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SCC: Automatic Classification of code Snippets 18

SCC: Automatic Classification of Code Snippets

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18th ieee International working conference on source code analysis and manipulation (SCAM)

作者： Alreshedy, Kamel Dharmaretnam, Dhanush German, Daniel M. Srinivasan, Venkatesh Gulliver, T. Aaron Univ Victoria Victoria BC V8W 2Y2 Canada

ISBN: (纸本)9781538682906

Determining the programming language of a source code file has been considered in the research community;it has been shown that Machine Learning (ML) and Natural Language Processing (NLP) algorithms can be effective in identifying the programming language of source code files. However, determining the programming language of a code snippet or a few lines of source code is still a challenging task. Online forums such as Stack Overflow and code repositories such as GitHub contain a large number of code snippets. In this paper, we describe source code Classification (SCC), a classifier that can identify the programming language of code snippets written in 21 different programming languages. A Multinomial Naive Bayes (MNB) classifier is employed which is trained using Stack Overflow posts. It is shown to achieve an accuracy of 75% which is higher than that with Programming Languages Identification (PLI-a proprietary online classifier of snippets) whose accuracy is only 55.5%. The average score for precision, recall and the F1 score with the proposed tool are 0.76, 0.75 and 0.75, respectively. In addition, it can distinguish between code snippets from a family of programming languages such as C, C++ and C#, and can also identify the programming language version such as C# 3.0, C# 4.0 and C# 5.0.

关键词： Classification Machine Learning Natural Language Processing Programming languages

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A Constraint Programming Approach to Conflict-aware Optimal Scheduling of Prioritized code Clone Refactoring

A Constraint Programming Approach to Conflict-aware Optimal ...

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11th ieee International working conference on source code analysis and manipulation/ieee International conference on Software Maintenance/ieee International Symposium on Web Systems Evolution/VISSOFT/MESOCA

作者： Zibran, Minhaz F. Roy, Chanchal K. Univ Saskatchewan Dept Comp Sci Saskatoon SK S7N 5C9 Canada

ISBN: (纸本)9780769543475

Duplicated code, also known as code clones, are one of the malicious 'code smells' that often need to be removed through refactoring for enhancing maintainability. Among all the potential refactoring opportunities, the choice and order of a set of refactoring activities may have distinguishable effect on the design/code quality. Moreover, there may be dependencies and conflicts among those refactorings. The organization may also impose priorities on certain refactoring activities. Addressing all these conflicts, priorities, and dependencies, manual formulation of an optimal refactoring schedule is very expensive, if not impossible. Therefore, an automated refactoring scheduler is necessary, which will maximize benefit and minimize refactoring effort. In this paper, we present a refactoring effort model, and propose a constraint programming approach for conflict-aware optimal scheduling of code clone refactoring.

关键词： Cloning Equations Mathematical model Measurement Object oriented modeling Programming Schedules code clone conflict aware optimal scheduling constraint handling constraint programming constraint programming approach duplicated code maintainability malicio

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Semantics-Based code Search Using Input/Output Examples 18

Semantics-Based Code Search Using Input/Output Examples

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18th ieee International working conference on source code analysis and manipulation (SCAM)

作者： Jiang, Renhe Chen, Zhengzhao Zhang, Zejun Pei, Yu Pan, Minxue Zhang, Tian Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China

ISBN: (纸本)9781538682906

As the quality and quantity of open source code increase, semantics-based code search has become an emerging need for software developers to retrieve and reuse existing source code. We present an approach of semantics-based code search using input/output examples for the Java language. Our approach encodes Java methods in code repositories into path constraints via symbolic analysis and leverages SMT solvers to find the methods whose path constraints can satisfy the given input/output examples. Our approach extends the applicability of the semantics-based search technology to more general Java code compared with existing methods. To evaluate our approach, we encoded 1228 methods from GitHub and applied semantics-based code search on 35 queries extracted from Stack Overflow. Correct method code for 29 queries was obtained during the search and the average search time was just about 48 seconds.

关键词： code query symbolic analysis SMT solver

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The Effect of Lexicon Bad Smells on Concept Location in source code

The Effect of Lexicon Bad Smells on Concept Location in Sour...

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作者： Abebe, Surafel Lemma Haiduc, Sonia Tonella, Paolo Marcus, Andrian Fdn Bruno Kessler Software Engn Res Unit I-38122 Trento Italy Wayne State Univ Dept Comp Sci Detroit MI 48202 USA

ISBN: (纸本)9780769543475

Experienced programmers choose identifier names carefully, in the attempt to convey information about the role and behavior of the labeled code entity in a concise and expressive way. In fact, during program understanding the names given to code entities represent one of the major sources of information used by developers. We conjecture that lexicon bad smells, such as, extreme contractions, inconsistent term use, odd grammatical structure, etc., can hinder the execution of maintenance tasks which rely on program understanding. We propose an approach to determine the extent of this impact and instantiate it on the task of concept location. In particular, we conducted a study on two open source software systems where we investigated how lexicon bad smells affect Information Retrieval-based concept location. In this study, the classes changed in response to past modification requests are located before and after lexicon bad smells are identified and removed from the source code. The results indicate that lexicon bad smells impact concept location when using IR-based techniques.

关键词： lexicon bad smells program comprehension concept location text retrieval software lexicon code smells

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Using Changeset Descriptions as a Data source to Assist Feature Location 15

Using Changeset Descriptions as a Data Source to Assist Feat...

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15th ieee International working conference on source code analysis and manipulation (SCAM)

作者： Chochlov, Muslim English, Michael Buckley, Jim Univ Limerick Dept Comp Sci & Informat Syst Limerick Ireland

ISBN: (纸本)9781467375290

Feature location attempts to assist developers in discovering functionality in source code. Many textual feature location techniques utilize information retrieval and rely on comments and identifiers of source code to describe software entities. An interesting alternative would be to employ the changeset descriptions of the code altered in that changeset as a data source to describe such software entities. To investigate this we implement a technique utilizing changeset descriptions and conduct an empirical study to observe this technique's overall performance. Moreover, we study how the granularity (i.e. file or method level of software entities) and changeset range inclusion (i.e. most recent or all historical changesets) affect such an approach. The results of a preliminary study with Rhino and Mylyn. Tasks systems suggest that the approach could lead to a potentially efficient feature location technique. They also suggest that it is advantageous in terms of the effort to configure the technique at method level granularity and that older changesets from older systems may reduce the effectiveness of the technique.

关键词： Feature location information retrieval software repositories

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Towards a taxonomy for annotation of data science experiment repositories 21

Towards a taxonomy for annotation of data science experiment...

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21st ieee International working conference on source code analysis and manipulation (SCAM)

作者： Sivasothy, Shangeetha Barnett, Scott Fernando, Niroshinie Vasa, Rajesh Sinha, Roopak Simmons, Andrew Deakin Univ Appl Artificial Intelligence Inst Geelong Vic Australia Deakin Univ Sch Informat Technol Geelong Vic Australia Auckland Univ Technol Dept Comp Sci & Software Engn Auckland New Zealand

ISBN: (纸本)9781665448970

Data scientists, like software engineers, use search engines, code repositories, tutorials, and question and answer sites for finding code snippets. The objective of this study is to understand what information can be extracted from data science experiment repositories for quicker availability of relevant information when data scientists search for information. In this paper, we investigated a set of notebooks to identify recurring data science techniques for efficient information retrieval and easy adaptation from online solutions to support their search during experimentation. From the manual annotation of 57 natural language processing notebooks, a taxonomy on 106 data science techniques was developed, grouped by data science workflow stages. The preliminary evaluation shows that our constructed taxonomy is relevant to retrieve information that data scientists are searching for. Future work will continue to investigate the creation of a context aware code snippet engine designed for data scientists.

关键词： data scientists experiments source code taxonomy information finding

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Investigating the Use of code analysis and NLP to Promote a Consistent Usage of Identifiers 17

Investigating the Use of Code Analysis and NLP to Promote a ...

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ieee 17th International working conference on source code analysis and manipulation (SCAM)

作者： Lin, Bin Scalabrino, Simone Mocci, Andrea Oliveto, Rocco Bavota, Gabriele Lanza, Michele USI Lugano Switzerland Univ Molise Campobasso Italy

ISBN: (纸本)9781538632383

Meaningless identifiers as well as inconsistent use of identifiers in the source code might hinder code readability and result in increased software maintenance efforts. Over the past years, effort has been devoted to promoting a consistent usage of identifiers across different parts of a system through approaches exploiting static code analysis and Natural Language Processing (NLP). These techniques have been evaluated in small-scale studies, but it is unclear how they compare to each other and how they complement each other. Furthermore, a full-fledged larger empirical evaluation is still missing. We aim at bridging this gap. We asked developers of five projects to assess the meaningfulness of the recommendations generated by three techniques, two already existing in the literature (one exploiting static analysis, one using NLP) and a novel one we propose. With a total of 922 rename refactorings evaluated, this is, to the best of our knowledge, the largest empirical study conducted to assess and compare rename refactoring tools promoting a consistent use of identifiers. Our study sheds light on the current state-of-the-art in rename refactoring recommenders, and indicates directions for future work.

关键词： Tools Natural language processing Java Standards Context modeling Training Static analysis

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WAL: a Tool for Diagnosing Accessibility Issues and Evolving Legacy Web Systems at Runtime 19

WAL: a Tool for Diagnosing Accessibility Issues and Evolving...

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19th ieee International working conference on source code analysis and manipulation (SCAM)

作者： Teotonio, Wanessa C. Gonzalez, Pablo Maia, Paulo Henrique Muniz, Pedro H. G. Univ Estadual Ceara Dell Res Dev & Innovat Ctr Fortaleza Ceara Brazil

ISBN: (纸本)9781728149370

The vast majority of pages available on the Web are developed under the tacit assumption that the final user will not have any kind of disability. Thus, accessibility aspects are not contemplated in their development process. As a consequence, many users encounter interaction barriers and cannot access much of the content in the Web. But the improvement of Websites can be challenging due to their high complexity and lack of documentation, the impossibility of accessing the source code, the use of out-of-dated technologies, and the fact that development teams are often unaware of accessibility rules. To mitigate this problem, this paper proposes a tool, called Website Accessibility Layer (WAL), which aims at both inserting accessibility features into existing Web pages at runtime and diagnosing accessibility issues through a dynamic source code analysis. The current version of the tool contributes to the accessibility of users with visual impairment, dyslexia, and reading difficulties, with respect to 13 Web page resources. The proposal has been validated by being applied to 40 widely accessed Websites with satisfactory results, proving the feasibility of the solution. Furthermore, real users also evaluated positively the benefits brought by the tool to their daily work activities.

关键词： Web accessibility legacy Web systems dynamic source code analysis

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Collective Intelligence for Smarter API Recommendations in Python 16

Collective Intelligence for Smarter API Recommendations in P...

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16th ieee International working conference on source code analysis and manipulation (SCAM)

作者： D'Souza, Andrea Renika Yang, Di Lopes, Cristina V. Univ Calif Irvine Dept Informat Irvine CA 92697 USA

ISBN: (纸本)9781509038497

Software developers use Application Programming Interfaces (APIs) of libraries and frameworks extensively while writing programs. In this context, the recommendations provided in code completion pop-ups help developers choose the desired methods. The candidate lists recommended by these tools, however, tend to be large, ordered alphabetically and sometimes even incomplete. A fair amount of work has been done recently to improve the relevance of these code completion results, especially for statically typed languages like Java. However, these proposed techniques rely on the static type of the object and are therefore inapplicable for a dynamically typed language like Python. In this paper, we present PyReco, an intelligent code completion system for Python which uses the mined API usages from open source repositories to order the results based on relevance rather than the conventional alphabetic order. To recommend suggestions that are relevant for a working context, a nearest neighbor classifier is used to identify the best matching usage among all the extracted usage patterns. To evaluate the effectiveness of our system, the code completion queries are automatically extracted from projects and tested quantitatively using a ten-fold cross validation technique. The evaluation shows that our approach outperforms the alphabetically ordered API recommendation systems in recommending APIs for standard, as well as, third-party libraries.

关键词： API Recommendations code completion code recommenders Dynamic languages Program analysis Python Static analysis Usage Mining

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FaultBuster: An Automatic code Smell Refactoring Toolset 15

FaultBuster: An Automatic Code Smell Refactoring Toolset

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15th ieee International working conference on source code analysis and manipulation (SCAM)

作者： Szoke, Gabor Nagy, Csaba Fulop, Lajos Jeno Ferenc, Rudolf Gyimothy, Tibor Univ Szeged Dept Software Engn Szeged Hungary

ISBN: (纸本)9781467375290

One solution to prevent the quality erosion of a software product is to maintain its quality by continuous refactoring. However, refactoring is not always easy. Developers need to identify the piece of code that should be improved and decide how to rewrite it. Furthermore, refactoring can also be risky;that is, the modified code needs to be re-tested, so developers can see if they broke something. Many IDEs offer a range of refactorings to support so-called automatic refactoring, but tools which are really able to automatically refactor code smells are still under research. In this paper we introduce FaultBuster, a refactoring toolset which is able to support automatic refactoring: identifying the problematic code parts via static code analysis, running automatic algorithms to fix selected code smells, and executing integrated testing tools. In the heart of the toolset lies a refactoring framework to control the analysis and the execution of automatic algorithms. FaultBuster provides IDE plugins to interact with developers via popular IDEs (Eclipse, Netbeans and IntelliJ IDEA). All the tools were developed and tested in a 2-year project with 6 software development companies where thousands of code smells were identified and fixed in 5 systems having altogether over 5 million lines of code.

关键词： Automatic refactoring code smells coding issues antipatterns sourceMeter Columbus

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