Complementing global and local contexts in representing API descriptions to improve API retrieval tasks

Nguyen, Thanh V.; Tran, Ngoc Mai; Phan, Hung; Nguyen, Trong Duc; Truong, Linh H.; Nguyen, Anh Tuan; Nguyen, Hoan Anh; Nguyen, Tien N.

doi:10.1145/3236024.3236036

Cited by 20 publications

(6 citation statements)

References 35 publications

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“…Zhao et al [17] propose the DeepSim technique where the control flow and data flow of a piece of code is encoded into a semantic matrix and a deep learning model is developed to measure code functional similarity based on this representation. Nguyen et al [18] develop the D2Vec neural network model to compute the vector representations for the APIs. The model maintains the global context of the current API topic under description and the local orders of words and APIs in the text phrases, which helps to capture the semantics of API documentation.…”

Section: Code Searchmentioning

confidence: 99%

“…Since no semantic information is taken into account when deciding whether a piece of code should be considered as a match during the search, keyword-based search often produce results that are irrelevant. To improve the search result quality, various semantics-based code search techniques have been developed in the past few years [2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18], among which techniques for example-based code search have yielded promising results [3,19,20,21]. In example-based code search, a query typically contains a set of examples specifying the desired input/output (IO) behaviors of the target code.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Enhancing example-based code search with functional semantics

Chen

Jiang

Zhang

et al. 2020

Journal of Systems and Software

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Section: Code Searchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Enhancing example-based code search with functional semantics

Chen

Jiang

Zhang

et al. 2020

Journal of Systems and Software

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“…Other studies have also exploited different aspects of APIs and natural language to better retrieve the APIs and their related information. The techniques include: using global and local contexts of the queries [26], leveraging usage similarity for effective retrieval of API examples [27], employing word embeddings to document similarities for improved API retrieval [28], exploiting user knowledge [29], and task-API knowledge gap [30] during retrieval of semantically annotated API operations.…”

Section: B Api Resource Retrievalmentioning

confidence: 99%

FACOS: Finding API Relevant Contents on Stack Overflow with Semantic and Syntactic Analysis

Luong¹,

Hadi²,

Thung³

et al. 2021

Preprint

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Collecting API examples, usages, and mentions relevant to a specific API method over discussions on venues such as Stack Overflow is not a trivial problem. It requires efforts to correctly recognize whether the discussion refers to the API method that developers/tools are searching for. The content of the thread, which consists of both text paragraphs describing the involvement of the API method in the discussion and the code snippets containing the API invocation, may refer to the given API method. Leveraging this observation, we develop FACOS, a context-specific algorithm to capture the semantic and syntactic information of the paragraphs and code snippets in a discussion. FACOS combines a syntactic word-based score with a score from a predictive model fine-tuned from CodeBERT. FACOS beats the state-of-the-art approach by 13.9% in terms of F1-score.

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“…The recent advances in Artificial Intelligence (AI), NLP and Natural Language Undersdanding (NLU) are a good fit to address these issues given the unstructured nature of large parts of API documentation. Initial attempts along these lines include the use of NLP for Web APIs documentation [125], API embeddings for API usage/application [126] and API document embeddings [127]. We argue that further research is needed to assess API documentation quality, e.g., by leveraging embedding technologies on top of both structured (API formal specification) and unstructured data (API documentation).…”

Section: Disscussion and Threat To Validitymentioning

confidence: 99%

Scout-bot: Leveraging API Community Knowledge for Exploration and Discovery of API Learning Resources

Ajam

Rodríguez

Benatallah

2021

CLEIej

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Application Programming Interface (API) is a core technology that facilitates developers’ productivity by enabling the reuse of software components. Understanding APIs and gaining knowledge about their usage are therefore fundamental needs for developers. Here, API documentation plays a pivotal role in enabling developers to take full advantage of the benefits brought by APIs. The quality of API documentation has therefore become an important concern given the celerity and dynamics at which APIs are now being made available to users. This article aims at exploring existing research in the area of API documentation in order to identify the associated quality dimensions addressed by the literature. The research is carried out as a systematic mapping study where 103 research papers selected from the literature were reviewed and a total of 5 core quality dimensions were identified and analyzed. By focusing on the two most relevant quality dimensions (understandability and completeness), this article presents an approach to enable API users to explore, discover and learn about APIs through API topic issues discussed in Stack Overflow (SO). We demonstrate the feasibility of our approach through Scout-bot, our tool for exploration and discovery of API topic issues.

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Complementing global and local contexts in representing API descriptions to improve API retrieval tasks

Cited by 20 publications

References 35 publications

Enhancing example-based code search with functional semantics

Enhancing example-based code search with functional semantics

FACOS: Finding API Relevant Contents on Stack Overflow with Semantic and Syntactic Analysis

Scout-bot: Leveraging API Community Knowledge for Exploration and Discovery of API Learning Resources

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