CN109885767B - Method and system for recommending software assets based on GitHub - Google Patents
Method and system for recommending software assets based on GitHub Download PDFInfo
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Abstract
The invention provides a method and a system for recommending software assets based on GitHub. The method comprises the following steps: presenting the current development condition of developers and software codes according to developer data and software asset data of a GitHub platform, and contributing to the comprehensive statistics and analysis of the developers and the software assets; establishing a developer information model A and a software asset information model B; collecting behavior information of a developer on software and code development, and establishing a developer-behavior matrix model C; recommending Top-n software assets which best meet requirements for a target developer by utilizing a collaborative filtering recommendation technology based on developer similarity measurement and behavior prediction, namely a Top-n recommendation module; therefore, the problem that developers waste a large amount of time to find the software assets which best meet the requirements is solved, effective development resources and development directions are provided for software developers according to the software asset recommendation system, and rapid development of software asset markets is promoted.
Description
Technical Field
The invention relates to a method and a system for recommending software assets.
Background
GitHub has a huge amount of open source code libraries and versions, and the GitHub has become a preferred method for managing software development and finding existing codes and is a necessary tool for code players. Although the traditional software asset management technology can master the software development and code use conditions, software and codes which best meet the requirements of developers cannot be recommended in time according to the software and code development conditions, so that the software developers need to spend redundant time in huge software and code warehouses to find the self requirement targets, the burden and time and energy cost of the developers are increased, and the development of the software asset market is not facilitated to be accelerated.
Disclosure of Invention
The invention aims to effectively recommend the software assets which best meet the requirements of developers on the premise of reasonableness and science, provide efficient selection paths for the developers, save time and labor cost and promote the development of software development markets.
In order to achieve the above object, the present invention provides a method and a system for recommending software assets based on a GitHub, the steps of the present invention include:
step 1, acquiring software asset information of a GitHub platform;
step 2, establishing a developer information model A to record behavior information of different developers on software assets; the behavior information includes: searching, browsing, downloading, editing and submitting;
step 3, establishing a software asset information model B to record the total times of different behaviors of a developer on the software asset;
step 4, collecting behavior information of a developer on the software assets in the GitHub, and establishing a developer-behavior matrix model C for analyzing the most similar developer according to behavior similarity and providing the software assets which most meet the requirements;
step 5, adding different weight values k to the behavior information of each developer on the software assets;
and 6, recommending the Top-n software assets meeting the requirements for the developer by utilizing a collaborative filtering recommendation technology based on a similarity measurement technology of the code developer and a behavior prediction technology of the developer.
Preferably, the software asset information in step 1 includes: software discovery information, software licensing information, software usage information, software version information, software patch information, software development information, code development information.
Preferably, in the step 2, a developer searching module, a browsing module, a downloading module, an editing module and a submitting module are constructed according to the developer information model a, and a software asset list that the developer has acted is recorded through each module.
Preferably, in the step 5, the k values of searching, browsing, downloading, editing and submitting are sequentially set to 1, 2, 3, 4 and 5, respectively.
Preferably, in step 6, calculating a similarity sim (i, j) between the target developer i and the other developer j according to a similarity calculation method based on a developer similarity measurement technique;
h is a software asset set commonly acted by developers i and j; ki,h、Kj,hRespectively representing the actual behavior values of the developers i and j to the commonly-acted software asset h;
respectively representing the software asset weight average values of i and j behaviors of the developers.
Preferably, the developer behavior prediction technology arranges sim (i, j) values in descending order, takes the top N adjacent developer sets N with the highest similarity value, and calculates the behavior prediction value v for the target project s of the target developer i according to each adjacent developer u in the adjacent developer sets Ni,s；
Wherein the behavior weight of the adjacent developer u to the target item s is Ku,s；
Representing the average of the behavior of the neighboring developers u for all the software assets that have performed.
Preferably, the method for recommending the Top-n software assets meeting the requirement for the developer comprises the following steps:
step 6.1, setting a threshold value a;
step 6.2, when vi,s>When a, putting the cells into a Top-n set, and arranging the cells in a descending order;
and 6.3, finally recommending the first n software assets which best meet the requirements of the developers according to the similarity of the behaviors of the developers and the behavior predicted value.
A GitHub-based software asset recommendation system comprising the following modules: the system comprises a developer information acquisition module, a software asset information construction module, a developer behavior information construction module, a target developer behavior information acquisition module, a target developer software asset information acquisition module, a similar developer behavior information acquisition module, a similar developer software asset information acquisition module and a Top-n recommendation software asset display module;
the developer information acquisition module and the software asset information acquisition module are respectively connected with a data warehouse in the GitHub platform so as to acquire software asset information and developer information;
the developer information includes: the account ID information of the developers and the behavior information of different developers on the software assets;
the developer information acquisition module sends developer information to the developer behavior information construction module, and the developer behavior information construction module sequentially and correspondingly generates behavior information of developers with different account ID information on software assets;
the target developer behavior information acquisition module searches all developers of the developer behavior information construction module, acquires the behavior information of the target developer corresponding to the target developer, and records different behaviors according to the behavior with the highest weight;
the software asset information acquisition module sends the acquired software asset information to a software asset information construction module to generate ID information of each software asset, url information of each software asset and the name of each software asset, and the total behavior times of a developer are recorded in the url of each software asset;
the target developer software asset information acquisition module acquires the behavior information of the target developer corresponding to the target developer, which is sent by the target developer behavior information acquisition module;
the target developer behavior information acquisition module sends behavior information of the target developer to the similar developer behavior information acquisition module, and the similar developer behavior information acquisition module generates similar developer behavior information;
the target developer software asset information acquisition module provides a software asset set of behaviors of the target developer for the similar developer behavior information acquisition module, and the similar developer behavior information acquisition module generates a software asset set of behaviors of the similar developer;
the target developer software asset information acquisition module transmits the software asset information of the target developer to the software asset information acquisition module of the similar developer, and the software asset information acquisition module of the similar developer generates the software asset information of the similar developer;
the software asset information acquisition module of the similar developer provides software asset information of the similar developer for the similar developer behavior information acquisition module, and the similar developer behavior information acquisition module generates behavior information of the similar developer on the software asset according to the software asset information of the similar developer provided by the software asset information acquisition module of the similar developer;
the behavior information acquisition module of the similar developer and the software asset information acquisition module of the similar developer acquire the similar behavior and the software asset information of the behavior of the similar developer by using the behavior measurement similarity of the developer and then send the software asset information to the Top-n recommendation software asset display module;
and the Top-n recommendation software asset display module comprehensively recommends the Top-n software asset which best meets the requirements of the target developer according to the behavior prediction technology and the collaborative filtering recommendation algorithm.
Preferably, the developer behavior information construction module further comprises: the method comprises the following steps that a developer searches a construction module, browses the construction module, downloads the construction module, edits the construction module and submits the construction module;
the behavior information of the developer on the software assets comprises: searching, browsing, downloading, editing and submitting;
the system comprises a developer searching and constructing module, a developer browsing and constructing module, a developer downloading and constructing module, a developer editing and constructing module and a developer submitting and constructing module, wherein the developer searching and constructing module is used for recording a software asset list searched by the developer, the developer browsing and constructing module is used for recording a software asset list browsed by the developer, the developer downloading and constructing module is used for recording a software asset list downloaded by the developer, the developer editing and constructing module is used for recording a software development code list edited by the developer, and the developer submitting and constructing module is used for recording a software asset list submitted by.
Preferably, the software asset information comprises: software discovery information, software licensing information, software usage information, software version information, software patch information, software development information, code development information.
The method has the advantages that the requirements of developers can be effectively identified and integrated, time and energy are reduced for the developers, development of software development markets can be facilitated, and development rate and innovation of the developers are improved. On the premise of reasonableness and science, the invention effectively recommends the software assets which best meet the requirements of developers, furthest exerts the benefits of the software assets, and has important significance for promoting the development of the software assets industry and promoting the innovation of developers.
Drawings
FIG. 1 is a schematic flow diagram of the process of the present invention;
fig. 2 is a schematic diagram of the general architecture of the system of the present invention.
Detailed Description
In order to make the technical means, the original characteristics, the achieved purposes and the effects of the invention easy to understand, the invention is further explained in detail with the accompanying drawings and the specific embodiments, but the scope of the invention is not limited in any way.
As shown in fig. 2, the system structure of the present invention comprises: the system comprises a developer information acquisition module (203), a software asset information acquisition module (202), a software asset information construction module (210), a developer behavior information construction module (209), a target developer behavior information acquisition module (211), a target developer software asset information acquisition module (212), a similar developer behavior information acquisition module (214), a similar developer software asset information acquisition module (213) and a Top-n recommendation software asset display module (215).
The developer information acquisition module (203) and the software asset information acquisition module (202) are respectively connected with a data warehouse (201) in the GitHub platform to acquire software asset information and developer information; the developer information includes: developer account ID information and behavior information of different developers on software assets.
The developer information acquisition module (203) sends developer information to the developer behavior information construction module (209), and the developer behavior information construction module (209) sequentially generates behavior information of developers with different account ID information on software assets correspondingly.
And the target developer behavior information acquisition module (211) searches all developers of the developer behavior information construction module (209), acquires the behavior information of the target developer corresponding to the target developer, and records different behaviors according to the behavior with the highest weight.
The software asset information acquisition module (202) sends the acquired software asset information to a software asset information construction module (210) to generate ID information of each software asset, url (resource locator) information of each software asset and the name of each software asset, wherein the url of each software asset records the total browsing times and the total downloading times of a developer.
A target developer software asset information acquisition module (212) acquires the behavior information of the target developer corresponding to the target developer, which is sent by a target developer behavior information acquisition module (211); the target developer behavior information acquisition module (211) sends behavior information of the target developer to the similar developer behavior information acquisition module (214), and the similar developer behavior information acquisition module (214) generates similar developer behavior information; the target developer software asset information acquisition module (212) provides the software asset set which is subjected to the behavior of the target developer for the similar developer behavior information acquisition module (214), and the similar developer behavior information acquisition module (214) generates the software asset set which is subjected to the joint behavior of the similar developers.
The target developer software asset information acquisition module (212) sends the software asset information of the target developer to the software asset information acquisition module (213) of the similar developer, and the software asset information acquisition module (213) of the similar developer generates the software asset information of the similar developer; the software asset information acquisition module (213) of the similar developer provides the software asset information of the similar developer for the behavior information acquisition module (214) of the similar developer, and the behavior information acquisition module (214) of the similar developer generates the behavior information of the similar developer to the software asset according to the software asset information of the similar developer provided by the software asset information acquisition module (213) of the similar developer; the similar developer behavior information acquisition module (214) and the similar developer software asset information acquisition module (213) acquire similar behavior and behavior software asset information of similar developers by using the similarity of the developer behavior metrics, and then send the information to the Top-n recommendation software asset display module (215).
And the Top-n recommendation software asset display module (215) comprehensively recommends the Top-n software asset which best meets the requirements of the target developer according to the behavior prediction technology and the collaborative filtering recommendation algorithm.
The developer behavior information construction module (209) further comprises: the method comprises the following steps that a developer searches for a building module (205), browses the building module (204), downloads the building module (206), edits the building module (207) and submits the building module (208); the behavior information of the developer on the software assets comprises: searching, browsing, downloading, editing and submitting.
The developer search building module (205) is used for recording a software asset list searched by the developer, the developer browse building module (204) is used for recording a software asset list browsed by the developer, the developer download building module (206) is used for recording a software asset list downloaded by the developer, the developer edit building module (207) is used for recording a software development code list edited by the developer, and the developer submission building module (208) is used for recording a software asset list submitted by the developer.
The software asset information includes: software discovery information, software licensing information, software usage information, software version information, software patch information, software development information, code development information.
As shown in fig. 1, the steps of the present invention include:
step 1, acquiring software asset information of a GitHub platform.
Step 2, establishing a developer information model A to record behavior information of different developers on software assets; the behavior information includes: searching, browsing, downloading, editing and submitting.
And 3, establishing a software asset information model B to record the total times of different behaviors of the developer on the software asset, such as the total browsing times, the total downloading times and the like.
And 4, collecting behavior information of the developer on the software assets in the GitHub, and establishing a developer-behavior matrix model C for analyzing the most similar developer according to the behavior similarity and providing the software assets which most meet the requirements.
Step 5, adding different weight values k to the behavior information of each developer on the software assets; and setting the k values of searching, browsing, downloading, editing and submitting to be 1, 2, 3, 4 and 5 in sequence respectively.
And 6, recommending the Top-n software assets meeting the requirements for the developer by utilizing a collaborative filtering recommendation technology based on a similarity measurement technology of the code developer and a behavior prediction technology of the developer.
Further, in step 2, a developer search module, a browse module, a download module, an edit module and a submit module are constructed according to the developer information model a, and a software asset list that the developer has acted is recorded through each module, including a search list, a browse list, a download list, an edit list and a submit list.
Further, in step 6, based on the developer similarity measurement technique, a similarity sim (i, j) between the target developer i and the other developer j is calculated according to a similarity calculation method;
h is a software asset set commonly acted by developers i and j; ki,h、Kj,hRespectively representing the actual behavior values of the developers i and j to the commonly-acted software asset h;
respectively representing the software asset weight average values of i and j behaviors of the developers.
The developer behavior prediction technology arranges sim (i, j) values in descending order, takes the first N adjacent developer sets N with the highest similarity value, and then develops according to the adjacentEach adjacent developer u in the developer set N respectively calculates a behavior predicted value v for a target project s of a target developer ii,s；
Wherein the behavior weight of the adjacent developer u to the target item s is Ku,s；
Representing the average of the behavior of the neighboring developers u for all the software assets that have performed.
The method for recommending the Top-n software assets meeting the requirements for the developer comprises the following steps:
step 6.1, setting a threshold value a;
step 6.2, when vi,s>When a, putting the cells into a Top-n set, and arranging the cells in a descending order;
and 6.3, finally recommending the first n software assets which best meet the requirements of the developers according to the similarity of the behaviors of the developers and the behavior predicted value.
While the present invention has been described in detail by way of the foregoing preferred examples, it is to be understood that the above description is not to be taken as limiting the invention. Various modifications and alterations to this invention will become apparent to those skilled in the art upon reading the foregoing description. Accordingly, the scope of the invention should be determined from the following claims.
Claims (7)
1. A method for gitchub-based software asset recommendation, comprising the steps of:
step 1, acquiring software asset information of a GitHub platform;
step 2, establishing a developer information model A to record behavior information of different developers on software assets; the behavior information includes: searching, browsing, downloading, editing and submitting;
step 3, establishing a software asset information model B to record the total times of different behaviors of a developer on the software asset;
step 4, collecting behavior information of a developer on the software assets in the GitHub, and establishing a developer-behavior matrix model C which is used for analyzing the most similar developer according to behavior similarity and providing the software assets which best meet the requirements;
step 5, adding different weight values k to the behavior information of each developer on the software assets;
step 6, recommending the Top-n software assets meeting the requirements for the developer by utilizing a collaborative filtering recommendation technology based on a similarity measurement technology of a code developer and a behavior prediction technology of the developer;
in the step 5, the k values searched, browsed, downloaded, edited and submitted are sequentially and respectively set to be 1, 2, 3, 4 and 5;
in step 6, calculating a similarity sim (i, j) between the target developer i and the other developer j according to a similarity calculation method based on a developer similarity measurement technique;
h is a software asset set commonly acted by developers i and j; ki,h、Kj,hRespectively representing the actual behavior values of the developers i and j to the commonly-acted software asset h;
respectively representing the software asset weight average values of i and j behaviors of the developer;
the developer behavior prediction technology arranges sim (i, j) values in descending order, takes the former N adjacent developer sets N with the highest similarity value, and calculates the behavior prediction value v for the target project s of the target developer i according to each adjacent developer u in the adjacent developer sets Ni,s；
Wherein the behavior weight of the adjacent developer u to the target item s is Ku,s；
Representing the average of the behavior of the neighboring developers u for all the software assets that have performed.
2. The method of claim 1, wherein the software asset information of step 1 comprises: software discovery information, software licensing information, software usage information, software version information, software patch information, software development information, code development information.
3. The method according to claim 1, wherein in the step 2, a developer searching module, a browsing module, a downloading module, an editing module and a submitting module are constructed according to the developer information model A, and a software asset list which is acted by the developer is recorded through each module.
4. The method of claim 1, wherein the method step of recommending Top-n software assets meeting the requirement for the developer comprises:
step 6.1, setting a threshold value a;
step 6.2, when vi,s>When a, putting the cells into a Top-n set, and arranging the cells in a descending order;
and 6.3, finally recommending the first n software assets which best meet the requirements of the developers according to the similarity of the behaviors of the developers and the behavior predicted value.
5. A GitHub-based software asset recommendation system comprising the following modules: the system comprises a developer information acquisition module (203), a software asset information acquisition module (202), a software asset information construction module (210), a developer behavior information construction module (209), a target developer behavior information acquisition module (211), a target developer software asset information acquisition module (212), a similar developer behavior information acquisition module (214), a similar developer software asset information acquisition module (213) and a Top-n recommendation software asset display module (215);
the developer information acquisition module (203) and the software asset information acquisition module (202) are respectively connected with a data warehouse (201) in the GitHub platform to acquire software asset information and developer information;
the developer information includes: the account ID information of the developers and the behavior information of different developers on the software assets;
the developer information acquisition module (203) sends developer information to the developer behavior information construction module (209), and the developer behavior information construction module (209) sequentially generates behavior information of developers with different account ID information on software assets correspondingly;
the target developer behavior information acquisition module (211) searches all developers of the developer behavior information construction module (209), acquires the behavior information of the target developer corresponding to the target developer, and records different behaviors according to the behavior with the highest weight;
the software asset information acquisition module (202) sends the acquired software asset information to a software asset information construction module (210) to generate ID information of each software asset, url information of each software asset and the name of each software asset, and the total behavior times of a developer are recorded in the url of each software asset;
a target developer software asset information acquisition module (212) acquires the behavior information of the target developer corresponding to the target developer, which is sent by a target developer behavior information acquisition module (211);
the target developer behavior information acquisition module (211) sends behavior information of the target developer to the similar developer behavior information acquisition module (214), and the similar developer behavior information acquisition module (214) generates similar developer behavior information;
the target developer software asset information acquisition module (212) provides a software asset set of target developer behaviors for the similar developer behavior information acquisition module (214), and the similar developer behavior information acquisition module (214) generates a software asset set of similar developers which have jointly behaviors;
the target developer software asset information acquisition module (212) sends the software asset information of the target developer to the software asset information acquisition module (213) of the similar developer, and the software asset information acquisition module (213) of the similar developer generates the software asset information of the similar developer;
the software asset information acquisition module (213) of the similar developer provides the software asset information of the similar developer for the behavior information acquisition module (214) of the similar developer, and the behavior information acquisition module (214) of the similar developer generates the behavior information of the similar developer to the software asset according to the software asset information of the similar developer provided by the software asset information acquisition module (213) of the similar developer;
a similar developer behavior information acquisition module (214) and a similar developer software asset information acquisition module (213) acquire similar behaviors and behavior software asset information of similar developers by using developer behavior measurement similarity, and then send the information to a Top-n recommendation software asset display module (215);
and the Top-n recommendation software asset display module (215) comprehensively recommends the Top-n software asset which best meets the requirements of the target developer according to the behavior prediction technology and the collaborative filtering recommendation algorithm.
6. The GitHub-based software asset recommendation system according to claim 5, wherein said developer behavior information building module (209) further comprises: the method comprises the following steps that a developer searches for a building module (205), browses the building module (204), downloads the building module (206), edits the building module (207) and submits the building module (208);
the behavior information of the developer on the software assets comprises: searching, browsing, downloading, editing and submitting;
the developer search building module (205) is used for recording a software asset list searched by the developer, the developer browse building module (204) is used for recording a software asset list browsed by the developer, the developer download building module (206) is used for recording a software asset list downloaded by the developer, the developer edit building module (207) is used for recording a software development code list edited by the developer, and the developer submission building module (208) is used for recording a software asset list submitted by the developer.
7. The GitHub-based software asset recommendation system according to claim 5, wherein said software asset information comprises: software discovery information, software licensing information, software usage information, software version information, software patch information, software development information, code development information.
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