技术领域Technical Field
本发明涉及计算机技术领域，特别是涉及一种开源组件的动态评分方法、系统、及计算机储存介质。The present invention relates to the field of computer technology, and in particular to a dynamic scoring method and system for open source components, and a computer storage medium.
背景技术Background Art
开源组件，指的是通过开源许可证声明该软件在指定条件下可用于商业应用，再进行分发和使用，从而使其成为商业和非商业软件项目中的受欢迎的选择。Open source components refer to software that is distributed and used under specified conditions and declared to be available for commercial applications through an open source license, making it a popular choice in commercial and non-commercial software projects.
但是，功能相同、相似的开源组件在开源社区中通常有很多。这是因为在软件开发中存在各种技术和框架，不同的开发者会选择不同的技术栈来实现类似的功能，这就会产生有多个功能相似但实现方式不同的开源组件。参差不齐的开源组件给用户在选择时造成了极大的困难。However, there are usually many open source components with the same or similar functions in the open source community. This is because there are various technologies and frameworks in software development, and different developers will choose different technology stacks to implement similar functions, which will result in multiple open source components with similar functions but different implementation methods. The uneven open source components make it extremely difficult for users to choose.
目前，用户对相似开源组件进行评分的方法通常为对待测开源组件的表现效果与相似开源组件的整体表现效果进行比较分析，该评分方法会因为计算量大而造成分析困难，而且由于大多数开源组件的开发是不能进行实际应用的，因此将待测开源组件与相似开源组件的整体效果进行对比评分的方法得到的评分不准确。At present, the method for users to score similar open source components is usually to compare and analyze the performance of the open source component to be tested with the overall performance of similar open source components. This scoring method will cause analysis difficulties due to the large amount of calculation, and because most open source components are developed and cannot be used in practice, the scoring obtained by comparing the overall performance of the open source component to be tested with similar open source components is inaccurate.
发明内容Summary of the invention
本发明要解决的技术问题是：解决目前对开源组件进行评分的方法不够准确的问题。The technical problem to be solved by the present invention is to solve the problem that the current method for scoring open source components is not accurate enough.
为了解决上述技术问题，本发明提供了一种开源组件的动态评分方法，所述评分方法包括：In order to solve the above technical problems, the present invention provides a dynamic scoring method for open source components, the scoring method comprising:
获取若干与待测开源组件功能相似的相似开源组件的信息数据，选取最优的所述相似开源组件的信息数据作为最优数据，所述最优数据包括所述相似开源组件的最优引入量、所述相似开源组件的最优评分、某公司对所述相似开源组件的最优引入量、所述相似开源组件的最优偏差、所述相似开源组件中最少的一个开源组件的高危安全漏洞的个数、所述相似开源组件中最少的一个开源组件的中危安全漏洞的个数、所述相似开源组件中最少的一个开源组件的低危安全漏洞的个数、所述相似开源组件中最少的一个开源组件的提示级安全漏洞的个数、所述相似开源组件中最少的一个开源组件的高危功能漏洞的个数、所述相似开源组件中最少的一个开源组件的中危功能漏洞的个数、所述相似开源组件中最少的一个开源组件的低危功能漏洞的个数、所述相似开源组件中最少的一个开源组件的提示级功能漏洞的个数、所述相似开源组件中的一个开源组件最短的响应时间、所述相似开源软件中的更新最多的开源组件的更新次数、所述相似开源组件的许可总类型数最多的开源组件的许可类型数；Obtain information data of several similar open source components with similar functions to the open source component to be tested, select the best information data of the similar open source components as the best data, the best data includes the best introduction amount of the similar open source components, the best score of the similar open source components, the best introduction amount of the similar open source components by a certain company, the best deviation of the similar open source components, the number of high-risk security vulnerabilities of the least open source component among the similar open source components, the number of medium-risk security vulnerabilities of the least open source component among the similar open source components, the number of low-risk security vulnerabilities of the least open source component among ... the number of warning-level security vulnerabilities of the least open source component among the similar open source components, the number of high-risk functional vulnerabilities of the least open source component among the similar open source components, the number of medium-risk functional vulnerabilities of the least open source component among the similar open source components, the number of low-risk functional vulnerabilities of the least open source component among the similar open source components, the number of warning-level functional vulnerabilities of the least open source component among the similar open source components, the shortest response time of an open source component among the similar open source components, the number of updates of the most updated open source component among the similar open source software, and the number of license types of the open source component with the largest total number of license types among the similar open source components;
根据所述最优数据对所述待测开源组件的使用频率的分值a1、方法稳定性的分值a2、安全漏洞的分值a3、功能漏洞的分值a4、性能的分值a5、更新频率的分值a6、许可类型的分值a7分别进行单独计算；According to the optimal data, the score a1 of the usage frequency of the open source component to be tested, the score a2 of the method stability, the score a3 of the security vulnerability, the score a4 of the functional vulnerability, the score a5 of the performance, the score a6 of the update frequency, and the score a7 of the license type are calculated separately;
根据所述使用频率的分值a1、方法稳定性的分值a2、安全漏洞的分值a3、功能漏洞的分值a4、性能的分值a5、更新频率的分值a6、许可类型的分值a7的重要程度，分别确定每个分值a＝{a1,a2,a3,……，a7}对应的权重k＝{k1,k2,k3,……k7}；According to the importance of the usage frequency score a1 , the method stability score a2 , the security vulnerability score a3 , the functional vulnerability score a4 , the performance score a5 , the update frequency score a6 , and the license type score a7 , respectively determine the weight k = {k1 , k2 , k3 , ..., k7 } corresponding to each score a = {a1 , a2 , a3 , ..., a7 };
根据所述权重k和所述分值a得到所述待测开源组件的综合评分s，所述综合评分s的计算公式为s＝a1*k1+a2*k2+a3*k3+……a7*k7。A comprehensive score s of the open source component to be tested is obtained according to the weight k and the score a, and a calculation formula of the comprehensive score s is s=a1 *k1 +a2 *k2 +a3 *k3 + ...a7 *k7 .
更进一步地，所述使用频率的分值a1的计算公式为Furthermore, the calculation formula of the usage frequency scorea1 is:
其中，a1为使用频率的评分分值，Q为所述待测开源组件的网络引入量，Q优为所述相似开源组件的最优引入量，P为所述待测开源组件的网络评分,P优为所述相似开源组件的最优评分，M为某公司对所述待测开源组件的引入量，M优为某公司对所述相似开源组件的最优引入量，α+β+θ＝100，25≤α＝β≤30。Among them,a1 is the score of usage frequency, Q is the network introduction amount of the open source component to be tested, Qis the optimal introduction amount of the similar open source components, P is the network score of the open source component to be tested, Pis the optimal score of the similar open source components, M is the introduction amount of the open source component to be tested by a certain company, Mis the optimal introduction amount of the similar open source components by a certain company, α+β+θ=100, 25≤α=β≤30.
更进一步地，所述方法稳定性的分值a2的计算公式为Furthermore, the calculation formula of the stability scorea2 of the method is:
其中，a2为使用频率的评分分值，d优为所述相似开源组件的最优偏差，d为所述待测开源组件在一定运行次数中产生的偏差次数。Wherein, a2 is the score of the frequency of use, dis the optimal deviation of the similar open source components, and d is the number of deviations generated by the open source component to be tested in a certain number of runs.
更进一步地，所述安全漏洞的分值a3的计算公式为Furthermore, the calculation formula of the security vulnerability scorea3 is:
其中，a3为安全漏洞的评分分值，U1为所述待测开源组件的高危安全漏洞的个数，V1为所述待测开源组件的中危安全漏洞的个数，W1为所述待测开源组件的低危安全漏洞的个数，X1为所述待测开源组件的提示级安全漏洞的个数，U1优为在所述相似开源组件中最少的一个开源组件的高危安全漏洞的个数，V1优为在所述相似开源组件中最少的一个开源组件的中危安全漏洞的个数，W1优为在所述相似开源组件中最少的一个开源组件的低危安全漏洞的个数，X1优为在所述相似开源组件中最少的一个开源组件的提示级安全漏洞的个数。Among them,a3 is the scoring score of the security vulnerability,U1 is the number of high-risk security vulnerabilities of the open source component to be tested,V1 is the number of medium-risk security vulnerabilities of the open source component to be tested,W1 is the number of low-risk security vulnerabilities of the open source component to be tested,X1 is the number of warning-level security vulnerabilities of the open source component to be tested, U1is the number of high-risk security vulnerabilities of the open source component with the least number of similar open source components, V1is the number of medium-risk security vulnerabilities of the open source component with the least number of similar open source components, W1is the number of low-risk security vulnerabilities of the open source component with the least number of similar open source components, and X1is the number of warning-level security vulnerabilities of the open source component with the least number of similar open source components.
更进一步地，所述功能漏洞的分值a4的计算公式为Furthermore, the calculation formula of the score a4 of the functional vulnerability is:
其中a4为功能漏洞的评分分值，U2为所述待测开源组件的高危功能漏洞的个数，V2为所述待测开源组件的中危功能漏洞的个数，W2所述待测的开源组件的低危功能漏洞的个数，X2为所述待测开源组件的提示级功能漏洞的个数，U2优为在所述相似开源组件中最少的一个开源组件的高危功能漏洞的个数，V2优为在所述相似开源组件中最少的一个开源组件的中危功能漏洞的个数，W2优为在所述相似开源组件中最少的一个开源组件的低危功能漏洞的个数，X2优为在所述相似开源组件中最少的一个开源组件的提示级功能漏洞的个数。Whereina4 is the scoring value of the functional vulnerability,U2 is the number of high-risk functional vulnerabilities of the open source component to be tested,V2 is the number of medium-risk functional vulnerabilities of the open source component to be tested,W2 is the number of low-risk functional vulnerabilities of the open source component to be tested,X2 is the number of warning-level functional vulnerabilities of the open source component to be tested, U2is the number of high-risk functional vulnerabilities of the open source component with the least number of similar open source components,V2 is the number of medium-risk functional vulnerabilities of the open source component with the least number of similar open source components, W2is the number of low-risk functional vulnerabilities of the open source component with the least number of similar open source components, and X2is the number of warning-level functional vulnerabilities of the open source component with the least number of similar open source components.
更进一步地，所述性能的分值a5的计算公式为Furthermore, the calculation formula of the performance scorea5 is:
其中，a5为性能评分的评分分值，t为所述待测开源组件的响应时间，t优为所述相似开源组件中的一个开源组件最短的响应时间。Wherein, a5 is the score of the performance score, t is the response time of the open source component to be tested, and tbest is the shortest response time of an open source component among the similar open source components.
更进一步地，所述更新频率的分值a6的计算公式为Furthermore, the calculation formula of the update frequency scorea6 is:
其中，a6为更新频率的评分分值，e为待测开源组件的更新次数，e优为所述相似开源软件中的更新最多的开源组件的更新次数。Wherein, a6 is the score of the update frequency, e is the update number of the open source component to be tested, and eis the update number of the most updated open source component among the similar open source software.
更进一步地，所述许可类型的分值a7的计算公式为Furthermore, the calculation formula of the scorea7 of the license type is:
其中，a7为许可类型的评分分值，m为所述待测开源组件的许可类型数，m优为所述相似开源组件的许可总类型数最多的开源组件的许可类型数。Wherein,a7 is the score of the license type, m is the number of license types of the open source component to be tested, andmbest is the number of license types of the open source component with the largest total number of license types of the similar open source components.
根据本发明的另一方面，本发明提供一种开源组件的动态评分系统，包括：According to another aspect of the present invention, the present invention provides a dynamic scoring system for open source components, comprising:
信息筛选模块，获取若干与待测开源组件功能相似的相似开源组件的信息数据，选取最优的所述相似开源组件的信息数据作为最优数据，所述最优数据包括所述相似开源组件的最优引入量、所述相似开源组件的最优评分、某公司对所述相似开源组件的最优引入量、所述相似开源组件的最优偏差、所述相似开源组件中最少的一个开源组件的高危安全漏洞的个数、所述相似开源组件中最少的一个开源组件的中危安全漏洞的个数、所述相似开源组件中最少的一个开源组件的低危安全漏洞的个数、所述相似开源组件中最少的一个开源组件的提示级安全漏洞的个数、所述相似开源组件中最少的一个开源组件的高危功能漏洞的个数、所述相似开源组件中最少的一个开源组件的中危功能漏洞的个数、所述相似开源组件中最少的一个开源组件的低危功能漏洞的个数、所述相似开源组件中最少的一个开源组件的提示级功能漏洞的个数、所述相似开源组件中的一个开源组件最短的响应时间、所述相似开源软件中的更新最多的开源组件的更新次数、所述相似开源组件的许可总类型数最多的开源组件的许可类型数；An information screening module obtains information data of several similar open source components with similar functions to the open source component to be tested, selects the best information data of the similar open source components as the best data, and the best data includes the best introduction amount of the similar open source components, the best score of the similar open source components, the best introduction amount of the similar open source components by a certain company, the best deviation of the similar open source components, the number of high-risk security vulnerabilities of the least open source component among the similar open source components, the number of medium-risk security vulnerabilities of the least open source component among the similar open source components, the number of low-risk security vulnerabilities of the least open source component among the similar open source components, and the number of high-risk security vulnerabilities of the least open source component among the similar open source components. The number of warning-level security vulnerabilities of the least open source component among the open source components, the number of high-risk functional vulnerabilities of the least open source component among the similar open source components, the number of medium-risk functional vulnerabilities of the least open source component among the similar open source components, the number of low-risk functional vulnerabilities of the least open source component among the similar open source components, the number of warning-level functional vulnerabilities of the least open source component among the similar open source components, the shortest response time of an open source component among the similar open source components, the number of updates of the most updated open source component among the similar open source software, and the number of license types of the open source component with the largest total number of license types among the similar open source components;
分量计算模块，根据所述最优数据对所述待测开源组件的使用频率的分值a1、方法稳定性的分值a2、安全漏洞的分值a3、功能漏洞的分值a4、性能的分值a5、更新频率的分值a6、许可类型的分值a7分别进行单独计算；A component calculation module calculates the score a1 of the usage frequency of the open source component to be tested, the score a2 of the method stability, the score a3 of the security vulnerability, the score a4 of the functional vulnerability, the score a5 of the performance, the score a6 of the update frequency, and the score a7 of the license type, respectively, according to the optimal data;
权重确定模块，根据所述使用频率的分值a1、方法稳定性的分值a2、安全漏洞的分值a3、功能漏洞的分值a4、性能的分值a5、更新频率的分值a6、许可类型的分值a7的重要程度，分别确定每个分值a＝{a1,a2,a3,……，a7}对应的权重k＝{k1,k2,k3,……k7}；a weight determination module, determining a weight k = {k 1 , k2 ,k 3 , ..., k 7 } corresponding to each score a = {a 1 , a 2 , a 3 , ..., a 7 } according to the importance of the usage frequency score a 1 , the method stability score a 2,thesecurityvulnerabilityscorea3, the functional vulnerability score a4 , the performance score a 5 , theupdate frequency score a6 , and the license type scorea7 ;
综合计算模块，根据所述权重k和所述分值a得到所述待测开源组件的综合评分s，所述综合评分s的计算公式为s＝a1*k1+a2*k2+a3*k3+……a7*k7。A comprehensive calculation module obtains a comprehensive score s of the open source component to be tested according to the weight k and the score a, wherein a calculation formula of the comprehensive score s is s=a1 *k1 +a2 *k2 +a3 *k3 + ...a7 *k7 .
根据本发明的另一方面，提供了一种存储有计算机指令的非瞬时计算机可读存储介质，其中，该计算机指令用于使计算机执行本发明实施例中任一相似开源组件的动态评分方法。According to another aspect of the present invention, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable a computer to execute any dynamic scoring method for similar open source components in an embodiment of the present invention.
本发明实施例一种开源组件的动态评分方法与现有技术相比，其有益效果在于：Compared with the prior art, the dynamic scoring method for open source components in the embodiment of the present invention has the following beneficial effects:
本发明实施例通过引入相似开源组件的最佳数据，将相似开源组件中最佳的数据作为参考样本，这些数据代表了在同类开源组件中被广泛接受和认可的特征和质量标准，引入相似开源组件的最佳数据可以增强对待测开源组件的评分过程的透明度和可信度，让评分依据更具有参考性和普适性，使得评分结果更具说服力，进而提高待测开源组件的评分的准确性。The embodiment of the present invention introduces the best data of similar open source components and uses the best data among similar open source components as reference samples. These data represent the characteristics and quality standards that are widely accepted and recognized in similar open source components. Introducing the best data of similar open source components can enhance the transparency and credibility of the scoring process of the open source components to be tested, make the scoring basis more referenceable and universal, and make the scoring results more convincing, thereby improving the accuracy of the scoring of the open source components to be tested.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
图1是本发明实施例提供的开源组件的动态评分方法的流程图；FIG1 is a flow chart of a dynamic scoring method for open source components provided by an embodiment of the present invention;
图2是本发明实施例提供的开源组件的动态评分系统的示意图；FIG2 is a schematic diagram of a dynamic scoring system for open source components provided by an embodiment of the present invention;
图3是用来实现本发明实施例的电子设备的框图。FIG. 3 is a block diagram of an electronic device for implementing an embodiment of the present invention.
图中，10、信息筛选模块；20、分量计算模块；30、权重确定模块；40、综合计算模块；600、电子设备；601、计算单元；602、ROM；603、RAM；604、总线；605、I/O接口；606、输入单元；607、输出单元；608、存储单元；609、通信单元。In the figure, 10, information screening module; 20, component calculation module; 30, weight determination module; 40, comprehensive calculation module; 600, electronic device; 601, calculation unit; 602, ROM; 603, RAM; 604, bus; 605, I/O interface; 606, input unit; 607, output unit; 608, storage unit; 609, communication unit.
具体实施方式DETAILED DESCRIPTION
以下结合附图对本发明的示范性实施例作出说明，其中包括本发明实施例的各种细节以助于理解，应当将它们认为仅仅是示范性的。因此，本领域普通技术人员应当认识到，可以对这里描述的实施例做出各种改变和修改，而不会背离本发明的范围。同样，为了清楚和简明，以下的描述中省略了对公知功能和结构的描述。The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present invention. Similarly, for clarity and conciseness, the description of well-known functions and structures is omitted in the following description.
如图1所示，在本发明的一个可选实施例中，所述评分方法包括：As shown in FIG1 , in an optional embodiment of the present invention, the scoring method includes:
S1,获取若干与待测开源组件功能相似的相似开源组件的信息数据，选取最优的所述相似开源组件的信息数据作为最优数据，所述最优数据包括所述相似开源组件的最优引入量、所述相似开源组件的最优评分、某公司对所述相似开源组件的最优引入量、所述相似开源组件的最优偏差、所述相似开源组件中最少的一个开源组件的高危安全漏洞的个数、所述相似开源组件中最少的一个开源组件的中危安全漏洞的个数、所述相似开源组件中最少的一个开源组件的低危安全漏洞的个数、所述相似开源组件中最少的一个开源组件的提示级安全漏洞的个数、所述相似开源组件中最少的一个开源组件的高危功能漏洞的个数、所述相似开源组件中最少的一个开源组件的中危功能漏洞的个数、所述相似开源组件中最少的一个开源组件的低危功能漏洞的个数、所述相似开源组件中最少的一个开源组件的提示级功能漏洞的个数、所述相似开源组件中的一个开源组件最短的响应时间、所述相似开源软件中的更新最多的开源组件的更新次数、所述相似开源组件的许可总类型数最多的开源组件的许可类型数；S2,根据所述最优数据对所述待测开源组件的使用频率的分值a1、方法稳定性的分值a2、安全漏洞的分值a3、功能漏洞的分值a4、性能的分值a5、更新频率的分值a6、许可类型的分值a7分别进行单独计算；S3,根据所述使用频率的分值a1、方法稳定性的分值a2、安全漏洞的分值a3、功能漏洞的分值a4、性能的分值a5、更新频率的分值a6、许可类型的分值a7的重要程度，分别确定每个分值a＝{a1,a2,a3,……，a7}对应的权重k＝{k1,k2,k3,……k7}；S4,根据所述权重k和所述分值a得到所述待测开源组件的综合评分s，所述综合评分s的计算公式为s＝a1*k1+a2*k2+a3*k3+……a7*k7。S1, obtaining information data of several similar open source components with similar functions to the open source component to be tested, selecting the best information data of the similar open source components as the best data, wherein the best data includes the best introduction amount of the similar open source components, the best score of the similar open source components, the best introduction amount of the similar open source components by a certain company, the best deviation of the similar open source components, the number of high-risk security vulnerabilities of the least open source component among the similar open source components, the number of medium-risk security vulnerabilities of the least open source component among the similar open source components, the number of low-risk security vulnerabilities of the least open source component among the similar open source components, the number of the least open source component among the similar open source components, and the number of the least open source component among the similar open source components. S2, the number of warning-level security vulnerabilities, the number of high-risk functional vulnerabilities of the least open source component among the similar open source components, the number of medium-risk functional vulnerabilities of the least open source component among the similar open source components, the number of low-risk functional vulnerabilities of the least open source component among the similar open source components, the number of warning-level functional vulnerabilities of the least open source component among the similar open source components, the shortest response time of an open source component among the similar open source components, the number of updates of the most updated open source component among the similar open source software, and the number of license types of the open source component with the largest total number of license types of the similar open source components; S3, the score a of the usage frequency of the open source component to be tested according to the optimal data1 , the scorea2 of method stability, the scorea3 of security vulnerability, the scorea4 of functional vulnerability, the scorea5 of performance, the scorea6 of update frequency, and the scorea7 of license type are calculated separately; S3, according to the importance of the scorea1 of usage frequency, the scorea2 of method stability, the scorea3 of security vulnerability, the scorea4 of functional vulnerability, the scorea5 of performance, the scorea6 of update frequency, and the scorea7 of license type, the weight k={k1 ,k2 ,k3 ,...k7 } corresponding to each score a={a1 ,a2 ,a3 ,...,a7 } is determined respectively; S4, according to the weight k and the score a, a comprehensive score s of the open source component to be tested is obtained, and the calculation formula of the comprehensive score s is s=a1 *k1 +a2 *k2 +a3 *k3 + … a7 *k7 .
其中，使用频率的分值a1指的是该开源组件被用户使用的频率或者被其他软件项目所采用的频率，它反映了该组件在实际应用中的普及程度或者被广泛采用的程度。方法稳定性的分值指的是开源组件中提供的方法或功能的稳定性程度。这包括了方法的可靠性、稳定性和容错性，它反映了开发者在使用该组件时能够依赖其提供的功能而不会出现意外行为或崩溃的程度。安全漏洞的分值指的是开源组件存在安全漏洞的程度。这包括已知的漏洞数量、漏洞的严重程度以及对这些漏洞的及时修复程度。安全漏洞是指可能被黑客利用或导致系统遭受损害的软件缺陷或漏洞。Among them, the frequency of use score a1 refers to the frequency with which the open source component is used by users or adopted by other software projects, which reflects the popularity of the component in actual applications or the degree to which it is widely adopted. The method stability score refers to the stability of the methods or functions provided in the open source component. This includes the reliability, stability and fault tolerance of the method, which reflects the extent to which developers can rely on the functions provided by the component without unexpected behavior or crashes when using it. The security vulnerability score refers to the extent to which the open source component has security vulnerabilities. This includes the number of known vulnerabilities, the severity of the vulnerabilities, and the degree to which these vulnerabilities are promptly fixed. Security vulnerabilities refer to software defects or loopholes that can be exploited by hackers or cause damage to the system.
具体地，在步骤S2中，最优数据的筛选根据其功能、用途、等特征来确定，例如在引入量这个影响待测开源组件的评分的因子中，其包含的最佳数据为相似开源组件的最大引入量；在安全漏洞这个影响待测开源组件的评分的因子中，其包含的最佳数据为相似开源组件最少的漏洞个数量；在更新次数这个影响待测开源组件的评分的因子中，其包含的最佳数据为相似开源组件更新次数最多的量。Specifically, in step S2, the screening of optimal data is determined based on its function, purpose, and other characteristics. For example, in the factor of introduction quantity that affects the score of the open source component to be tested, the optimal data included is the maximum introduction quantity of similar open source components; in the factor of security vulnerabilities that affects the score of the open source component to be tested, the optimal data included is the minimum number of vulnerabilities in similar open source components; in the factor of number of updates that affects the score of the open source component to be tested, the optimal data included is the maximum number of updates of similar open source components.
具体地，在S2中，根据各个所述因子之间的重要程度确定各个因子对应的权重，该重要程度可以通过分析已知数据或历史记录来确定权重。例如，可以分析过去的问题报告、安全漏洞修复速度、用户反馈等数据来估算各因素的重要性，从而确定权重；也可以使用主观分析法，即通过团队讨论或专家意见来确定权重，对各个所述因子进行讨论和投票，然后根据投票结果确定权重。Specifically, in S2, the weights corresponding to the factors are determined according to the importance of the factors, and the importance can be determined by analyzing known data or historical records. For example, the importance of each factor can be estimated by analyzing past problem reports, security vulnerability repair speed, user feedback and other data to determine the weights; subjective analysis can also be used, that is, the weights are determined through team discussions or expert opinions, and the factors are discussed and voted on, and then the weights are determined based on the voting results.
本发明实施例通过引入相似开源组件的最佳数据，将相似开源组件中评分最高的数据作为参考样本，这些数据代表了在同类开源组件中被广泛接受和认可的特征和质量标准，引入相似开源组件的最佳数据可以增强对待测开源组件的评分过程的透明度和可信度，让评分依据更具有参考性和普适性，使得评分结果更具说服力，进而提高待测开源组件的评分的准确性。The embodiment of the present invention introduces the best data of similar open source components and uses the highest-scoring data among similar open source components as reference samples. These data represent the features and quality standards that are widely accepted and recognized among similar open source components. Introducing the best data of similar open source components can enhance the transparency and credibility of the scoring process of the open source components to be tested, make the scoring basis more referenceable and universal, and make the scoring results more convincing, thereby improving the accuracy of the scoring of the open source components to be tested.
在本发明的一个可选实施例中，所述使用频率的分值a1的计算公式为In an optional embodiment of the present invention, the calculation formula of the usage frequency scorea1 is:
其中，a1为使用频率的评分分值，Q为所述待测开源组件的网络引入量，Q优为所述相似开源组件的最优引入量，P为所述待测开源组件的网络评分,P优为所述相似开源组件的最优评分，M为某公司对所述待测开源组件的引入量，M优为某公司对所述相似开源组件的最优引入量，α+β+θ＝100，25≤α＝β≤30。Among them,a1 is the score of usage frequency, Q is the network introduction amount of the open source component to be tested, Qis the optimal introduction amount of the similar open source components, P is the network score of the open source component to be tested, Pis the optimal score of the similar open source components, M is the introduction amount of the open source component to be tested by a certain company, Mis the optimal introduction amount of the similar open source components by a certain company, α+β+θ=100, 25≤α=β≤30.
其中，Q优相似开源组件的最优引入量指的是在一系列相似开源组件中所引入最多次数的量，通过待测开源组件的引入量Q与Q优的比值可以用来衡量待测开源组件在引入量方面的表现，当Q与Q优的比值接近1时，a1的分值就越高。P优为所述相似开源组件的最优评分指的是在一系列相似开源组件中所获得的最高评分的开源组件，通过待测开源组件的评分P与P优的比值可以用来衡量待测开源组件在评分方面的表现，当P与P优的比值接近1时，a1的分值就越高。Among them, the optimal introduction quantity of Q-excellent similar open source components refers to the quantity introduced the most times in a series of similar open source components. The ratio of the introduction quantity Q of the open source component to be tested to Q-excellent can be used to measure the performance of the open source component to be tested in terms of introduction quantity. When the ratio of Q to Q-excellent is close to 1, the score ofa1 is higher.P-excellent is the optimal score of the similar open source component, which refers to the open source component with the highest score in a series of similar open source components. The ratio of the score P of the open source component to be tested to P-excellent can be used to measure the performance of the open source component to be tested in terms of score. When the ratio of P to P-excellent is close to 1, the score ofa1 is higher.
在本发明实施例中，使用频率的分值a1评分计算公式通过对Q优、P优、M优的引用与待测相似开源组件的比值来确定a1的大小，该方法引入了相似开源组件关于引入量和网络评分的最优指标，将其作为a1的依据，该方法使得评分分值更具客观性。In the embodiment of the present invention, the frequency of use scorea1 scoring calculation formula determines the size ofa1 by the ratio of the references of Q-excellent , P-excellent , and M-excellent to the similar open source components to be tested. This method introduces the optimal indicators of similar open source components regarding the introduction volume and network score, and uses them as the basis fora1 . This method makes the scoring score more objective.
在本发明的一个可选实施例中，所述方法稳定性的分值a2的计算公式为In an optional embodiment of the present invention, the calculation formula of the stability scorea2 of the method is:
其中，a2为使用频率的评分分值，d优为所述相似开源组件的最优偏差，d为所述待测开源组件在一定运行次数中产生的偏差次数。Wherein, a2 is the score of the frequency of use, dis the optimal deviation of the similar open source components, and d is the number of deviations generated by the open source component to be tested in a certain number of runs.
其中，d优为所述相似开源组件的最优偏差指的是在一定时间内，一系列相似开源组件中在一定运行次数中产生最少偏差的次数。Among them, dis the optimal deviation of the similar open source components, which refers to the number of times a series of similar open source components produce the least deviation in a certain number of runs within a certain period of time.
具体地，待测开源组件的运行次数通常指的是该组件在实际使用环境中被执行或调用的次数。运行的偏差次数指的是待测开源组件在多次运行中产生的性能或行为上的差异。这种差异可能是由于环境变化、输入数据不同或者其他因素导致的。通过量化这种差异，可以评估开源组件的稳定性和可靠性。Specifically, the number of runs of the open source component under test usually refers to the number of times the component is executed or called in the actual usage environment. The number of deviations in the runs refers to the differences in performance or behavior of the open source component under test during multiple runs. This difference may be caused by changes in the environment, different input data, or other factors. By quantifying this difference, the stability and reliability of the open source component can be evaluated.
在本发明实施例中，通过引入d优作为a2的评分考量可以降低因组件在运行时表现不佳而带来的风险，这种方法有助于提高对开源组件性能的评估准确度，为用户选择合适的开源组件提供更可靠的参考依据。In the embodiment of the present invention, by introducing dexcellent as a scoring consideration for a2 , the risk caused by poor performance of components at runtime can be reduced. This method helps to improve the accuracy of evaluating the performance of open source components and provide a more reliable reference for users to select appropriate open source components.
在本发明的一个可选实施例中，所述安全漏洞的分值a3的计算公式为In an optional embodiment of the present invention, the calculation formula of the security vulnerability scorea3 is:
其中，a3为安全漏洞的评分分值，U1为所述待测开源组件的高危安全漏洞的个数，V1为所述待测开源组件的中危安全漏洞的个数，W1为所述待测开源组件的低危安全漏洞的个数，X1为所述待测开源组件的提示级安全漏洞的个数，U1优为在所述相似开源组件中最少的一个开源组件的高危安全漏洞的个数，V1优为在所述相似开源组件中最少的一个开源组件的中危安全漏洞的个数，W1优为在所述相似开源组件中最少的一个开源组件的低危安全漏洞的个数，X1优为在所述相似开源组件中最少的一个开源组件的提示级安全漏洞的个数。Among them,a3 is the scoring score of the security vulnerability,U1 is the number of high-risk security vulnerabilities of the open source component to be tested,V1 is the number of medium-risk security vulnerabilities of the open source component to be tested,W1 is the number of low-risk security vulnerabilities of the open source component to be tested,X1 is the number of warning-level security vulnerabilities of the open source component to be tested, U1is the number of high-risk security vulnerabilities of the open source component with the least number of similar open source components, V1is the number of medium-risk security vulnerabilities of the open source component with the least number of similar open source components, W1is the number of low-risk security vulnerabilities of the open source component with the least number of similar open source components, and X1is the number of warning-level security vulnerabilities of the open source component with the least number of similar open source components.
其中，具体地，安全漏洞指的是软件中存在关于软件安全方面的漏洞或缺陷，这些漏洞可以被恶意用户利用来获取未经授权的访问或执行未经授权的操作，从而对系统的安全性造成威胁。安全漏洞可能导致数据泄露、拒绝服务攻击、远程代码执行等安全问题。因此，对安全漏洞进行评分对评估开源组件至关重要。高危安全漏洞指的是软件中存在的严重漏洞或缺陷，可能导致严重的安全问题，例如远程代码执行、越权访问敏感信息、拒绝服务攻击等。这些漏洞可能会被恶意用户利用来对系统造成严重的损害或入侵。中危安全漏洞指的是软件中存在的一些漏洞或缺陷，虽然不像高危漏洞那样严重，但仍然可能对系统的安全性造成一定程度的威胁。这些漏洞可能会导致数据泄露、越权访问、身份验证问题等安全隐患。低危安全漏洞指的是软件中存在的一些漏洞或缺陷，其影响程度相对较轻，不会对系统的安全性造成严重威胁。这些漏洞可能包括一些界面问题、功能不完善、低优先级的错误等。尽管低危漏洞不会导致严重的安全问题，但它们仍然需要被记录、跟踪和修复，以确保软件的完整性和稳定性。提示级安全漏洞指的是软件中存在的一些较为轻微的问题或建议，通常不会导致实际的安全威胁，但可能会影响系统的易用性、性能或其他方面。这些漏洞可能包括一些提示性的警告或建议，例如代码风格不规范、文档不完整、优化建议等。其中，安全漏洞的评分系数反映了漏洞的严重程度和影响程度。高危漏洞具有更高的权重系数，而提示级漏洞的权重系数最低。这种评分计算公式可以帮助决策者更好地理解开源组件的安全风险，并采取相应的措施来降低这些风险Specifically, security vulnerabilities refer to vulnerabilities or defects in software security that can be exploited by malicious users to obtain unauthorized access or perform unauthorized operations, thereby threatening the security of the system. Security vulnerabilities may lead to security issues such as data leakage, denial of service attacks, and remote code execution. Therefore, scoring security vulnerabilities is crucial for evaluating open source components. High-risk security vulnerabilities refer to serious vulnerabilities or defects in software that may lead to serious security issues such as remote code execution, unauthorized access to sensitive information, and denial of service attacks. These vulnerabilities may be exploited by malicious users to cause serious damage or intrusion to the system. Medium-risk security vulnerabilities refer to some vulnerabilities or defects in software that, although not as serious as high-risk vulnerabilities, may still pose a certain degree of threat to the security of the system. These vulnerabilities may lead to security risks such as data leakage, unauthorized access, and authentication issues. Low-risk security vulnerabilities refer to some vulnerabilities or defects in software that have a relatively mild impact and will not pose a serious threat to the security of the system. These vulnerabilities may include some interface problems, imperfect functions, low-priority errors, etc. Although low-risk vulnerabilities do not cause serious security issues, they still need to be recorded, tracked, and fixed to ensure the integrity and stability of the software. Warning-level security vulnerabilities refer to some relatively minor problems or suggestions in the software, which usually do not cause actual security threats, but may affect the usability, performance or other aspects of the system. These vulnerabilities may include some suggestive warnings or suggestions, such as irregular code style, incomplete documentation, optimization suggestions, etc. Among them, the scoring coefficient of the security vulnerability reflects the severity and impact of the vulnerability. High-risk vulnerabilities have higher weight coefficients, while warning-level vulnerabilities have the lowest weight coefficient. This scoring calculation formula can help decision makers better understand the security risks of open source components and take appropriate measures to reduce these risks.
在本发明实施例中，将待测开源组件的安全漏洞情况与相似开源组件中最少安全漏洞的情况进行比值而产生的a3能够使评分更为形象准确。In the embodiment of the present invention, a3 generated by comparing the security vulnerability situation of the open source component to be tested with the situation of the least security vulnerability in similar open source components can make the scoring more vivid and accurate.
在本发明的一个实施例中，所述性能的分值a5的计算公式为In one embodiment of the present invention, the calculation formula of the performance scorea5 is:
其中，a5为性能评分的评分分值，t为所述待测开源组件的响应时间，t优为所述相似开源组件中的一个开源组件最短的响应时间。相似开源组件的最短响应时间是指在相似的开源组件中选择一个具有最短响应时间的组件，用作性能评估的基准。这意味着该组件在一定条件下(例如负载、网络环境等)能够以最快的速度响应请求。通过将待测开源组件的实际响应时间与这个最短响应时间进行比较，可以更好地评估待测开源组件的性能表现。Among them,a5 is the score of the performance score, t is the response time of the open source component to be tested, andtoptimum is the shortest response time of an open source component among the similar open source components. The shortest response time of similar open source components refers to selecting a component with the shortest response time among similar open source components as a benchmark for performance evaluation. This means that the component can respond to requests at the fastest speed under certain conditions (such as load, network environment, etc.). By comparing the actual response time of the open source component to be tested with this shortest response time, the performance of the open source component to be tested can be better evaluated.
在本发明实施例中，通过考量相似开源组件中的最优性能指标和待测开源组件的实际性能表现，可以更全面地评估待测开源组件的性能优劣。该方法可以帮助用户更准确地选择适合其需求的开源组件，提高评分的准确性。In the embodiment of the present invention, by considering the optimal performance indicators of similar open source components and the actual performance of the open source component to be tested, the performance of the open source component to be tested can be more comprehensively evaluated. This method can help users more accurately select open source components that meet their needs and improve the accuracy of scoring.
在本发明的一个可选实施例中，所述更新频率的分值a6的计算公式为In an optional embodiment of the present invention, the calculation formula of the update frequency scorea6 is:
其中，a6为更新频率的评分分值，e为待测开源组件的更新次数，e优为所述相似开源软件中的更新最多的开源组件的更新次数。Wherein, a6 is the score of the update frequency, e is the update number of the open source component to be tested, and eis the update number of the most updated open source component among the similar open source software.
具体地，该方法使用客观的数据来评估更新频率，避免了主观因素的影响；该方法将待测开源组件的更新频率与相似开源软件中的更新频率进行比较，可以更好地评估其更新频率的相对水平。该方法可以根据开源组件的更新情况进行动态调整，确保评分结果始终保持最新和准确。Specifically, this method uses objective data to evaluate update frequency, avoiding the influence of subjective factors; this method compares the update frequency of the open source component to be tested with the update frequency of similar open source software, which can better evaluate the relative level of its update frequency. This method can be dynamically adjusted according to the update status of the open source component to ensure that the scoring results are always up-to-date and accurate.
在本发明实施例中，引入相似开源软件中的更新最多的开源组件的更新次数，这种方法可以更好地衡量待测组件的更新频率相对于同类组件的更新情况，从而提供更准确的评分结果。In an embodiment of the present invention, the update times of the most updated open source components in similar open source software are introduced. This method can better measure the update frequency of the component to be tested relative to the update of similar components, thereby providing a more accurate scoring result.
在发明的一个可选实施例中，所述许可类型的分值a7的计算公式为In an optional embodiment of the invention, the calculation formula of the scorea7 of the license type is:
其中，a7为许可类型的评分分值，m为所述待测开源组件的许可类型数，m优为所述相似开源组件的许可总类型数最多的开源组件的许可类型数。Wherein,a7 is the score of the license type, m is the number of license types of the open source component to be tested, andmbest is the number of license types of the open source component with the largest total number of license types of the similar open source components.
在本发明实施例中，将待测开源组件的许可类型数与相似开源组件中许可类型数最多的开源组件的许可类型数进行比较，根据比值的大小，给予相应的评分分值，该方法给了许可类型的评分一个比较基准，增加了评分的客观性。In an embodiment of the present invention, the number of license types of the open source component to be tested is compared with the number of license types of the open source component with the largest number of license types among similar open source components, and a corresponding scoring score is given according to the size of the ratio. This method provides a comparison benchmark for the scoring of the license type and increases the objectivity of the scoring.
如图2所示，在本发明的一个实施例中，提供一种开源组件的动态评分系统，包括：As shown in FIG2 , in one embodiment of the present invention, a dynamic scoring system for open source components is provided, including:
10信息筛选模块，获取若干与待测开源组件功能相似的相似开源组件的信息数据，选取最优的所述相似开源组件的信息数据作为最优数据，所述最优数据包括所述相似开源组件的最优引入量、所述相似开源组件的最优评分、某公司对所述相似开源组件的最优引入量、所述相似开源组件的最优偏差、所述相似开源组件中最少的一个开源组件的高危安全漏洞的个数、所述相似开源组件中最少的一个开源组件的中危安全漏洞的个数、所述相似开源组件中最少的一个开源组件的低危安全漏洞的个数、所述相似开源组件中最少的一个开源组件的提示级安全漏洞的个数、所述相似开源组件中最少的一个开源组件的高危功能漏洞的个数、所述相似开源组件中最少的一个开源组件的中危功能漏洞的个数、所述相似开源组件中最少的一个开源组件的低危功能漏洞的个数、所述相似开源组件中最少的一个开源组件的提示级功能漏洞的个数、所述相似开源组件中的一个开源组件最短的响应时间、所述相似开源软件中的更新最多的开源组件的更新次数、所述相似开源组件的许可总类型数最多的开源组件的许可类型数；20分量计算模块，根据所述最优数据对所述待测开源组件的使用频率的分值a1、方法稳定性的分值a2、安全漏洞的分值a3、功能漏洞的分值a4、性能的分值a5、更新频率的分值a6、许可类型的分值a7分别进行单独计算；30权重确定模块，根据所述使用频率的分值a1、方法稳定性的分值a2、安全漏洞的分值a3、功能漏洞的分值a4、性能的分值a5、更新频率的分值a6、许可类型的分值a7的重要程度，分别确定每个分值a＝{a1,a2,a3,……，a7}对应的权重k＝{k1,k2,k3,……k7}；40综合计算模块，用于根据所述权重k和所述分值a得到所述待测开源组件的综合评分s，所述综合评分s的计算公式为s＝a1*k1+a2*k2+a3*k3+……a7*k7。10. An information screening module, which obtains information data of several similar open source components with similar functions to the open source component to be tested, selects the best information data of the similar open source components as the best data, wherein the best data includes the best introduction amount of the similar open source components, the best score of the similar open source components, the best introduction amount of the similar open source components by a certain company, the best deviation of the similar open source components, the number of high-risk security vulnerabilities of the least open source component among the similar open source components, the number of medium-risk security vulnerabilities of the least open source component among the similar open source components, the number of low-risk security vulnerabilities of the least open source component among the similar open source components, and the number of the least open source component among the similar open source components. the number of warning-level security vulnerabilities, the number of high-risk functional vulnerabilities of the least open source component among the similar open source components, the number of medium-risk functional vulnerabilities of the least open source component among the similar open source components, the number of low-risk functional vulnerabilities of the least open source component among the similar open source components, the number of warning-level functional vulnerabilities of the least open source component among the similar open source components, the shortest response time of an open source component among the similar open source components, the number of updates of the most updated open source component among the similar open source software, and the number of license types of the open source component with the largest total number of license types of the similar open source components; 20 component calculation modules, according to the optimal data, the score a of the use frequency of the open source component to be tested1 , the score a2 of method stability, the score a3 of security vulnerability, the score a4 of functional vulnerability, the score a5 of performance, the score a6 of update frequency, and the score a7 of license type are calculated separately; 30 a weight determination module, according to the importance of the score a1 of usage frequency, the score a2 of method stability, the score a3 of security vulnerability, the score a4 of functional vulnerability, the score a5 of performance, the score a6 of update frequency, and the score a7 of license type, respectively determine the weight k = {k1 , k2 , k3 , ..., k7 } corresponding to each score a = {a1 , a2 , a3 , ..., a7 }; 40 a comprehensive calculation module, for obtaining a comprehensive score s of the open source component to be tested according to the weight k and the score a, the calculation formula of the comprehensive score s is s = a1 *k1 +a2 *k2 +a3 *k3 +…a7 *k7 .
在本发明实施例中，本发明实施例通过引入相似开源组件的最佳数据，将相似开源组件中评分最高的数据作为参考样本，这些数据代表了在同类开源组件中被广泛接受和认可的特征和质量标准，引入相似开源组件的最佳数据可以增强对待测开源组件的评分过程的透明度和可信度，让评分依据更具有参考性和普适性，使得评分结果更具说服力，进而提高待测开源组件的评分的准确性。In an embodiment of the present invention, the best data of similar open source components is introduced, and the data with the highest scores among similar open source components is used as a reference sample. These data represent the characteristics and quality standards that are widely accepted and recognized in similar open source components. The introduction of the best data of similar open source components can enhance the transparency and credibility of the scoring process of the open source components to be tested, make the scoring basis more referenceable and universal, and make the scoring results more convincing, thereby improving the accuracy of the scoring of the open source components to be tested.
根据本发明的实施例，本发明还提供了一种电子设备、一种可读存储介质和一种计算机程序产品。According to an embodiment of the present invention, the present invention also provides an electronic device, a readable storage medium and a computer program product.
图示出了可以用来实施本发明的实施例的示例电子设备600的示意性框图。电子设备旨在表示各种形式的数字计算机，诸如，膝上型计算机、台式计算机、工作台、个人数字助理、服务器、刀片式服务器、大型计算机和其他适合的计算机。电子设备还可以表示各种形式的移动装置，诸如，个人数字助理、蜂窝电话、智能电话、可穿戴设备和其他类似的计算装置。本文所示的部件、它们的连接和关系、以及它们的功能仅仅作为示例，并且不意在限制本文中描述的和/或者要求的本发明的实现。The figure shows a schematic block diagram of an example electronic device 600 that can be used to implement an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and/or required herein.
如图3所示，设备600包括计算单元601，其可以根据存储在只读存储器(ROM)602中的计算机程序或者从存储单元608加载到随机访问存储器(RAM)603中的计算机程序，来执行各种适当的动作和处理。在RAM 603中，还可存储设备600操作所需的各种程序和数据。计算单元601、ROM 602以及RAM 603通过总线604彼此相连。输入/输出(I/O)接口605也连接至总线604。As shown in FIG3 , the device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 can also be stored. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to the bus 604.
设备600中的多个部件连接至I/O接口605，包括：输入单元606，例如键盘、鼠标等；输出单元607，例如各种类型的显示器、扬声器等；存储单元608，例如磁盘、光盘等；以及通信单元609，例如网卡、调制解调器、无线通信收发机等。通信单元609允许设备600通过诸如因特网的计算机网络和/或各种电信网络与其他设备交换信息/数据。A number of components in the device 600 are connected to the I/O interface 605, including: an input unit 606, such as a keyboard, a mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a disk, an optical disk, etc.; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information/data with other devices through a computer network such as the Internet and/or various telecommunication networks.
计算单元601可以是各种具有处理和计算能力的通用和/或专用处理组件。计算单元601的一些示例包括但不限于中央处理单元(CPU)、图形处理单元(GPU)、各种专用的人工智能(AI)计算芯片、各种运行机器学习模型算法的计算单元、数字信号处理器(DSP)、以及任何适当的处理器、控制器、微控制器等。计算单元601执行上文所描述的各个方法和处理，例如一种发电功率预测方法。例如，在一些实施例中，一种发电功率预测方法可被实现为计算机软件程序，其被有形地包含于机器可读介质，例如存储单元608。在一些实施例中，计算机程序的部分或者全部可以经由ROM 602和/或通信单元609而被载入和/或安装到设备600上。当计算机程序加载到RAM 603并由计算单元601执行时，可以执行上文描述的一种发电功率预测方法的一个或多个步骤。备选地，在其他实施例中，计算单元601可以通过其他任何适当的方式(例如，借助于固件)而被配置为执行一种发电功率预测方法。The computing unit 601 may be a variety of general and/or special processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 601 performs the various methods and processes described above, such as a power generation prediction method. For example, in some embodiments, a power generation prediction method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed on the device 600 via the ROM 602 and/or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of a power generation prediction method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform a power generation prediction method in any other appropriate manner (e.g., by means of firmware).
本文中以上描述的系统和技术的各种实施方式可以在数字电子电路系统、集成电路系统、现场可编程门阵列(FPGA)、专用集成电路(ASIC)、专用标准产品(ASSP)、芯片上系统的系统(SOC)、负载可编程逻辑设备(CPLD)、计算机硬件、固件、软件、和/或它们的组合中实现。这些各种实施方式可以包括：实施在一个或者多个计算机程序中，该一个或者多个计算机程序可在包括至少一个可编程处理器的可编程系统上执行和/或解释，该可编程处理器可以是专用或者通用可编程处理器，可以从存储系统、至少一个输入装置、和至少一个输出装置接收数据和指令，并且将数据和指令传输至该存储系统、该至少一个输入装置、和该至少一个输出装置。Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and/or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.
用于实施本发明的方法的程序代码可以采用一个或多个编程语言的任何组合来编写。这些程序代码可以提供给通用计算机、专用计算机或其他可编程数据处理装置的处理器或控制器，使得程序代码当由处理器或控制器执行时使流程图和/或框图中所规定的功能/操作被实施。程序代码可以完全在机器上执行、部分地在机器上执行，作为独立软件包部分地在机器上执行且部分地在远程机器上执行或完全在远程机器或服务器上执行。The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions/operations specified in the flow chart and/or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.
在本发明的上下文中，机器可读介质可以是有形的介质，其可以包含或存储以供指令执行系统、装置或设备使用或与指令执行系统、装置或设备结合地使用的程序。机器可读介质可以是机器可读信号介质或机器可读储存介质。机器可读介质可以包括但不限于电子的、磁性的、光学的、电磁的、红外的、或半导体系统、装置或设备，或者上述内容的任何合适组合。机器可读存储介质的更具体示例会包括基于一个或多个线的电气连接、便携式计算机盘、硬盘、随机存取存储器(RAM)、只读存储器(ROM)、可擦除可编程只读存储器(EPROM或快闪存储器)、光纤、便捷式紧凑盘只读存储器(CD-ROM)、光学储存设备、磁储存设备、或上述内容的任何合适组合。In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
为了提供与用户的交互，可以在计算机上实施此处描述的系统和技术，该计算机具有：用于向用户显示信息的显示装置(例如，CRT(阴极射线管)或者LCD(液晶显示器)监视器)；以及键盘和指向装置(例如，鼠标或者轨迹球)，用户可以通过该键盘和该指向装置来将输入提供给计算机。其它种类的装置还可以用于提供与用户的交互；例如，提供给用户的反馈可以是任何形式的传感反馈(例如，视觉反馈、听觉反馈、或者触觉反馈)；并且可以用任何形式(包括声输入、语音输入、或者触觉输入)来接收来自用户的输入。To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).
可以将此处描述的系统和技术实施在包括后台部件的计算系统(例如，作为数据服务器)、或者包括中间件部件的计算系统(例如，应用服务器)、或者包括前端部件的计算系统(例如，具有图形用户界面或者网络浏览器的用户计算机，用户可以通过该图形用户界面或者该网络浏览器来与此处描述的系统和技术的实施方式交互)、或者包括这种后台部件、中间件部件、或者前端部件的任何组合的计算系统中。可以通过任何形式或者介质的数字数据通信(例如，通信网络)来将系统的部件相互连接。通信网络的示例包括：局域网(LAN)、广域网(WAN)和互联网。The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communications network). Examples of communications networks include: a local area network (LAN), a wide area network (WAN), and the Internet.
计算机系统可以包括客户端和服务器。客户端和服务器一般远离彼此并且通常通过通信网络进行交互。通过在相应的计算机上运行并且彼此具有客户端-服务器关系的计算机程序来产生客户端和服务器的关系。服务器可以是云服务器，也可以为分布式系统的服务器，或者是结合了区块链的服务器。A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.
应该理解，可以使用上面所示的各种形式的流程，重新排序、增加或删除步骤。例如，本发明中记载的各步骤可以并行地执行也可以顺序地执行也可以不同的次序执行，只要能够实现本发明公开的技术方案所期望的结果，本文在此不进行限制。It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in the present invention can be achieved, and this document does not limit this.
上述具体实施方式，并不构成对本发明保护范围的限制。本领域技术人员应该明白的是，根据设计要求和其他因素，可以进行各种修改、组合、子组合和替代。任何在本发明的原则之内所作的修改、等同替换和改进等，均应包含在本发明保护范围之内。The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the principles of the present invention should be included in the protection scope of the present invention.
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| CN119829017A (en)* | 2024-11-13 | 2025-04-15 | 深圳开源互联网安全技术有限公司 | Open source component selection method and system based on post maintenance support |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119829017A (en)* | 2024-11-13 | 2025-04-15 | 深圳开源互联网安全技术有限公司 | Open source component selection method and system based on post maintenance support |
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