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Methods for Categorizing and Recommending api usage patterns Based on Degree Centralities and pattern Distances

JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 2018年第3期34卷 593-610页

作者： Lee, Shin-Jie Su, Wu-Chen Huang, Chi-En You, Jie-Lin Natl Cheng Kung Univ Comp & Network Ctr Tainan 701 Taiwan Natl Cheng Kung Univ Dept Comp Sci & Informat Engn Tainan 701 Taiwan Univ Kentucky Dept Clin Sci Lexington KY 40506 USA

api usage patterns have been considered as significant materials in reusing software library apis for saving development time and improving software quality. Although efforts have been made on discovering and searching api usage patterns, the following two issues are still largely unexplored: how to provide a well-organised view of the discovered api usage patterns? and how to recommend follow-up api usage patterns once a usage pattern is adopted? This paper proposes two methods for categorizing and recommending api usage patterns: first, categories of the usage patterns are automatically identified based on a proposed degree centrality-based clustering algorithm;and second, follow-up usage patterns of an adopted pattern are recommended based on a proposed metric of measuring distances between patterns. In the experimental evaluations, the patterns categorization can achieve 85.4% precision rate with 83% recall rate. The patterns recommendation had approximately half a chance of correctly predicting the follow-up patterns that were actually used by the programmers.

关键词： api usage pattern code example code search system api usage patterns categorization api usage patterns recommendation

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Categorizing and Recommending api usage patterns based on Degree Centralities and pattern Distances

Categorizing and Recommending API Usage Patterns based on De...

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International Computer Symposium (ICS)

作者： Lee, Shin-Jie Su, Wu-Chen Huang, Chi-En You, Jie-Lin Natl Cheng Kung Univ Comp & Network Ctr Tainan Taiwan Univ Kentucky Dept Clin Sci Lexington KY USA Natl Cheng Kung Univ Dept Comp Sci & Informat Engn Tainan Taiwan

ISBN: (纸本)9781509034383

Although efforts have been made on discovering and searching api usage patterns, how to categorize and recommend follow-up api usage patterns is still largely unexplored. This paper advances the state-of-the-art by proposing two methods for categorizing and recommending api usage patterns: first, categories of the usage patterns are automatically identified based on a proposed degree centrality-based clustering algorithm;and second, follow-up usage patterns of an adopted pattern are recommended based on a proposed metric of measuring distances between patterns. In the experimental evaluations, the patterns categorization can achieve 85.4% precision rate with 83% recall rate. The patterns recommendation had approximately half a chance of correctly predicting the follow-up patterns that were actually used by the programmers.

关键词： api usage pattern code example code search system api usage patterns categorization api usage patterns recommendation

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Mining Complex Temporal api usage patterns: An Evolutionary Approach 17

Mining Complex Temporal API Usage Patterns: An Evolutionary ...

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IEEE/ACM 39th International Conference on Software Engineering Companion (ICSE-C)

作者： Huppe, Samuel Saied, Mohamed Aymen Sahraoui, Houari Univ Montreal DIRO Montreal PQ Canada

ISBN: (纸本)9781538615898

Learning to use existing or new software libraries is a difficult task for software developers, which would impede their productivity. Much existing work has provided different techniques to mine api usage patterns from client programs in order to help developers on understanding and using existing libraries. However, this techniques produce incomplete patterns, i.e., without temporal properties, or simple ones. In this paper, we propose a new formulation of the problem of api temporal pattern mining and a new approach to solve it. Indeed, we learn complex temporal patterns using a genetic programming approach. Our preliminary results show that across a considerable variability of client programs, our approach has been able to infer non-trivial patterns that reflect informative temporal properties.

关键词： api documentation api usage pattern Genetic programming Linear temporal logic

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Augmenting Stack Overflow with api usage patterns Mined from GitHub 2018

Augmenting Stack Overflow with API Usage Patterns Mined from...

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26th ACM Joint Meeting on European Software Engineering Conference (ESEC) / Symposium on the Foundations of Software Engineering (FSE)

作者： Reinhardt, Anastasia Zhang, Tianyi Mathur, Mihir Kim, Miryung George Fox Univ Newberg OR USA Univ Calif Los Angeles Los Angeles CA 90095 USA

ISBN: (纸本)9781450355735

Programmers often consult Q&A websites such as Stack Overflow(SO) to learn new apis. However, online code snippets are notalways complete or reliable in terms of api usage. To help program-mers assess online code snippets, we build a Chrome-extension, EXAMPLECHECKTHAT detects api usage violations in SO posts usingapi usage patterns mined from 380K GitHub projects. It quantifies how many GitHub examples follow common api usage and illustrates how to remedy the detected violation in a given SO snippet. With EXAMPLECHECK, programmers can easily identify the pitfalls of a given SO snippet and learn how much it deviates from common api usage patterns in GitHub. The demo video is at http://***/WOnN-wQZsH0.

关键词： online Q&A forum api usage pattern code assessment

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Automatically Generating api usage patterns from Natural Language Queries 25

Automatically Generating API Usage Patterns from Natural Lan...

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25th Asia-Pacific Software Engineering Conference (APSEC)

作者： Tian, Yanfei Wang, Xu Sun, Hailong Zhao, Yi Guo, Chunbo Liu, Xudong Beihang Univ Sch Comp Sci & Engn SKLSDE Lab Beijing Peoples R China Beijing Adv Innovat Ctr Big Data & Brain Comp Beijing Peoples R China

ISBN: (纸本)9781728119700

Automatically generating code from natural language query is a very promising but much challenging direction. Existing approaches either try to generate the whole code or only predict a small part of critical code elements such as api sequence. Meanwhile, api usage patterns, including apis and api-related control-flow statements, have the moderate complexity, but can provide enough code framework information and are very helpful for developers to implement various functionalities. Therefore, in this work, we study the problem of generating api usage patterns, represent api usage patterns by one special constrained tree api-MCTree and design one new api-MCTree decoder for automatically transforming natural language queries to api usage patterns, which can leverage both the difference of control-flow statement types and the syntactic knowledge of api usage patterns. We evaluate our model with annotated code snippets in real Java projects collected from GitHub, and the experimental results show that our approach is effective and outperforms the related approaches.

关键词： api Encoder-Decoder Model api usage pattern Code Generation

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A Comment-Driven Approach to api usage patterns Discovery and Search

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JOURNAL OF INTERNET TECHNOLOGY 2018年第5期19卷 1587-1601页

作者： Lee, Shin-Jie Lin, Xavier Su, Wu-Chen Chen, Hsi-Min Natl Cheng Kung Univ Comp & Network Ctr Tainan Taiwan Natl Cheng Kung Univ Dept Comp Sci & Informat Engn Tainan Taiwan Univ Kentucky Dept Clin Sci Lexington KY 40506 USA Feng Chia Univ Dept Informat Engn & Comp Sci Taichung Taiwan

Considerable effort has gone into the discovery of api usage patterns or examples. However, how to enable programmers to search for discovered api usage examples using natural language queries is still a significant research problem. This paper presents an approach, referred to as Codepus, to facilitate the discovery of api usage examples based on mining comments in open source code while permitting searches using natural language queries. The approach includes two key features: api usage patterns as well as multiple keywords and tf-idf values are discovered by mining open source comments and code snippets;and a matchmaking function is devised for searching for api usage examples using natural language queries by aggregating scores related to semantic similarity, correctness, and the number of apis. In a practical application, the proposed approach discovered 43,721 api usage patterns with 641,591 api usage examples from 15,814 open source projects. Experiment results revealed the following: (1) Codepus reduced the browsing time required for locating api usage examples by 46.5%, compared to the time required when using a web search engine. (2) The precision of Codepus is 91% when using eleven real-world frequently asked questions, which is superior to those of Gists and Open Hub.

关键词： api usage pattern Code example Code search system

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Automated api Property Inference Techniques

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2013年第5期39卷 613-637页

作者： Robillard, Martin P. Bodden, Eric Kawrykow, David Mezini, Mira Ratchford, Tristan McGill Univ Sch Comp Sci Montreal PQ H3A 2A7 Canada Tech Univ Darmstadt Secure Software Engn Grp European Ctr Secur & Privacy Design EC SPRIDE D-64293 Darmstadt Germany Tech Univ Darmstadt D-64289 Darmstadt Germany IBM Res Cambridge MA 02142 USA

Frameworks and libraries offer reusable and customizable functionality through Application Programming Interfaces (apis). Correctly using large and sophisticated apis can represent a challenge due to hidden assumptions and requirements. Numerous approaches have been developed to infer properties of apis, intended to guide their use by developers. With each approach come new definitions of api properties, new techniques for inferring these properties, and new ways to assess their correctness and usefulness. This paper provides a comprehensive survey of over a decade of research on automated property inference for apis. Our survey provides a synthesis of this complex technical field along different dimensions of analysis: properties inferred, mining techniques, and empirical results. In particular, we derive a classification and organization of over 60 techniques into five different categories based on the type of api property inferred: unordered usage patterns, sequential usage patterns, behavioral specifications, migration mappings, and general information.

关键词： api property programming rules specifications protocols interface data mining pattern mining api evolution api usage pattern

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MACs: Mining api code snippets for code reuse

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EXPERT SYSTEMS WITH APPLICATIONS 2011年第6期38卷 7291-7301页

作者： Hsu, Sheng-Kuei Lin, Shi-Jen Natl Cent Univ Dept Informat Management Chungli 320 Taiwan

We apply data mining to source code projects to guide developers through related api usage patterns: "Developers who code the program statement also code..." Given a set of source code files, the mined association rules suggest related code snippets to form the components of object-oriented programs. The mined sequential rules predict likely additional api sequences within a method. After an initial program statement is given, our MACs prototype can correctly predict useful related api code snippets. In our evaluation, we present two studies investigating the usefulness of MACs in software development tasks. One study evaluated the utility of MACs's association pattern recommendations. The other evaluated usefulness of sequential pattern recommendations, and both drew from a sample of eight source code projects from ***. Our experimental evaluation shows that MACs has significant potential to assist developers, especially api newcomers, and provides an alternative method for code reuse. (c) 2010 Elsevier Ltd. All rights reserved.

关键词： Mining software repositories api usage pattern Code reuse

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Building Development Tools Interactively using the EKEKO Meta-Programming Library

Building Development Tools Interactively using the EKEKO Met...

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Software Evolution Week / IEEE Conference on Software Maintenance, Reengineering, and Reverse Engineering (CSMR-WCRE)

作者： De Roover, Coen Stevens, Reinout Vrije Univ Brussel Software Languages Lab Brussels Belgium

ISBN: (纸本)9781479937523

EKEKO is a Clojure library for applicative logic meta-programming against an Eclipse workspace. EKEKO has been applied successfully to answering program queries (e.g., "does this bug pattern occur in my code?"), to analyzing project corpora (e.g., "how often does this api usage pattern occur in this corpus?"), and to transforming programs (e.g., "change occurrences of this pattern as follows") in a declarative manner. These applications rely on a seamless embedding of logic queries in applicative expressions. While the former identify source code of interest, the latter associate error markers with, compute statistics about, or rewrite the identified source code snippets. In this paper, we detail the logic and applicative aspects of the EKEKO library. We also highlight key choices in their implementation. In particular, we demonstrate how a causal connection with the Eclipse infrastructure enables building development tools interactively on the Clojure read-eval-print loop.

关键词： application program interfaces logic programming program control structures program debugging query processing software libraries source code (software) api usage pattern Clojure library Clojure read-eval-print loop EKEKO metaprogramming library Eclipse infrastructure Eclipse workspace applicative logic metaprogramming building development tools error markers logic queries program query answering program transformation project corpora analysis source code snippet identification Buildings Computational modeling Java Libraries Logic programming Vectors Visualization

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Mining api Constraints from Library and Client to Detect api Misuses 28

Mining API Constraints from Library and Client to Detect API...

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28th Asia-Pacific Software Engineering Conference (APSEC)

作者： Zcng, Hushuang Chen, Jingxin Shen, Bcijun Zhong, Hao Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Peoples R China

ISBN: (纸本)9781665437844

Calling Application Programming Interfaces (apis) shall follow various constraints (e.g., call orders). If these constraints are violated, api misuses are introduced to code, and such misuses can cause severe bugs. To effectively detect api misuses, most prior approaches mine constraints from client code, and assume that the violations of constraints are potential misuses. However, as client code only illustrates a small portion of api usages, constraints mined from client code are typically incomplete. As a result, when mined constraints are used to detect bugs, many violations of constraints turn out to be false positives. In this paper, our research purpose is to find more misuses and to reduce false positives. As library code contains many details on apis, we propose an approach that mines api constraints from both client and library code. From client code, our approach builds api usage graphs and uses a frequent subgraph mining algorithm to mine frequent usage patterns as api constraints. From library code, our approach derives various types of constraints with our predefined strategies. With constraints from both sources, our graph matching algorithm can detect api misuses. As a result, our approach takes advantage from both the comprehensiveness and informativeness of library-based constraints and the accuracy of client-based patterns. We compared our approach with MuDetect on the MuBench dataset. Our results show that it significantly improves the detection effectiveness of MuBench from 39.5% to 50.2% of the recall, and from 30.6% to 41.7% of the precision.

关键词： api misuse detection api usage pattern api constraint

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