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A Survey of source code search: A 3-dimensional Perspective

ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY 2024年第6期33卷 1-51页

作者： Sun, Weisong Fang, Chunrong Ge, Yifei Hu, Yuling Chen, Yuchen Zhang, Quanjun Ge, Xiuting Liu, Yang Chen, Zhenyu Nanjing Univ Software Inst Nanjing Peoples R China Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore

(source) code search is widely concerned by software engineering researchers because it can improve the productivity and quality of software development. Given a functionality requirement usually described in a natural language sentence, a code search system can retrieve code snippets that satisfy the requirement from a large-scale code corpus, e.g., GitHub. To realize effective and efficient code search, many techniques have been proposed successively. These techniques improve code search performance mainly by optimizing three core components, including query understanding component, code understanding component, and query-code matching component. In this article, we provide a 3-dimensional perspective survey for code search. Specifically, we categorize existing code search studies into query-end optimization techniques, code-end optimization techniques, and match-end optimization techniques according to the specific components they optimize. These optimization techniques are proposed to enhance the performance of specific components, and thus the overall performance of code search. Considering that each end can be optimized independently and contributes to the code search performance, we treat each end as a dimension. Therefore, this survey is 3-dimensional in nature, and it provides a comprehensive summary of each dimension in detail. To understand the research trends of the three dimensions in existing code search studies, we systematically review 68 relevant literatures. Different from existing code search surveys that only focus on the query end or code end or introduce various aspects shallowly (including codebase, evaluation metrics, modeling technique, etc.), our survey provides a more nuanced analysis and review of the evolution and development of the underlying techniques used in the three ends. Based on a systematic review and summary of existing work, we outline several open challenges and opportunities at the three ends that remain to be addressed in f

关键词： source code search deep learning query-end optimization code-end optimization match-end optimization

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Generating Clarifying Questions for Query Refinement in source code search 29

Generating Clarifying Questions for Query Refinement in Sour...

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29th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Eberhart, Zachary McMillan, Collin Univ Notre Dame Dept Comp Sci Notre Dame IN 46556 USA

ISBN: (纸本)9781665437868

In source code search, a common information-seeking strategy involves providing a short initial query with a broad meaning, and then iteratively refining the query using terms gleaned from the results of subsequent searches. This strategy requires programmers to spend time reading search results that are irrelevant to their development needs. In contrast, when programmers seek information from other humans, they typically refine queries by asking and answering clarifying questions. Clarifying questions have been shown to benefit general-purpose search engines, but have not been examined in the context of code search. We present a method for generating natural-sounding clarifying questions using information extracted from function names and comments. Our method outperformed a keyword-based method for single-turn refinement in synthetic studies, and was associated with shorter search durations in human studies.

关键词： source code search code retrieval clarifying questions query refinement software maintenance

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Towards Summarizing Program Statements in source code search 20

Towards Summarizing Program Statements in Source Code Search

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35th Annual ACM Symposium on Applied Computing (SAC)

作者： Marin, Victor J. Bansal, Iti Rivero, Carlos R. Rochester Inst Technol Rochester NY 14623 USA

ISBN: (纸本)9781450368667

A common practice among programmers is to find pieces of source code using search engines. Programs retrieved by these engines are typically semantically but not necessarily syntactically similar. As a result, ranking methods are exploited to present relevant programs to users. However, due to implementation variability, users need to understand such programs. In this paper, we propose a method to group statements into clusters from a set of programs retrieved by a source code search engine. Each cluster comprises a number of program statements that have similar but not exact semantics and are pervasive. Our hypothesis is that such clusters help understand at a glance a set of semantically-related programs. We use approximate graph alignment to find correspondences among statements in two program dependence graphs that are similar with respect to their control and data flows, as well as operations they perform. We then build a graph with pairwise comparisons of program dependence graphs, and cast the problem of clustering statements as finding communities of statements that consistently align. Our evaluation using programs collected by BigCloneBench shows that clusters of statements discovered by our approach help discern implementation variations.

关键词： source code search Program Dependence Graph Approximate Graph Alignment Community Detection

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Query Quality Prediction and Reformulation for source code search: The Refoqus Tool

Query Quality Prediction and Reformulation for Source Code S...

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35th International Conference on Software Engineering (ICSE)

作者： Haiduc, Sonia De Rosa, Giuseppe Bavota, Gabriele Oliveto, Rocco de Lucia, Andrea Marcus, Andrian Wayne State Univ Dept Comp Sci Detroit MI 48202 USA Univ Salerno Sch Sci I-84084 Salerno Italy Univ Molise Dept Biosci & Territory I-86090 Molise Italy

ISBN: (纸本)9781467330763

Developers search source code frequently during their daily tasks, to find pieces of code to reuse, to find where to implement changes, etc. code search based on text retrieval (TR) techniques has been widely used in the software engineering community during the past decade. The accuracy of the TR-based search results depends largely on the quality of the query used. We introduce Refoqus, an Eclipse plugin which is able to automatically detect the quality of a text retrieval query and to propose reformulations for it, when needed, in order to improve the results of TR-based code search. A video of Refoqus is found online at http://***/watch?v=UQlWGiauyk4.

关键词： source code search Text Retrieval Query Quality Query Reformulation

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NCDsearch: Sliding Window-Based code Clone search Using Lempel-Ziv Jaccard Distance

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2022年第5期E105D卷 973-981页

作者： Ishio, Takashi Maeda, Naoto Shibuya, Kensuke Iwamoto, Kenho Inoue, Katsuro Nara Inst Sci & Technol Ikoma 6300192 Japan NEC Corp Ltd Tokyo 1088001 Japan Osaka Univ Suita Osaka 5650871 Japan

Software developers may write a number of similar source code fragments including the same mistake in software products. To remove such faulty code fragments, developers inspect code clones if they found a bug in their code. While various code clone detection methods have been proposed to identify clones of either code blocks or functions, those tools do not always fit the code inspection task because a faulty code fragment may be much smaller than code blocks, e.g. a single line of code. To enable developers to search code clones of such a small faulty code fragment in a large-scale software product, we propose a method using Lempel-Ziv Jaccard Distance, which is an approximation of Normalized Compression Distance. We conducted an experiment using an existing research dataset and a user survey in a company. The result shows our method efficiently reports cloned faulty code fragments and the performance is acceptable for software developers.

关键词： source code search normalized compression distance

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Reusable Component Retrieval: A Semantic search Approach for Low-Resource Languages

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ACM TRANSACTIONS ON ASIAN AND LOW-REsource LANGUAGE INFORMATION PROCESSING 2023年第5期22卷 1-31页

作者： Bibi, Nazia Rana, Tauseef Maqbool, Ayesha Alkhalifah, Tamim Khan, Wazir Zada Bashir, Ali Kashif Bin Zikria, Yousaf Natl Univ Sci & Technol Dept Comp Software Engn Scholars Ave H-12 Islamabad 46000 Pakistan Qassim Univ Dept Comp Sci Coll Sci & Arts Ar Rass POB 1162 Buraydah 52571 Saudi Arabia Qassim Univ Dept Comp Coll Sci & Arts Ar Rass Ar Rass 1162 Qassim Saudi Arabia Univ Wah Dept Comp Sci Quaid Ave Wah 47040 Pakistan Manchester Metropolitan Univ Dept Comp & Math Manchester M15 6BH England Woxsen Univ Woxsen Sch Business Hyderabad 502345 Telangana India Yeungnam Univ Dept Informat & Commun Engn 280 Daehak Ro Gyongsan 38541 South Korea

A common practice among programmers is to reuse existing code, accomplished by performing natural language queries through search engines. The main aim of code retrieval is to search for the most relevant snippet from a corpus of code snippets. However, code retrieval frameworks for low-resource languages are insufficient. Retrieving the most relevant code snippet efficiently can be accomplished only by eliminating the semantic gap between the code snippets residing in the repository and the user's query (natural language description). The primary objective of the research is to contribute to this field by providing a code search framework that can be extended for low-resource languages. The secondary objective is to provide a code retrieval mechanism that is semantically relevant to the user query and provide programmers with the ability to locate source code that they want to use when developing new applications. The proposed approach is implemented using a web platform to search for source code. As code retrieval is a sophisticated task, the proposed approach incorporates a semantic search mechanism. This research uses a semantic model for code retrieval, which generates meanings or synonyms of words. The proposed model integrates ontologies and Natural Language Processing. System performance measures and classification accuracy are computed using precision, recall, and F1-score. We also compare the proposed approach with state-of-the-art baseline models. The retrieved results are ranked, showing that our approach significantly outperforms robust code matching. Our evaluation shows that semantic matching leads to improved source code retrieval. This study marks a substantial advancement in integrating programming expertise with code retrieval techniques. Moreover, our system lets users know when and how it is used for successful semantic searching.

关键词： Ontologies web semantics source code retrieval source code search information retrieval

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Efficient storage and fast querying of source code

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INFORMATION SYSTEMS FRONTIERS 2011年第3期13卷 349-357页

作者： Panchenko, Oleksandr Plattner, Hasso Zeier, Alexander B. Hasso Plattner Inst Software Syst Engn D-14440 Potsdam Germany

Enabling fast and detailed insights over large portions of source code is an important task in a global development ecosystem. Numerous data structures have been developed to store source code and to support various structural queries, to help in navigation, evaluation and analysis. Many of these data structures work with tree-based or graph-based representations of source code. The goal of this project is to elaborate a data storage that enables efficient storing and fast querying of structural information. The naive adjacency list method has been enhanced with the use of recent data compression approaches for column-oriented databases to allow no-loss albeit compact storage of fine-grained structural data. The graph indexing has enabled the proposed data model to expeditiously answer fine-grained structural queries. This paper describes the basics of the proposed approach and illustrates its technical feasibility.

关键词： source code search source code analysis Global code repository Structural information

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Exploiting spatial code proximity and order for improved source code retrieval for bug localization

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JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS 2017年第1期29卷 1-24页

作者： Sisman, Bunyamin Akbar, Shayan A. Kak, Avinash C. Purdue Univ Dept Elect & Comp Engn W Lafayette IN 47907 USA

Practically all information retrieval based approaches developed to date for automatic bug localization are based on the bag-of-words assumption that ignores any positional and ordering relationships between the terms in a query. In this paper, we argue that bug reports are ill-served by this assumption because such reports frequently contain various types of structural information whose terms must obey certain positional and ordering constraints. It therefore stands to reason that the quality of retrieval for bug localization would improve if these constraints could be taken into account when searching for the most relevant files. In this paper, we demonstrate that such is indeed the case. We show how the well-known Markov Random Field based retrieval framework can be used for taking into account the term-term proximity and ordering relationships in a query vis-a-vis the same relationships in the files of a source-code library to greatly improve the quality of retrieval of the most relevant source files. We have carried out our experimental evaluations on popular large software projects using over 4000 bug reports. The results we present demonstrate unequivocally that the new proposed approach is far superior to the widely used bag-of-words based approaches. Copyright (c) 2016 John Wiley & Sons, Ltd.

关键词： bug localization source code search term proximity Markov Random Fields

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Precise and Scalable Querying of Syntactical source code Patterns Using Sample code Snippets and a Database

Precise and Scalable Querying of Syntactical Source Code Pat...

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IEEE 19th International Conference on Program Comprehension (ICPC)

作者： Panchenko, Oleksandr Karstens, Jan Plattner, Hasso Zeier, Alexander Hasso Plattner Inst Potsdam Germany SAP AG Walldorf Germany

ISBN: (纸本)9780769543987

While analyzing a log file of a text-based source code search engine we discovered that developers search for fine-grained syntactical patterns in 36% of queries. Currently, to cope with queries of this kind developers need to use regular expressions, to add redundant terms to the query or to combine searching with other tools provided by the development environment. To improve the expressiveness of the queries, these can be formulated as tree patterns of abstract syntax trees. These search patterns can be expressed by using query languages, such as XPath. However, developers usually do not work with either XPath or with AST. To shield developers from the complexity of query formulation we propose using sample code snippets as queries. The novelty of our approach is the combination of a query language that is very close to the surface programming language and a special database technology to store a large amount of abstract syntax trees. The advantage of this approach over existing source code query languages and search engines is the performance of both query formulation and query execution. This paper describes the technical details of the method and illustrates the value of this approach with performance measures and an industrial controlled experiment. All developers were able to complete the tasks of the experiment faster and more accurately by using our tool (ACS) than by using a text-based search engine. The number of false positives in the result lists was significantly decreased.

关键词： source code search query-by-example source code query language abstract syntax trees XPath database

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On the Use of Positional Proximity in IR-Based Feature Location

On the Use of Positional Proximity in IR-Based Feature Locat...

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

作者： Hill, Emily Sisman, Bunyamin Kak, Avinash Montclair State Univ Dept Comp Sci Montclair NJ 07043 USA Purdue Univ Sch Elect & Comp Engn W Lafayette IN USA

ISBN: (纸本)9781479937523

As software systems continue to grow and evolve, locating code for software maintenance tasks becomes increasingly difficult. Recently proposed approaches to bug localization and feature location have suggested using the positional proximity of words in the source code files and the bug reports to determine the relevance of a file to a query. Two different types of approaches have emerged for incorporating word proximity and order in retrieval: those based on ad-hoc considerations and those based on Markov Random Field (MRF) modeling. In this paper, we explore using both these types of approaches to identify over 200 features in five open source Java systems. In addition, we use positional proximity of query words within natural language (NL) phrases in order to capture the NL semantics of positional proximity. As expected, our results indicate that the power of these approaches varies from one dataset to another. However, the variations are larger for the ad-hoc positional-proximity based approaches than with the approach based on MRF. In other words, the feature location results are more consistent across the datasets with MRF based modeling of the features.

关键词： feature location source code search software maintenance

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