Abstract
As developers rely more and more on reusing components from online sources, an important challenge is that of finding snippets in order to integrate these components and/or to address common programming problems. Thus, several snippet mining systems have been developed, which however have important limitations. API usage mining systems require the developer to know which library to use beforehand, while more generic snippet mining systems usually output a list of examples, without distinguishing among different implementations and without assessing the quality and the reusability of the proposed snippets. In this chapter, we present CodeCatch, a system that receives queries in natural language and assesses the retrieved snippets both for their quality and for their preference by the developers. Furthermore, our system clusters the snippets according to their API calls, thus allowing the developer to select among the different implementations. We provide an example usage scenario for CodeCatch and evaluate it in a set of programming queries to illustrate how it can be useful for the developer.
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Notes
- 1.
As already mentioned in the previous chapters, the Google Code Search Engine resided in http://www.google.com/codesearch, however, the service was discontinued in 2013.
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- 3.
As a side note, this local index is only used to assess the reusability of the components; our search, however, is not limited within it (as is the case with other systems) as we employ a search engine and crawl multiple pages. To further ensure that our reusability evaluator is always up-to-date, we could rebuild its index along with the rebuild cycles of the index of AGORA.
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Diamantopoulos, T., Symeonidis, A.L. (2020). Mining Source Code for Snippet Reuse. In: Mining Software Engineering Data for Software Reuse. Advanced Information and Knowledge Processing. Springer, Cham. https://doi.org/10.1007/978-3-030-30106-4_7
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