Ltd
Priority date: 2022-02-28
Filing date: 2022-02-28
Publication date: 2022-05-27

Abstract

The invention provides an online programming learning auxiliary method, an online programming learning auxiliary device, an online programming learning auxiliary equipment and a storage medium, which can respond to preset operation of a user for a programmed program code when the user performs online programming learning, detect the program code, determine a coding error type corresponding to each abnormal programming content existing in the program code based on the coding type of the program code when the abnormal programming content is detected, and further generate a learning auxiliary plan comprising programming knowledge points aiming at the abnormal programming content and the corresponding coding error type and learning suggestions aiming at the programming knowledge points for the user, so that the learning auxiliary plan is pushed to the user. Therefore, the writing abnormal content in the program code is effectively utilized, and the learning auxiliary plan can be generated for the user in time, so that the user is assisted to perform online programming learning, the possibility of similar errors in the subsequent online programming learning is reduced, and the speed and the efficiency of the online programming learning are greatly improved.

Description

Online programming learning auxiliary method, device, equipment and storage medium

Technical Field

The disclosure relates to the technical field of computers, and in particular, to an online programming learning assistance method, apparatus, device and storage medium.

Background

With the rapid development of the internet, the network has gradually become an indispensable assistant for people, great convenience is brought to the work and life of people through the network, various application tools based on the internet are well known and used by people, people can program on line by means of application software and the like, the programming becomes more convenient, quicker and more efficient, meanwhile, the programming becomes more popular in recent years, and the acceptance of people on the programming becomes higher and higher.

However, in the programming process, if there is writing abnormal content in the written program code, the user can only know the problem in the program code and the position corresponding to the problem, and the problem user is still puzzled and unable to solve the problem actually, so that it is difficult for the user to avoid the repeated occurrence of similar problems in the subsequent programming learning process, which affects the programming learning progress of the user.

Disclosure of Invention

The embodiment of the disclosure at least provides an online programming learning auxiliary method, an online programming learning auxiliary device, online programming learning equipment and a storage medium.

The embodiment of the disclosure provides an online programming learning auxiliary method, which includes:

when a user conducts online programming learning, responding to preset operation of the user for a written program code, and detecting whether the written program code has writing abnormal content;

if the program code exists, determining the coding error type corresponding to each abnormal writing content in the program code based on the coding type of the program code;

generating a learning auxiliary plan for the user based on each abnormal compiling content and the corresponding coding error type, wherein the learning auxiliary plan comprises programming knowledge points aiming at the abnormal compiling content and the corresponding coding error type and learning suggestions aiming at the programming knowledge points;

and pushing the learning assistance plan to the user.

In an optional implementation manner, the determining, based on the encoding type of the program code, the encoding error type corresponding to each writing exception content existing in the program code includes:

determining a first error type to which writing abnormal content belongs for each writing abnormal content existing in the program code based on multiple preset basic error types in the coding category, wherein the basic error types comprise at least one of spelling errors, source code errors and syntax errors;

generating a learning assistance plan for the user based on each of the writing abnormal content and the corresponding coding error type, comprising:

generating a learning assistance plan for the user based on each of the writing exception content and the corresponding first error type.

In an optional embodiment, after the determining the first error type to which the composition exception content belongs, the method further includes:

determining a second error type to which the writing abnormal content belongs based on a plurality of content error types under the first error type;

determining content abnormal information of the abnormal compiling content based on a first error type and a second error type of the abnormal compiling content;

generating a learning assistance plan for the user based on each of the writing exception content and the corresponding first error type, comprising:

generating a learning auxiliary plan for the user based on the first error type and the second error type corresponding to each abnormal compiling content, each abnormal compiling content and corresponding content abnormal information;

wherein, when the first error type is a syntax error, the content error type includes at least one of a key error, a modifier error, a container error, and an expression error.

In an optional implementation manner, after determining, based on the encoding type of the program code, the encoding error type corresponding to each writing exception existing in the program code, the method further includes:

generating an exception analysis report for the program code based on each of the writing exception content and the corresponding encoding error type;

presenting content of the exception analysis report to the user in response to the user's review of the exception analysis report.

In an optional embodiment, the generating a learning assistance plan for the user based on each composition anomaly content and the corresponding coding error type includes:

sending each abnormal writing content and the corresponding coding error type existing in the program code to a server;

and receiving a learning auxiliary plan fed back by the server, wherein the learning auxiliary plan is generated by a matching result obtained by matching each reported abnormal compiling content and the corresponding coding error type with a plurality of preset programming knowledge points by the server.

determining account information and identity information corresponding to the user aiming at the user;

determining at least one historical writing abnormal content of the user based on the account information and the identity information corresponding to the user;

based on the at least one historical writing abnormal content, performing duplicate removal processing on each writing abnormal content existing in the program code to obtain at least one writing abnormal content after duplicate removal;

and generating a learning auxiliary plan for the user based on the at least one abnormal compiling content and the coding error type corresponding to each abnormal compiling content.

In an optional embodiment, the method further comprises:

when detecting whether the program code has the writing abnormal content, acquiring the detection time for detecting the program code;

the performing, based on the at least one historical writing abnormal content, deduplication processing on each writing abnormal content existing in the program code to obtain at least one target writing abnormal content includes:

aiming at the at least one history writing abnormal content, determining a target history abnormal content from the at least one history writing abnormal content based on a preset time interval, the detection time and the history detection time corresponding to each history writing abnormal content, wherein the interval between the history detection time and the detection time of the target history abnormal content is smaller than the preset time interval;

matching the target historical abnormal content with each writing abnormal content in the program code, and determining the writing abnormal content which is the same as the target historical abnormal content from a plurality of writing abnormal contents in the program code;

and based on the determined writing abnormal contents with the same contents, performing duplicate removal processing on each writing abnormal content in the program code to obtain at least one writing abnormal content after duplicate removal.

In an optional embodiment, in the case that it is determined that at least one history of the user authored abnormal content, the method further comprises:

screening each abnormal compiling content existing in the program code based on the at least one historical abnormal compiling content to obtain at least one high-frequency abnormal compiling content;

and generating a learning auxiliary plan for the user based on the high-frequency writing abnormal content and the corresponding coding error type.

The embodiment of the present disclosure further provides an online programming learning auxiliary device, which includes:

the code detection module is used for responding to preset operation of the user for the written program codes when the user performs online programming learning and detecting whether the written program codes have abnormal writing contents;

the type determining module is used for determining the coding error type corresponding to each abnormal writing content in the program code based on the coding type of the program code if the program code exists;

a plan generation module, configured to generate a learning auxiliary plan for the user based on each abnormal writing content and a corresponding coding error type, where the learning auxiliary plan includes a programming knowledge point for the abnormal writing content and the corresponding coding error type, and a learning suggestion for each programming knowledge point;

and the plan pushing module is used for pushing the learning auxiliary plan to the user.

In an optional implementation manner, the type determining module is specifically configured to:

the plan generation module is specifically configured to:

In an optional embodiment, the type determining module is further configured to:

the plan generation module is specifically configured to:

In an optional embodiment, the online programming learning assistance device further comprises a report generation module, and the report generation module is configured to:

In an optional implementation manner, the plan generation module is specifically configured to:

In an optional implementation manner, the code detection module is further configured to:

the plan generating module is specifically configured to, when the plan generating module is configured to perform deduplication processing on each writing abnormal content existing in the program code based on the at least one historical writing abnormal content to obtain at least one target writing abnormal content:

In an alternative embodiment, in the event that at least one history of the user is determined to write anomalous content, the plan generation module is configured to:

An embodiment of the present disclosure further provides an electronic device, including: the online programming learning auxiliary method comprises a processor, a memory and a bus, wherein the memory stores machine readable instructions executable by the processor, the processor and the memory are communicated through the bus when the electronic device runs, and the machine readable instructions are executed by the processor to execute the steps of the online programming learning auxiliary method.

The embodiment of the present disclosure further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program performs the steps in the online programming learning assistance method.

The online programming learning auxiliary method, the online programming learning auxiliary device, the online programming learning auxiliary equipment and the storage medium provided by the embodiment of the disclosure can respond to the preset operation of the user for the programmed program code when the user performs online programming learning, and detect whether the programmed program code has abnormal programming content; if the program code exists, determining the coding error type corresponding to each abnormal writing content in the program code based on the coding type of the program code; generating a learning auxiliary plan for the user based on each abnormal compiling content and the corresponding coding error type, wherein the learning auxiliary plan comprises programming knowledge points aiming at the abnormal compiling content and the corresponding coding error type and learning suggestions aiming at the programming knowledge points; and pushing the learning assistance plan to the user.

Therefore, after the abnormal compiling content in the program code is detected, the coding error type corresponding to the abnormal compiling content can be determined, so that the programming knowledge points aiming at the abnormal compiling content and the corresponding coding error type and the learning suggestions aiming at all the programming knowledge points can be determined in time based on the abnormal compiling content and the corresponding coding error type, and a learning auxiliary plan can be further generated for the user, so that the user is assisted in online programming learning, the abnormal compiling content in the program code is effectively utilized, and the learning auxiliary plan suitable for the user is determined by analyzing and summarizing the abnormal compiling content, so that the possibility of occurrence of similar errors in the subsequent online programming learning is reduced, and the speed and the efficiency of the online programming learning are greatly improved.

In order to make the aforementioned objects, features and advantages of the present disclosure more comprehensible, preferred embodiments accompanied with figures are described in detail below.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the technical aspects of the disclosure.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings required for use in the embodiments will be briefly described below, and the drawings herein incorporated in and forming a part of the specification illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the technical solutions of the present disclosure. It is appreciated that the following drawings depict only certain embodiments of the disclosure and are therefore not to be considered limiting of its scope, for those skilled in the art will be able to derive additional related drawings therefrom without the benefit of the inventive faculty.

FIG. 1 is a flow chart illustrating an online programming learning assistance method provided by an embodiment of the present disclosure;

FIG. 2 is a flow chart illustrating a method for determining a coding error type in an online programming learning assistance method provided by an embodiment of the disclosure;

FIG. 3 illustrates a flow chart of another online programming learning assistance method provided by embodiments of the present disclosure;

FIG. 4 is a schematic diagram of an online programming learning aid provided by an embodiment of the disclosure;

fig. 5 illustrates a second schematic diagram of an online programming learning assistance device provided in the embodiment of the present disclosure;

fig. 6 shows a schematic diagram of an electronic device provided by an embodiment of the present disclosure.

Detailed Description

To make the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the technical solutions in the embodiments of the present disclosure will be described clearly and completely with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, not all of the embodiments. The components of the embodiments of the present disclosure, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present disclosure, presented in the figures, is not intended to limit the scope of the claimed disclosure, but is merely representative of selected embodiments of the disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the disclosure without making creative efforts, shall fall within the protection scope of the disclosure.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.

The term "and/or" herein merely describes an associative relationship, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, C, and may mean including any one or more elements selected from the group consisting of A, B and C.

Research shows that in the programming process, if the programmed program code has abnormal programming content, the problem in the program code and the position corresponding to the problem are usually displayed for a user, however, the user can only know the problem in the program code, the problem user still has confusion, the problem cannot be actually solved, and further, the user is difficult to avoid repeated similar errors in the subsequent programming learning process to influence the programming learning progress of the user, therefore, the user can only ask other people with programming experience for teaching, but the method has a complex process and consumes a large amount of time. Therefore, how to perform online programming learning aided planning on the user based on the writing abnormal content after determining the writing abnormal content in the program code becomes a problem to be solved urgently.

Based on the research, the present disclosure provides an online programming learning auxiliary method, which may detect whether there is writing abnormal content in a program code in response to a preset operation of a user for the written program code when the user performs online programming learning; if the program code exists, determining the coding error type corresponding to each abnormal writing content in the program code based on the coding type of the program code; generating a learning auxiliary plan for the user based on each abnormal compiling content and the corresponding coding error type, wherein the learning auxiliary plan comprises programming knowledge points aiming at the abnormal compiling content and the corresponding coding error type and learning suggestions aiming at the programming knowledge points; and pushing the learning assistance plan to the user.

The above-mentioned drawbacks are the results of the inventor after practical and careful study, and therefore, the discovery process of the above-mentioned problems and the solutions proposed by the present disclosure to the above-mentioned problems should be the contribution of the inventor in the process of the present disclosure.

To facilitate understanding of the present embodiment, first, a detailed description is given of an online programming learning auxiliary method disclosed in the present embodiment, where an execution main body of the online programming learning auxiliary method provided in the present embodiment may be an online programming learning auxiliary device, for example, the online programming learning auxiliary method may be executed by a terminal device or a server or other processing devices, where the terminal device may be a User Equipment (UE), a mobile device, a User terminal, a Personal Digital Assistant (PDA), a handheld device, and the like. In some possible implementations, the online programming learning assistance method may be implemented by a processor invoking computer readable instructions stored in a memory.

Referring to fig. 1, fig. 1 is a flowchart illustrating an online programming learning assistance method according to an embodiment of the disclosure. As shown in fig. 1, an online programming learning assistance method provided by an embodiment of the present disclosure includes:

s101: when a user conducts online programming learning, whether programming abnormal content exists in the program code is detected in response to preset operation of the user on the programmed program code.

In this step, when the user performs online programming learning, it may be detected in real time whether a preset operation of the user for the written program code is received, and in a case that it is determined that the preset operation of the user for the written program code is received, the program code may be detected in response to the preset operation of the user for the written program code, so as to determine whether there is writing abnormal content in the program code.

Here, the user may write a program code in a course listening process, write a program code in a homework process, write a program code in a usual practice process, and the like in the process of learning programming through the internet, which is not limited herein.

The preset operation of the user for the written program code may include a submission operation, a running operation, a detection operation, and the like of the user for the written program code. Accordingly, in a learning interface in which a user performs online programming learning, a submit button, a run button, a check button, and the like may be provided. Illustratively, in the event that the user is detected to click the submit button, it is determined that the program code written by the user is detected.

When the program code has writing abnormal content, each abnormal content corresponds to an abnormal occurrence point, and when the abnormal occurrence point is detected and the occurrence position of the abnormal occurrence point is located, it is determined that the writing abnormal content exists in the program code.

S102: and if so, determining the coding error type corresponding to each abnormal writing content in the program code based on the coding type of the program code.

In this step, when it is detected that the program code has the writing abnormal content, the encoding type of the program code may be determined first, so that the encoding error type corresponding to each writing abnormal content existing in the program code may be determined based on the encoding type.

Here, the encoding type of the program code may include a writing language type of the program code, such as a C language, a C + + language, a Java language, a Python language, and the like, and may further include a device system used for writing the program code, such as an Android (Android) system, an apple (iOS) system, and the like.

S103: and generating a learning auxiliary plan for the user based on each abnormal compiling content and the corresponding coding error type, wherein the learning auxiliary plan comprises programming knowledge points aiming at the abnormal compiling content and the corresponding coding error type and learning suggestions aiming at the programming knowledge points.

In this step, when determining the coding error type corresponding to each abnormal writing content existing in the program code, based on each abnormal writing content and the corresponding coding error type, the programming knowledge point corresponding to the coding error type and the learning suggestion for each programming knowledge point may be determined, so as to generate a learning assistance plan for the user.

It can be understood that different programming languages and programming specifications of program codes corresponding to different device systems are different, and coding error types corresponding to different programming specifications are also different, so that the coding error types under the coding types can be determined only by determining the coding types of the program codes.

Therefore, in some possible embodiments, the determining, based on the encoding type of the program code, the encoding error type corresponding to each writing exception existing in the program code includes:

In this step, when the encoding type of the program code is determined, a first error type to which the writing abnormal content belongs may be determined for each writing abnormal content existing in the program code based on a plurality of preset basic error types in the encoding type, and when the first error type to which the writing abnormal content belongs is determined, a learning auxiliary plan may be generated for the user based on each writing abnormal content and the corresponding first error type.

Here, the base error type includes at least one of a spelling error, a source code error, and a syntax error. It is understood that the spelling error refers to a case that the spelling error does not conform to the program code writing specification corresponding to the encoding type, the source code error refers to an error caused by calling program codes written by other users and/or program codes in a system template, and the syntax error refers to an error which does not conform to the syntax requirement in the program codes written by the users.

For example, referring to fig. 2, fig. 2 is a flowchart of a method for determining a coding error type in an online programming learning auxiliary method provided by an embodiment of the present disclosure, as shown in fig. 2, when it is detected that writing abnormal content exists in the program code, a first error type to which the writing abnormal content belongs is determined for each writing abnormal content existing in the program code based on multiple preset basic error types in the coding category, so as to obtain at least one of a spelling error, a source code error, and a syntax error.

Further, under the condition that the first error type of the writing abnormal content is determined, in order to generate a learning auxiliary plan for a user in a subsequent targeted manner, the writing abnormal content can be further analyzed.

Specifically, in some possible embodiments, after the determining the first error type to which the composition abnormal content belongs, the method further includes:

In this step, after determining the first error type to which the abnormal composition content belongs, the second error type to which the abnormal composition content belongs may be determined based on a plurality of content error types under the first error type, and in a case where the second error type to which the abnormal composition content belongs is determined, the content abnormality information of the abnormal composition content may be determined based on the first error type and the second error type to which the abnormal composition content belongs, so that a learning assistance plan may be generated for the user based on the first error type and the second error type corresponding to each abnormal composition content, and each abnormal composition content and the corresponding content abnormality information.

Here, when the first error type is a syntax error, the content error type includes at least one of a key error, a modifier error, a container error, and an expression error.

Further, when the first error type is a syntax error, the content error type may further include a process communication error, a thread related error, a conditional expression error, a loop expression error, a question mark expression error, a memory error, an algorithm error, and the like.

Accordingly, when the first error type is a spelling error, the content error type may include a big-small writing error, a first letter error, a symbol error, a Chinese-English format error, a space usage error, and the like.

And the content exception information corresponding to the abnormal compiling content is an error presenting mode after determining a corresponding first error type and a second error type according to the abnormal compiling content.

Illustratively, for the composition exception content whose encoding type is Java language, the content exception information may be, for example, arithmetic exception (arithmetric exception), null pointer exception (nulloperintexexpecection), type forced transition exception (classscastexception), array negative subscript exception (negativearray exception), file end exception (EOFExecption), file not found exception (filenotfound exception), security violation exception (security principle exception), string transition to digital exception (numberformat exception), array subscript crossing exception (arrayindextoutpoumpboudouxponexpecection), operational database exception (SQLExecption), input output exception (ioxexption), method not found exception (noshoxedpecection), cross subscript exception (indexponexponexponexponexponexponexponexponexponection), system exception (creating system), system negative exception (creating exception) and network error (network error exception (network error), etc.

Further, in order to generate a learning assistance plan in a case where each content of the programming exception and the corresponding type of the coding error existing in the program code are determined, in some possible embodiments, the generating a learning assistance plan for the user based on each content of the programming exception and the corresponding type of the coding error includes:

In this step, under the condition that each abnormal compiling content and a corresponding coding error type existing in the program code are determined, each abnormal compiling content and a corresponding coding error type existing in the program code are sent to a server, and after the server matches each abnormal compiling content and the corresponding coding error type, learning auxiliary planning fed back by the server is received.

It is understood that the user may use the user terminal for online programming learning, and the user terminal may be communicatively connected to the server.

The server is capable of matching each reported abnormal compiling content and the corresponding coding error type with the preset programming knowledge points to generate a matching result, wherein the matching result comprises the programming knowledge points corresponding to the coding error type, and a learning auxiliary plan can be generated based on the matching result.

Optionally, in another embodiment, the learning assistance plan may be generated by matching, at the user terminal, each of the writing exception content and the corresponding coding error type existing in the program code with a plurality of preset programming knowledge points.

In order to better assist the user in online programming learning, abnormal contents can be written in combination with the history of the user when the learning auxiliary plan is generated, so that the generated learning auxiliary plan is more comprehensive and detailed.

Accordingly, in some possible embodiments, the generating a learning assistance plan for the user based on the respective composition anomaly content and the corresponding encoding error type includes:

It can be understood that, in the process of online programming learning by a user, even though the user may use multiple device terminals to perform online programming learning, account information and identity information used when the user logs in are the same for the user, and then content corresponding to the same account information and identity information may be synchronously displayed in the multiple device terminals.

Therefore, for the user, account information and identity information corresponding to the user may be determined first, so that at least one historical writing abnormal content of the user is determined based on the account information and the identity information corresponding to the user, in practical application, the historical writing abnormal content and the writing abnormal content existing in the program code may be repeated, further, each writing abnormal content existing in the program code may be subjected to deduplication processing based on the at least one historical writing abnormal content, the at least one writing abnormal content after deduplication is obtained, and a learning auxiliary plan is generated for the user based on the at least one writing abnormal content and a coding error type corresponding to each writing abnormal content.

It can be understood that, in order to improve the practicability and effectiveness of the learning auxiliary plan, the writing abnormal content may be subjected to deduplication processing, so as to increase the speed of generating the learning auxiliary plan.

Furthermore, in the process of learning programming, the learning progress and the knowledge point mastering degree of a user are different at different learning times, the writing abnormal content and the corresponding coding error type in the program code written at different learning times are different, and the history writing abnormal content and the corresponding coding error type which are too long away from the current time may not have reference value for the current learning, so that the at least one history writing abnormal content can be screened after the at least one history writing abnormal content of the user is obtained.

Accordingly, in some possible embodiments, the method further comprises:

the performing, based on the at least one historical writing abnormal content, deduplication processing on each writing abnormal content existing in the program code to obtain at least one target writing abnormal content, including:

In this step, when detecting whether there is writing abnormal content in the program code, the detection time for detecting the program code may be obtained at the same time, so that, for the at least one historical writing abnormal content, a target historical abnormal content may be screened from the at least one historical writing abnormal content based on a preset time interval, the detection time, and a historical detection time corresponding to each historical writing abnormal content, where an interval between the historical detection time of the target historical abnormal content and the detection time is smaller than the preset time interval.

Illustratively, the detection time for detecting the program code is five days in a month, and the preset time interval is three days, so that the history writing abnormal content after the history detection time is two days in a month can be determined from the at least one history writing abnormal content, that is, the target history abnormal content is determined.

Then, the target history abnormal content and each writing abnormal content existing in the program code may be matched, whether the writing abnormal content identical to the target history abnormal content exists in a plurality of writing abnormal contents existing in the program code is detected, and when the writing abnormal content identical to the target history abnormal content exists, each writing abnormal content existing in the program code may be subjected to deduplication processing based on the determined writing abnormal content identical to the content, so as to obtain at least one writing abnormal content after deduplication.

Optionally, in order to improve the generation efficiency of the learning auxiliary plan, based on at least one historical writing abnormal content of the user and the writing abnormal content existing in the program code, a ranking list of the writing abnormal content for the user may be generated, so as to determine a high-frequency writing abnormal content in the ranking list of the writing abnormal content, and generate the learning auxiliary plan for the user based on the high-frequency writing abnormal content and a corresponding encoding error type.

Specifically, in some possible embodiments, in the case where it is determined that at least one history of the user wrote abnormal content, the method further includes:

In this step, under the condition that at least one history writing abnormal content of the user is determined, each writing abnormal content existing in the program code may be screened according to the at least one history writing abnormal content and in combination with a preset error frequency, at least one high-frequency writing abnormal content meeting the preset error frequency is determined from the writing abnormal contents existing in the program code, and then a learning auxiliary plan is generated for the user based on the high-frequency writing abnormal content and a corresponding encoding error type.

S104: and pushing the learning assistance plan to the user.

In this step, after generating the learning aid plan, the learning aid plan may be pushed to the user.

Furthermore, a programming wrong-choice exercise book can be correspondingly generated for the user based on the learning suggestion included in the learning auxiliary planning, and related exercises, examinations and courses can be pushed for the user.

Optionally, programming knowledge points of the same coding error type and learning suggestions for each programming knowledge point can also be pushed for the user.

Optionally, for the user, other coding error types corresponding to other users except the user may be collected, so as to determine programming knowledge points for the other coding error types and learning suggestions for each programming knowledge point, and the learning suggestions are pushed to the user to assist the user in performing online programming learning.

The online programming learning auxiliary method provided by the embodiment of the disclosure can respond to the preset operation of the user on the written program code when the user performs online programming learning, and detect whether the written program code has writing abnormal content; if the program code exists, determining the coding error type corresponding to each abnormal writing content in the program code based on the coding type of the program code; generating a learning auxiliary plan for the user based on each abnormal compiling content and the corresponding coding error type, wherein the learning auxiliary plan comprises programming knowledge points aiming at the abnormal compiling content and the corresponding coding error type and learning suggestions aiming at the programming knowledge points; and pushing the learning assistance plan to the user.

Referring to fig. 3, fig. 3 is a flowchart of another online programming learning assistance method according to an embodiment of the disclosure. As shown in fig. 3, an online programming learning assistance method provided by an embodiment of the present disclosure includes:

s301: when a user conducts online programming learning, whether programming abnormal content exists in the program codes is detected in response to preset operation of the user on the programmed program codes.

S302: and if so, determining the coding error type corresponding to each abnormal writing content in the program code based on the coding type of the program code.

S303: and generating a learning auxiliary plan for the user based on each abnormal compiling content and the corresponding coding error type, wherein the learning auxiliary plan comprises programming knowledge points aiming at the abnormal compiling content and the corresponding coding error type and learning suggestions aiming at the programming knowledge points.

S304: and pushing the learning assistance plan to the user.

The descriptions of step S301 to step S304 may refer to the descriptions of step S101 to step S104, and the same technical effect and the same technical problem can be achieved, which are not described herein again.

S305: generating an exception analysis report for the program code based on the respective write exception content and the corresponding type of coding error.

In this step, when determining the coding error type corresponding to each abnormal writing content existing in the program code, an abnormality analysis report for the program code may be generated based on each abnormal writing content and the corresponding coding error type.

The exception analysis report may include a detection time for detecting the program code, contents of each writing exception existing in the program code, and a corresponding type of encoding error.

S306: presenting content of the exception analysis report to the user in response to the user's review of the exception analysis report.

In this step, in the case of generating the abnormality analysis report, the content of the abnormality analysis report may be presented to the user in response to the user's view of the abnormality analysis report.

When the content of the abnormal analysis report is displayed for the user, a report text corresponding to the abnormal analysis report can be displayed, and a report audio/video and the like corresponding to the abnormal analysis report can be played.

It will be understood by those skilled in the art that in the method of the present invention, the order of writing the steps does not imply a strict order of execution and any limitations on the implementation, and the specific order of execution of the steps should be determined by their function and possible inherent logic.

Based on the same inventive concept, the embodiment of the present disclosure further provides an online programming learning auxiliary device corresponding to the online programming learning auxiliary method, and as the principle of solving the problem of the device in the embodiment of the present disclosure is similar to the online programming learning auxiliary method in the embodiment of the present disclosure, the implementation of the device may refer to the implementation of the method, and the repeated parts are not described again.

Referring to fig. 4 and fig. 5, fig. 4 is a first schematic diagram of an online programming learning assistance device according to an embodiment of the disclosure, and fig. 5 is a second schematic diagram of an online programming learning assistance device according to an embodiment of the disclosure. As shown in fig. 4, an online programming learning assistance device 400 provided by an embodiment of the present disclosure includes:

the code detection module 410 is used for responding to preset operation of a user on a written program code when the user performs online programming learning, and detecting whether the written program code has writing abnormal content;

a type determining module 420, configured to determine, based on the encoding type of the program code, an encoding error type corresponding to each writing exception content existing in the program code;

a plan generating module 430, configured to generate a learning auxiliary plan for the user based on each abnormal writing content and the corresponding coding error type, where the learning auxiliary plan includes programming knowledge points for the abnormal writing content and the corresponding coding error type, and a learning suggestion for each programming knowledge point;

a plan pushing module 440, configured to push the learning assistance plan to the user.

In an optional implementation manner, the type determining module 420 is specifically configured to:

the plan generation module 430 is specifically configured to:

In an optional implementation, the type determining module 420 is further configured to:

the plan generation module 430 is specifically configured to:

In an optional implementation manner, the plan generating module 430 is specifically configured to:

In an optional implementation, the code detection module 410 is further configured to:

the plan generating module 430 is specifically configured to, when the plan generating module is configured to perform deduplication processing on each writing abnormal content existing in the program code based on the at least one historical writing abnormal content to obtain at least one target writing abnormal content:

In an optional embodiment, in the case that it is determined that the at least one history of the user is writing abnormal content, the plan generation module 430 is configured to:

In an alternative embodiment, as shown in fig. 5, the online programming learning assistance device 400 further comprises a report generation module 450, wherein the report generation module 450 is configured to:

The description of the processing flow of each module in the apparatus and the interaction flow between the modules may refer to the relevant description in the above method embodiments, and will not be described in detail here.

The online programming learning auxiliary device provided by the embodiment of the disclosure can respond to the preset operation of the user on the programmed program code when the user performs online programming learning, and detect whether the programmed program code has abnormal programming content; if the program code exists, determining the coding error type corresponding to each abnormal writing content in the program code based on the coding type of the program code; generating a learning auxiliary plan for the user based on each abnormal compiling content and the corresponding coding error type, wherein the learning auxiliary plan comprises programming knowledge points aiming at the abnormal compiling content and the corresponding coding error type and learning suggestions aiming at the programming knowledge points; and pushing the learning assistance plan to the user.

Corresponding to the online programming learning auxiliary method in fig. 1 and fig. 3, an embodiment of the present disclosure further provides an electronic device 600, as shown in fig. 6, a schematic structural diagram of the electronic device 600 provided in the embodiment of the present disclosure includes:

a processor 610, a memory 620, and a bus 630; the storage 620 is used for storing execution instructions and includes a memory 621 and an external storage 622; the memory 621 is also referred to as an internal memory, and is used for temporarily storing operation data in the processor 610 and data exchanged with an external memory 622 such as a hard disk, the processor 610 exchanges data with the external memory 622 through the memory 621, and when the electronic device 600 operates, the processor 610 and the memory 620 communicate through the bus 630, so that the processor 610 can execute the steps of the online programming learning assistance method.

It is to be understood that the illustrated structure of the embodiment of the present application does not constitute a specific limitation to the electronic device 600. In other embodiments of the present application, the electronic device 600 may include more or fewer components than illustrated, or combine certain components, or split certain components, or a different arrangement of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

The embodiments of the present disclosure also provide a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to perform the steps of the online programming learning assistance method described in the above method embodiments. The storage medium may be a volatile or non-volatile computer-readable storage medium.

The embodiments of the present disclosure further provide a computer program product, where the computer program product includes computer instructions, and when the computer instructions are executed by a processor, the steps of the online programming learning assistance method in the foregoing method embodiments may be executed.

The computer program product may be implemented by hardware, software or a combination thereof. In an alternative embodiment, the computer program product is embodied in a computer storage medium, and in another alternative embodiment, the computer program product is embodied in a Software product, such as a Software Development Kit (SDK), or the like.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and devices may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. In the several embodiments provided in the present disclosure, it should be understood that the disclosed apparatus, device and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present disclosure may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present disclosure. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

Finally, it should be noted that: the above-mentioned embodiments are merely specific embodiments of the present disclosure, which are used for illustrating the technical solutions of the present disclosure and not for limiting the same, and the scope of the present disclosure is not limited thereto, and although the present disclosure is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive of the technical solutions described in the foregoing embodiments or equivalent technical features thereof within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present disclosure, and should be construed as being included therein. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.

Claims

1. An online programming learning assistance method, the method comprising:

and pushing the learning assistance plan to the user.

2. The method according to claim 1, wherein the determining, based on the encoding type of the program code, the encoding error type corresponding to each of the writing exception contents existing in the program code comprises:

determining a first error type to which the writing abnormal content belongs for each writing abnormal content existing in the program code based on a plurality of preset basic error types under the coding types, wherein the basic error types comprise at least one of spelling errors, source code errors and syntax errors;

3. The method of claim 2, wherein after said determining the first error type to which the compose exception belongs, the method further comprises:

4. The method according to claim 1, wherein after determining the type of coding error corresponding to each of the writing exceptions existing in the program code based on the coding type of the program code, the method further comprises:

5. The method of claim 1, wherein generating a learning assistance plan for the user based on the respective composition anomaly content and the corresponding type of coding error comprises:

6. The method of claim 1, wherein generating a learning assistance plan for the user based on the respective composition anomaly content and the corresponding type of coding error comprises:

7. The method of claim 6, further comprising:

8. The method of claim 6, wherein in the event that it is determined that at least one history of the user authored anomalous content, the method further comprises:

9. An online programming learning aid, the device comprising:

10. An electronic device, comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating over the bus when the electronic device is running, the machine-readable instructions when executed by the processor performing the steps of the online programming learning aid method of any of claims 1-8.

11. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, carries out the steps of the online programming learning assistance method according to any one of claims 1 to 8.