CN113806661B

CN113806661B - Barrier-free detection tool for website information

Info

Publication number: CN113806661B
Application number: CN202111099013.5A
Authority: CN
Inventors: 宋文林; 王欣; 徐洋; 杨平; 李政国
Original assignee: China Electronics Standardization Institute
Current assignee: China Electronics Standardization Institute
Priority date: 2021-09-18
Filing date: 2021-09-18
Publication date: 2023-08-25
Anticipated expiration: 2041-09-18
Also published as: CN113806661A

Abstract

The invention relates to the technical field of computers, in particular to a barrier-free detection tool for website information, which comprises the following components: compared with the prior art, the invention has the advantages of intelligent detection, automatic detection, increment support and continuous measurement suspension. Intelligent sampling and easy analysis, and detection results can be displayed according to perceptibility, operability, comprehensibility, compatibility and the like in the standard, counted according to the standard level and the like. The detection result can generate a report to derive compliance detection software which can support a plurality of standards of China, industry and the like, and the detection flow is complete, strict, quick and accurate.

Description

Barrier-free detection tool for website information

Technical Field

The invention relates to the technical field of computers, in particular to a barrier-free detection tool for website information.

Background

According to statistics, 81723 websites of government institutions are opened, but the proportion of barrier-free websites is less than 1%, and more than 90% websites of some foreign areas realize information barrier-free, and our country has a distance from developed countries in terms of information barrier-free.

The data quantity and the template quantity of the government website are large, and whether the information barrier-free construction reaches the standard or not is detected manually only, so that the page of the whole website cannot be covered, and the information barrier-free construction is completed by computer assistance. The technicians also need to accurately know the problem points and the transformation conditions of the implementation range when the barrier-free construction of the website is implemented. Implementation manager is more required to grasp the implementation progress of the project, and all of these require the assistance of detection software to improve efficiency and accuracy.

The existing detection means are divided into three types of machine detection, auxiliary detection and manual detection:

1. and (3) machine detection: the machine can fully determine that this detection point is erroneous.

2. Auxiliary detection: the machine detects this detection point. But not fully judged to be erroneous. The judgment needs to be made manually.

3. And (3) manual detection: the machine can not detect or the machine detection has passed, and detection judgment is needed to be performed manually.

The test mode 2 and 3 has low efficiency in test, high artificial error, long detection time for detecting whether the database completes the barrier-free detection of the website information if the webpage text is large, and serious influence on the data processing speed. The software development document is necessary data in the process of software development, use and maintenance. The method can improve the efficiency of software development, ensure the quality of the software, and has the functions of guidance, assistance and confusion in the use process of the software, and especially in maintenance work, development documents are indispensable materials.

Therefore, a barrier-free detection tool for website information needs to be designed, and the barrier-free detection tool has the advantages of intelligent detection, automatic detection, increment support, continuous detection suspension, intelligent sampling and easy analysis, the detection result can be displayed according to the perceptibility, operability, comprehensibility, compatibility and the like in the standard, statistics is carried out according to the standard level and the like, and the detection result can generate a report to derive compliance detection software which can support a plurality of standards of China, industry and the like, and the detection flow is complete, strict, rapid and accurate.

Disclosure of Invention

The invention aims to overcome the defects of the prior art, provides a barrier-free detection tool for website information, has the advantages of intelligent detection, automatic detection, increment support, continuous detection suspension, intelligent sampling, easy analysis, detection results which can be displayed according to the perceptibility, operability, comprehensibility, compatibility and the like in the standard, statistics according to the standard level and the like, and detection results which can generate reports to derive compliance detection software which can support a plurality of standards of China, industry and the like, and the detection flow is complete, strict, quick and accurate.

In order to achieve the above object, the present invention provides a website information barrier-free detection tool: comprising the following steps: crawler design, structural design, interface design, module design and data structure design;

[ crawler design ] includes:

s1: initiating a request to a server: initiating a Request to a target site through the HTTP library, namely sending a Request, wherein the Request can contain additional headers information, and waiting for a response of a server;

s2: acquiring response content: if the server responds normally, a Response is obtained, the content of the Response is the page content to be acquired, and the types of the Response include HTML, JSON and binary files (such as pictures and videos);

s3: the content is analyzed: the content obtained is as follows:

the first is HTML, which is parsed by a regular expression and a webpage parsing library;

the second is JSON, directly converting into JOSN object for analysis;

the third is binary data, stored or further processed;

s4: the content is stored: the storage forms are various, and comprise texts, databases or files in specific formats;

[ structural design ] is: the software is developed by adopting a CS architecture to design JAVA language, the user interface adopts an SWT development kit, the core module adopts a JXBrowse open source chrome browser, and the database adopts a Sqlite embedded database;

[ interface design ] includes: a file interface, interface setting, viewing setting, toolbar setting, control bar setting, detection window setting, detection state setting, detection result setting, screening setting and progress state setting;

the file interface comprises: storing or loading the detection result, inquiring the website or the source code, and reporting and exiting a single page or summary report;

interface settings include mode settings, level settings, timeout settings, depth settings, and web page filtering;

mode setting: standing an inner frame type depth search: default opening, automatically identifying that an inline frame in a station detects webpage content and connection during searching;

and (5) in-station connection type deep search: the default on state, search the website through the address of the connected href attribute, is the main way to search the website;

in-station intelligent domain name retrieval: when the method is started, the main domain name is not searched, the subdomain name is also searched, and the default condition is a closing state;

level setting: the method comprises the steps of dividing the standard into three levels, wherein each level corresponds to the index of the standard response, the index can be set in detail, one or more indexes can be selected, and the function can be used when a user detects and modifies a single standard;

timeout setting: asynchronous loading, etc. settings: when the webpage has asynchronously loaded data or codes, waiting time is not longer than the waiting time, and the next detection stage is continued;

page load timeout settings: the webpage loading waiting time is not accessed for a long time due to network reasons and the reasons of the website, and after overtime, the webpage which is skipped to be loaded is ignored to load the next webpage;

depth setting: the method refers to the hierarchy of a tree structure from a website homepage, wherein the level of a general webpage is about 3-4 layers, and the level of the general webpage does not exceed 6 layers;

web page filtering: all files, audio and video of the website are filtered under the default condition, and if a special website or type needs to be set;

the viewing settings include detection results, source codes, previews and charts;

toolbar setting: the user operation is facilitated by the schematic operation function in the icon mode, and the display interface mainly comprises: storing detection results, loading detection results, mode setting, level setting, overtime setting, depth setting, web page filtering, advanced setting, single report, summary report, help and exit;

control column setting: the control column mainly controls the detection process, and the main functions include: detecting stopping, pausing and continuing; the detected website input frame starts to detect a button, and loads a local file for detection;

and (3) setting a detection window: the detection window consists of four selection cards, which are respectively: detecting windows, detecting codes, source codes and previews; four of the menu interfaces should be;

and (3) detecting state setting: displaying the detected state in the detection process, wherein the displayed state is normal, overtime, invalid and failed, and the operation comprises the following steps: refreshing, starting refreshing, and displaying all pages;

and (3) setting a detection result: the two tabs are respectively: a detection result and a chart; and a corresponding checked detection result interface, wherein the detection result comprises: index, detection classification, standard number, level, detection mode, detection result, position and detection point composition;

screening and setting: the data in the detection result can be screened through perceptibility, operability, comprehensiveness, compatibility, machine detection, auxiliary detection, manual detection and all display combinations in the screening column, so that the user can conveniently view the desired content;

setting a progress state: the method mainly comprises the steps of mainly displaying the detection depth and the overall progress, wherein the depth is generally divided into 1-10 layers and can be set in a self-defining mode, the maximum is 10 layers, and the progress is the number of the grabbed websites and the detection number after detection is finished;

[ Module design ] includes: the system comprises a verification module, a downloading module, a screening module, a simulation module, a detection module, a storage module and an analysis module;

and (3) a verification module: accessing the website through the input detection website, and verifying whether the input website can be normally accessed;

and (3) a downloading module: after the verification module passes, opening a webpage to be accessed according to a set level, completely imitating browser access through a JXBrowse plug-in, and downloading a website source code after the browser loads the webpage (including static webpage codes and dynamically loaded codes);

and a screening module: filtering the resource path websites according to a webpage filtering rule, wherein file downloading is performed by default for improving efficiency and speed, and no file is involved in the information barrier-free detection standard;

and (3) an analog module: the method comprises the steps that simulation operation is carried out on a keyboard operation part of a webpage through simulation operation, whether the keyboard meets barrier-free standards is detected, whether focus sinking of the keyboard, link access can be normally accessed or not can be detected, and whether the information of all the webpages accessed through the keyboard is barrier-free or not is related to operability;

and a detection module: detecting the problems of attribute relevance and the like of codes one by one according to various indexes of a line standard or a national standard;

and a storage module: the detection result is stored in a database through four aspects of perceptibility, operability, understandability and compatibility and three detection modes of machine detection, manual detection and auxiliary detection;

and an analysis module: analyzing the detection result in the database, summarizing the detection condition of the whole website, and deriving a report and a chart;

[ data structure design ] includes: detecting a standard information database, detecting the information database and exporting a summary table;

the detection standard information database comprises a standard information table and a standard description table, and comprises a detection summary table, a detection information table, a detection source code storage table and a detection link storage table;

standard information table: when the content information of the main storage standard is used for detecting problems, the corresponding standard information is displayed, and sentences are created: CREATE TABLE esd_info_Standard (ID UNIQUE NOT NULL, DESCRIPTION NOT NULL, LVL VARCHAR, PROP, STANDARD _CODE, IS_ CHECKED VARCHAR DEFAULT (1), STANDARD_ NAME VARCHAR);

standard description table: for displaying standard descriptions or technical descriptions;

creating a statement: CREATE TABLE "esd_info_accessibil y" ([ ID ] UNIQUE NOT NULL, [ describe ] NOT NULL

)；

Detection summary table: storing the detected summarized information; creating statements

CREATE TABLE esd_check_count(ID INTEGER PRIMARY KEY AUTOINCREMENT,SITE,STATE,FIRST,SECOND,THIRD,MACHINERYCOUNT,URL UNIQUE,LVL,DEPTH,TIME,DOWNLOADTIME,CHECKTIME)；

Detection information table: storing various information in the detection process; creating a statement:

CREATE TABLE esd_check_information(SITE COLLATE RTRIM,URL COLLATE

RTRIM,PROP COLLATE RTRIM,TYPE,LVL,ID,ANCHOR,UNIQUE_ID VARCHAR,ELEMENT_INDEX INT DEFAULT(0))；

CREATE INDEX I_queryLvlCount ON esd_check_information(URL COLLATE

RTRIM ASC,SITE COLLATE RTRIM ASC,LVL COLLATE BINARY ASC)；

CREATE INDEX I_queryTypeCount ON esd_check_information(URL COLLATE

RTRIM ASC,TYPE COLLATE BINARY ASC,SITE COLLATE RTRIM ASC)；

CREATE INDEX TYPE_SITE_INDEX

on esd_check_information(TYPE,SITE)；

CREATE INDEX ID_INDEX

on esd_check_information(ID)；

detecting a source code storage table: source code for storing a web page; creating a statement: CREATE TABLE esd_html_Source (SITE COLLATE BINARY, URL COLLATEBINARY, HTML, CHARSET, ORIGIN _LINK); CREATE INDEX queryhtml ON esd _html_source (SITE COLLATE BINARY ASC, URLCOLLATE BINARY ASC);

detecting a link storage table: the method is used for storing and grabbing website link addresses and creating sentences:

CREATE TABLE esd_url(id INTEGER PRIMARY KEY AUTOINCREMENT,url

VARCHAR(256)UNIQUE,parent_url VARCHAR(256),depth INT,checkStatusVARCHAR DEFAULT(0))；

deriving a summary table: temporarily summarizing a table esd_printallreports_key during report export, and exporting sentences: CREATE TABLEesd_PrintReports_key (id VARCHAR PRIMARY KEY, "key" VARCHAR, path VARCHAR).

The Response includes:

the request mode is as follows: mainly comprises two types of GET and POST, and HEAD, PUT, DELETE, OPTIONS;

request URL: URL is a universal resource locator, such as a web document, a picture, a video, etc., that can be uniquely identified by URL;

request header: including header information at the time of the request, such as User-Agent, host, cookies information;

request body: and data carried additionally when requested, such as form data when the form is submitted.

The Response includes:

response state: there are various response states, 200 representing success, 301 representing a jump, 404 representing no page found, 502 representing a server error;

response head: content type, content length, server information and cookie are set;

response body: including the content of the requested resource, such as web page HTML, picture binary data.

Page content includes web page text, picture files, video, and other files.

The analysis method comprises the following steps: direct processing, json parsing, regular expressions, beautiffulSoup, pyquery and XPath.

The content preservation method comprises the following steps: text, relational databases, non-relational databases, and binary files.

Compared with the prior art, the invention has the advantages of intelligent detection, automatic detection, increment support and continuous detection suspension. Intelligent sampling and easy analysis, and detection results can be displayed according to perceptibility, operability, comprehensibility, compatibility and the like in the standard, counted according to the standard level and the like. The detection result can generate a report to derive compliance detection software which can support a plurality of standards of China, industry and the like, and the detection flow is complete, strict, quick and accurate.

Drawings

FIG. 1 is a schematic diagram of a detection flow of the present invention;

FIG. 2 is a standard information representation intent of the present invention;

FIG. 3 is a standard description representation of the present invention;

FIG. 4 is a schematic diagram of a test summary of the present invention;

FIG. 5 is a diagram showing the detection information of the present invention;

FIG. 6 is a diagram of a detected source code storage representation of the present invention;

FIG. 7 is a diagram of a detected link storage representation intent of the present invention;

FIG. 8 is a schematic diagram of a main interface of the present invention;

FIG. 9 is a toolbar of the present invention;

FIG. 10 is a schematic diagram of the structure of the present invention;

FIG. 11 is a diagram of a derived detection report according to the present invention.

Detailed Description

The invention will now be further described with reference to the accompanying drawings.

Referring to fig. 1-7, the present invention provides a website information barrier-free detection tool:

comprising the following steps: crawler design, structural design, interface design, module design and data structure design;

[ crawler design ] includes:

s3: the content is analyzed: the content obtained is as follows:

the second is JSON, directly converting into JOSN object for analysis;

the third is binary data, stored or further processed;

[ structural design ] is: the software is developed by adopting a CS architecture to design JAVA language, the user interface adopts a SWT development kit, the core module adopts a JXBrowse open source chrome browser, and the database adopts a Sqlite embedded database.

the mode setting: standing an inner frame type depth search: default opening, automatically identifying that an inline frame in a station detects webpage content and connection during searching;

)；

CREATE TABLE esd_check_information(SITE COLLATE RTRIM,URL COLLATE

CREATE INDEX I_queryLvlCount ON esd_check_information(URL COLLATE

RTRIM ASC,SITE COLLATE RTRIM ASC,LVL COLLATE BINARY ASC)；

CREATE INDEX I_queryTypeCount ON esd_check_information(URL COLLATE

RTRIM ASC,TYPE COLLATE BINARY ASC,SITE COLLATE RTRIM ASC)；

CREATE INDEX TYPE_SITE_INDEX

on esd_check_information(TYPE,SITE)；

CREATE INDEX ID_INDEX

on esd_check_information(ID)；

CREATE TABLE esd_url(id INTEGER PRIMARY KEY AUTOINCREMENT,url

VARCHAR(256)UNIQUE,parent_url VARCHAR(256),depth INT,checkStatus

VARCHAR DEFAULT(0))；

deriving a summary table: temporarily summarizing a table esd_printallreports_key during report export, and exporting sentences: CREATE TABLE esd_printReports_key (id VARCHAR PRIMARY KEY, "key" VARCHAR, path VARCHAR).

The Response includes:

Page content includes web page text, picture files, video, and other files.

In the actual use process, the invention operates according to the following steps:

detecting software main page

And (5) preserving the detection result: and (5) saving the result of detection completion. The file generated is a file of db.

Loading a detection result: loading the detection result, wherein the file is the file mode setting of db: the method for acquiring the website in the webpage is designed, and whether the second-level domain name is searched intelligently or not is judged.

Standing inner frame type depth search: the method is mainly used for setting whether to detect the src attribute in the < frame > tag and the < iframe >.

In-station linked depth setting: the method is mainly used for setting whether to detect the href attribute in the < a > tag.

In-station intelligent domain name search: the method is mainly used for detecting whether the website provided with the secondary domain name is detected or not. And (3) selecting: the second-level domain name is not searched, and is not checked: and searching the secondary domain name.

Level setting: the detection software classifies the detection points into 4 classes (perceptibility, operability, comprehensiveness, compatibility). There are 3 levels (level 1, level 2, level 3) in each class. The set here is the class 4 at the time of detection, all detected by that class. And meanwhile, whether the standard corresponding to each grade is detected or not can be set.

Timeout setting: it is set how long to download the completed web page source code. A timeout is considered if no download is completed within a set time. The web page displayed in the software in the timeout state is not detected as an invalid web page. But the web page in the timeout state may be changed to the normal state by increasing the timeout time.

Depth setting: the number of layers to be detected is set. To be used in conjunction with the set-up mode.

Web page filtering: adding some has no meaning. Or unwanted detection sites such as (.avi.mp3) etc.

Single page report: a report is generated for a single web page.

Batch report: and summarizing the report forms of all the detected web pages.

Help: software instructions. And an introduction to the software.

Exiting: the procedure is exited.

Detecting a control column: may be at the time of detection. And performing operation control of stopping, suspending and continuing.

Address bar: inputting a website or a local path to be detected.

Detection button: clicking starts to detect the input website or file.

Loading a local file: clicking can select a path of the local file. After selecting the file to be detected, clicking on the "open" program automatically sets the path into the address bar.

The main window mainly comprises (detection window, source code, preview);

detection window: the method is mainly used for displaying the detected web pages. Each row represents a detected web page.

Looking up the website: and viewing the website information of the current webpage.

All the marks are as follows: in the previewed browser, the information of all detection points in the web page is marked.

Viewing the source of the link: and viewing the current webpage link source information.

Meaning of each column of the table:

index: representing the line number.

Download status: the status representing the downloaded source code includes (normal, timeout, invalid)

First stage: total number of first level detection results of the current web page.

Second stage: total number of second level detection results of the current web page.

Third stage: total number of third level detection results of the current web page.

And (3) machine detection: and (5) detecting the current webpage machine. If 0, YES is displayed.

Detecting a website: displaying website information of current webpage

Source code window: one record in the detection window is clicked (one record represents one web page). The html source code with the processed line number is correspondingly displayed in the source code window.

Previewing: one record in the detection window is clicked (one record represents one web page). The preview window will display the page of the current web site.

Included in the auxiliary window (detection result, graph);

detecting classified query: is divided into two parts (characteristic query region, detection mode query region).

Characteristic query region: is a multi-selection button, and the detection results can be screened according to any combination of the characteristics of the wanted inquiry.

Detection mode query area: is a radio button and is screened according to the detection mode. All displays are meant to include both machine and manual detection, which is equivalent to not screening the detection means.

Detection result: and displaying the detection information corresponding to the selected webpage. Each row represents information of the detection result corresponding to one detection point. Clicking a row with the left key marks the current element position information in the form of a red frame in a detection window (preview). Double clicking a row with the left key displays the source code information of the currently detected element in the detection window (source code).

The auditing is as follows: the selected detection point or the corresponding standard is marked, and whether the detection is passed under the current website or webpage or not.

And (3) whole station: the currently selected criteria are marked as pass detection under the entire web site.

Web page: the currently selected criteria, under the current web page, are marked as pass detection.

Detecting point: under the current webpage, all detection records corresponding to the selected detection points are marked as passing detection.

A single bar: and marking one detection result corresponding to the currently selected detection point as passing detection under the current webpage.

View description: and checking the standard description corresponding to the current detection point. Meaning of all columns of the detection result table:

index: representing the line number.

And (5) detection classification: the 4-size features in the standard were examined.

Standard number: the number of the standard corresponding to the detection point.

Test grade: the name and grade of the standard corresponding to the detection point.

The detection mode is as follows: the method is divided into two types of machine detection, auxiliary detection and manual detection.

And (3) machine detection: the machine can fully determine that this detection point is erroneous. Auxiliary detection: the machine detects this detection point. But not fully judged to be erroneous. The judgment needs to be made manually.

And (3) manual detection: the machine can not detect or the machine detection has passed, and detection judgment is needed to be performed manually.

Detection point results: detection standard information corresponding to the detection points.

Position: detecting the specific position of the erroneous position.

Detecting point: current detection point number information

Graph (c): displaying the summary of the detection points of the currently selected webpage. The histogram is displayed in 4 large attribute categories.

The status bar is divided into 4 areas which are sequentially (running dynamic, downloading status, depth, detection progress) from left to right.

Motion state: dynamic display (initialization, start download, download complete, start detect, detect complete.) the running state of the software can be known from the displayed prompts.

Download status: the download status is classified as (normal, timeout, invalid).

Depth: the depth to be detected is displayed, and the currently detected depth is (1/10) represented. To detect 10 layers, layer 1 is currently being detected.

Detecting the progress: indicating the number of web pages to be detected and the number of web pages for which the detection is completed. The number of web pages to be detected increases according to the change in the number of layers.

Mode setting: at least one mode is selected to grasp the web site. Otherwise, only the input web page is detected.

Depth setting: the depth (also called the number of layers) is chosen according to the requirements. The software will detect the web site by layer according to the mode you choose in the "mode setting". The "page limit" is set to 0.

Timeout setting: the timeout is preferably 30 seconds during the whole station detection, and setting too few will generate excessive timeout and invalid web pages.

The operation is as follows: the homepage address of the website to be detected is input in the website column. Click the detect button.

Notice that: the detection software for the whole station can detect the website in the station and can not detect the externally linked website. How to distinguish whether the web address is an in-station web address is judged according to the features of the homepage web address input by you, for example: http:// www.163.com, http:// www.hao123.com, then (.163.) (.hao123.) are features. If a perfect match detection is desired for the entered web site, the "intelligent hyperlink detection in station" can be eliminated in the mode setting, and the feature is changed to (www.163.com /) where x represents any.

Depth setting: for the single page detection, only the web page of the inputted website is detected, and the layer number is not required, so that only the detection depth is set to 0 to indicate that only the page is detected, and the use is recommended. Setting the value in "page limit" to 1 without limiting the detection depth also achieves the effect of detecting only the current web page, but this method is not recommended.

Inputting the homepage address of the website to be detected in the website column, and clicking a detection button.

Local page, file detection:

depth setting: it will also work for local file depth settings. The detection depth setting of 0 is also required if only the local file is detected. If the number of layers is set. The software will operate the file as an effect of the homepage, but without homepage features, the external links will also be detected, resulting in an endless detection.

The operation is as follows: two methods

First kind: clicking the "load local file" button. Selecting a file to be detected, clicking on "open" can see the selected file path in the website column, and then clicking on detection.

Second kind: directly inputting a file path in a website column, and clicking for detection;

saving and loading test results

Notice that: the loaded and saved files are preferably the same version of software. Errors and the like may occur if the software is not the same version.

And (3) preserving: clicking on the save detection result in the toolbar selects the path to be saved.

And (3) loading: clicking the loading detection result in the toolbar to select the file to be loaded.

Single page detection report generation

Notice that: the single page report can be exported during detection. So long as the displayed web address in the detected form can be selected and exported.

And selecting a website from which the report is to be exported in the detection window. Clicking on a single page report in the toolbar. The single page report can be exported.

Generating summary report by the whole station

Notice that: the summary report is only tested after the software stops testing or the testing is finished. Can be summarized. Pausing is not possible to export summary reports.

After the detection is finished and the click is 'confirmed', clicking the summary report in the toolbar. The summarized report can be derived.

During the detection process. After clicking the stop button, clicking the summary report in the toolbar. A summary report may also be derived. The detailed operation is as follows:

and clicking the determination button can save the detection result data first, and storing the detection result data in a db format.

[ all derivatives ]: export summary page, each sub-page [ export summary page ]: only summary pages are exported.

The invention solves the problems of low efficiency and high human error during testing, provides a barrier-free detection tool for website information, has the advantages of intelligent detection, automatic detection, increment support, continuous detection suspension, intelligent sampling, easy analysis, detection results which can be displayed according to the classification of perceptibility, operability, comprehensibility, compatibility and the like in the standard, statistics according to the standard level and the like, and detection results which can generate reports to derive compliance detection software which can support a plurality of standards of China, industry and the like, and has complete, strict, quick and accurate detection flow.

While the embodiments of the present invention have been described above, the scope of the present invention is not limited to the above, and the present invention can be implemented by various modifications without departing from the gist of the present invention, but is included in the scope of protection of the present patent.

Claims

1. The website information barrier-free detection tool is characterized by comprising: crawler design, structural design, interface design, module design and data structure design;

the [ crawler design ] includes:

s2: acquiring response content: if the server responds normally, a Response is obtained, the content of the Response is the page content to be acquired, and the types of the Response are HTML, JSON and binary files;

s3: the content is analyzed: the content obtained is as follows:

the second is JSON, directly converting into JOSN object for analysis;

the third is binary data, stored or further processed;

the [ structural design ] is as follows: the software is developed by adopting a CS architecture to design JAVA language, the user interface adopts an SWT development kit, the core module adopts a JXBrowse open source chrome browser, and the database adopts a Sqlite embedded database;

the [ interface design ] includes: a file interface, interface setting, viewing setting, toolbar setting, control bar setting, detection window setting, detection state setting, detection result setting, screening setting and progress state setting;

the interface settings comprise mode settings, level settings, timeout settings, depth settings and web page filtering;

and (5) in-station connection type deep search: searching the website through the address of the connected href attribute in a default starting state;

the level setting: the method comprises the steps of dividing the standard into three levels, wherein each level corresponds to the index of the standard response, the index can be set in detail, one or more indexes can be selected, and the function can be used when a user detects and modifies a single standard;

the timeout setting: asynchronous loading, etc. settings: when the webpage has asynchronously loaded data or codes, waiting time is not longer than the waiting time, and the next detection stage is continued;

the depth setting: means a hierarchy of a tree structure starting from a website homepage;

the web page filtering: all files, audio and video of the website are filtered under the default condition, and if a special website or type needs to be set;

the viewing settings comprise detection results, source codes, previews and charts;

the toolbar setting: the user operation is facilitated by the schematic operation function in the mode of icons, and the display interface comprises: storing detection results, loading detection results, mode setting, level setting, overtime setting, depth setting, web page filtering, advanced setting, single report, summary report, help and exit;

the control column is set: the control column is used for controlling the detection process, and the functions comprise: detecting stopping, pausing and continuing; the detected website input frame starts to detect a button, and loads a local file for detection;

the detection window is set: the detection window consists of four selection cards, which are respectively: detecting windows, detecting codes, source codes and previews; four of the menu interfaces should be;

the detection state setting: displaying the detected state in the detection process, wherein the displayed state is normal, overtime, invalid and failed, and the operation comprises the following steps: refreshing, starting refreshing, and displaying all pages;

the detection result is set: the two tabs are respectively: a detection result and a chart; and a corresponding checked detection result interface, wherein the detection result comprises: index, detection classification, standard number, level, detection mode, detection result, position and detection point composition;

the screening arrangement: the data in the detection result can be screened through perceptibility, operability, comprehensiveness, compatibility, machine detection, auxiliary detection, manual detection and all display combinations in the screening column, so that the user can conveniently view the desired content;

the progress state is set: displaying the detection depth and the overall progress, wherein the depth is divided into 1-10 layers, the depth can be set in a self-defining way, the maximum is 10 layers, and the progress is the number of the grabbed websites and the detection number after detection is completed;

the [ module design ] includes: the system comprises a verification module, a downloading module, a screening module, a simulation module, a detection module, a storage module and an analysis module;

the verification module: accessing the website through the input detection website, and verifying whether the input website can be normally accessed;

the download module: after the verification module passes, starting to access the webpage according to the set level, completely simulating the browser access through the JXBrowse plug-in, and downloading the website source code after the browser loads the webpage;

the screening module is used for: filtering the resource path websites according to a webpage filtering rule, wherein file downloading is performed by default for improving efficiency and speed, and no file is involved in the information barrier-free detection standard;

the simulation module: the method comprises the steps that simulation operation is carried out on a keyboard operation part of a webpage through simulation operation, whether the keyboard meets barrier-free standards is detected, whether focus sinking of the keyboard, link access can be normally accessed or not can be detected, and whether the information of all the webpages accessed through the keyboard is barrier-free or not is related to operability;

the detection module is used for: detecting attribute relevance problems of codes one by one according to various indexes of a line standard or a national standard;

the storage module is used for: the detection result is stored in a database through four aspects of perceptibility, operability, understandability and compatibility and three detection modes of machine detection, manual detection and auxiliary detection;

the analysis module: analyzing the detection result in the database, summarizing the detection condition of the whole website, and deriving a report and a chart;

the [ data structure design ] includes: detecting a standard information database, detecting the information database and exporting a summary table;

the standard information table: storing standard content information, displaying corresponding standard information when the standard content information is used for detecting problems, and creating sentences: CREATE TABLE esd_info_Standard (ID UNIQUE NOT NULL, DESCRIPTION NOT NULL, LVL VARCHAR, PROP, STANDARD _CODE, IS_ CHECKED VARCHAR DEFAULT (1), STANDARD_ NAME VARCHAR);

the standard description table: for displaying standard descriptions or technical descriptions;

creating a statement: CREATE TABLE "esd_info_accessibility" ([ ID ] UNIQUE NOT NULL, [ DESCRIPTION ] NOT NULL)

)；

The detection summary table: storing the detected summarized information; creating statements

The detection information table: storing various information in the detection process; creating a statement:

CREATE TABLE esd_check_information(SITE COLLATE RTRIM,URL COLLATE

CREATE INDEX I_queryLvlCount ON esd_check_information(URL COLLATE

RTRIM ASC,SITE COLLATE RTRIM ASC,LVL COLLATE BINARY ASC)；

CREATE INDEX I_queryTypeCount ON esd_check_information(URL COLLATE

RTRIM ASC,TYPE COLLATE BINARY ASC,SITE COLLATE RTRIM ASC)；CREATE INDEX TYPE_SITE_INDEX

on esd_check_information(TYPE,SITE)；

CREATE INDEX ID_INDEX

on esd_check_information(ID)；

the detection source code storage table: source code for storing a web page; creating a statement: CREATE TABLE esd_html_Source (SITE COLLATE BINARY, URL COLLATEBINARY, HTML, CHARSET, ORIGIN _LINK); CREATE INDEX queryhtml ON esd _html_source (SITE COLLATE BINARY ASC, URLCOLLATE BINARY ASC);

the detection link stores the table: the method is used for storing and grabbing website link addresses and creating sentences:

CREATE TABLE esd_url(id INTEGER PRIMARY KEY AUTOINCREMENT,url

VARCHAR(256)UNIQUE,parent_url VARCHAR(256),depth INT,checkStatus

VARCHAR DEFAULT(0))；

the export summary table: temporarily summarizing a table esd_printallreports_key during report export, and exporting sentences: CREATE TABLE esd_printReports_key (id VARCHAR PRIMARY KEY, "key" VARCHAR, path VARCHAR).

2. The website information obstacle-free detection tool according to claim 1, wherein: the Response includes:

the request mode is as follows: GET, POST, HEAD, PUT, DELETE, OPTIONS;

request URL: URL is collectively referred to as uniform resource locator;

request header: including header information at the time of the request;

request body: data carried additionally when requested.

3. The website information obstacle-free detection tool according to claim 1, wherein: the Response includes:

response body: including the content of the requested resource.

4. The website information obstacle-free detection tool according to claim 1, wherein: the page content includes web page text, picture files, video and other files.

5. The website information obstacle-free detection tool according to claim 1, wherein: the analysis method comprises the following steps: direct processing, json parsing, regular expressions, beautiffulSoup, pyquery and XPath.

6. The website information obstacle-free detection tool according to claim 1, wherein: the stored content comprises: text, relational databases, non-relational databases, and binary files.