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API recommendation system for software development

机译:用于软件开发的API推荐系统

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Nowadays, software developers often utilize existing third party libraries and make use of Application Programming Interface (API) to develop a software. However, it is not always obvious which library to use or whether the chosen library will play well with other libraries in the system. Furthermore, developers need to spend some time to understand the API to the point that they can freely use the API methods and putting the right parameters inside them. In this work, I plan to automatically recommend relevant APIs to developers. This API recommendation can be divided into multiple stages. First, we can recommend relevant libraries provided a given task to complete. Second, we can recommend relevant API methods that developer can use to program the required task. Third, we can recommend correct parameters for a given method according to its context. Last but not least, we can recommend how different API methods can be combined to achieve a given task. In effort to realize this API recommendation system, I have published two related papers. The first one deals with recommending additional relevant API libraries given known useful API libraries for the target program. This system can achieve recall rate@5 of 0.852 and recall rate@10 of 0.894 in recommending additional relevant libraries. The second one deals with recommending relevant API methods a given target API and a textual description of the task. This system can achieve recall-rate@5 of 0.690 and recall-rate@10 of 0.779. The results for both system indicate that the systems are useful and capable in recommending the right API/library reasonably well. Currently, I am working on another system which can recommend web APIs (i.e., libraries) given a description of the task. I am also working on a system that recommends correct parameters given an API method. In the future, I also plan to realize API composition recommendation for the given task.
机译:如今,软件开发人员经常利用现有的第三方库并利用应用程序编程接口(API)来开发软件。但是,使用哪个库或所选的库是否可以与系统中的其他库配合使用并不总是很明显。此外,开发人员需要花费一些时间来理解API,以便他们可以自由使用API​​方法并将正确的参数放入其中。在这项工作中,我计划自动向开发人员推荐相关的API。该API建议可以分为多个阶段。首先,我们可以建议相关的库提供给定的任务来完成。其次,我们可以推荐相关的API方法,供开发人员用来对所需的任务进行编程。第三,我们可以根据上下文为给定方法推荐正确的参数。最后但并非最不重要的一点是,我们可以建议如何结合使用不同的API方法来完成给定的任务。为了实现此API推荐系统,我发表了两篇相关论文。第一个涉及推荐给目标程序已知有用的API库的其他相关API库。在推荐其他相关库时,该系统可以实现0.852的5的召回率和0.894的10的召回率。第二部分涉及推荐相关的API方法,给定的目标API和任务的文本描述。该系统可以实现0.690的5召回率和0.779的10召回率。两个系统的结果都表明,这些系统在合理合理地推荐正确的API /库方面非常有用并且能够胜任。目前,我正在另一个系统上工作,该系统可以在给出任务说明的情况下推荐Web API(即库)。我还在研究一种建议使用API​​方法的正确参数的系统。将来,我还计划为给定任务实现API组成建议。

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