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Using origin analysis to detect merging and splitting of source code entities

ieee TRANSACTIONS ON SOFTWARE ENGINEERING 2005年第2期31卷 166-181页

作者： Godfrey, MW Zou, LJ Univ Waterloo Sch Comp Sci Waterloo ON N2L 3G1 Canada

Merging and splitting source code entities is a common activity during the lifespan of a software system;as developers rethink the essential structure of a system or plan for a new evolutionary direction, so must they be able to reorganize the design artifacts at various abstraction levels as seems appropriate. However, while the raw effects of such changes may be plainly evident in the new artifacts, the original context of the design changes is often lost. That is, it may be obvious which characters of which files have changed, but it may not be obvious where or why moving, renaming, merging, and/or splitting of design elements has occurred. In this paper, we discuss how we have extended origin analysis [1], [2] to aid in the detection of merging and splitting of files and functions in procedural code;in particular, we show how reasoning about how call relationships have changed can aid a developer in locating where merges and splits have occurred, thereby helping to recover some information about the context of the design change. We also describe a case study of these techniques ( as implemented in the Beagle tool) using the PostgreSQL database system as the subject.

关键词： software evolution origin analysis restructuring reverse engineering reengineering

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Precise slicing of concurrent programs An Evaluation of static slicing algorithms for concurrent programs

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AUTOMATED SOFTWARE ENGINEERING 2009年第2期16卷 197-234页

作者： Giffhorn, Dennis Hammer, Christian Univ Karlsruhe TH Karlsruhe Germany

While there exist efficient algorithms to slice sequential programs precisely, there are only two algorithms for precise slicing of concurrent interprocedural programs with recursive procedures (Krinke in Proc. ESEC/FSE'03, pp. 178-187, 2003;Nanda and Ramesh in ACM Toplas. 28(6):1088-1144, 2006). We present an empirical evaluation of both algorithms for Java. We demonstrate that both algorithms provide the same precision up to the model of concurrency in use and show that the concurrency model has strong impact on slice precision and computation costs. Furthermore, we extend both algorithms to support dynamic thread creation both in loops and recursion-a feature that the original algorithms could not fully handle. The worst case complexity of the algorithms being exponential, we developed several optimizations and compared these with each other and with algorithms that trade precision for speed. Finally, we show that one algorithm may produce incorrect slices and present a remedy.

关键词： Slicing Program analysis Concurrency Threads

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Making Sense of Online code Snippets

Making Sense of Online Code Snippets

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10th ieee working conference on Mining Software Repositories (MSR)

作者： Subramanian, Siddharth Holmes, Reid Univ Waterloo Sch Comp Sci Waterloo ON Canada

ISBN: (纸本)9781479903450;9781467329361

Stack Overflow contains a large number of high-quality source code snippets. The quality of these snippets has been verified by users marking them as solving a specific problem. Stack Overflow treats source code snippets as plain text and searches surface snippets as they would any other text. Unfortunately, plain text does not capture the structural qualities of these snippets;for example, snippets frequently refer to specific API (e.g., Android), but by treating the snippets as text, linkage to the Android API is not always apparent. We perform snippet analysis to extract structural information from short plain-text snippets that are often found in Stack Overflow. This analysis is able to identify 253,137 method calls and type references from 21,250 Stack Overflow code snippets. We show how identifying these structural relationships from snippets could perform better than lexical search over code blocks in practice.

关键词： Linux Web sites application program interfaces information retrieval software quality

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ENYPD-Entry Points Detector Jakarta Server Faces Use Case 21

ENYPD-Entry Points Detector Jakarta Server Faces Use Case

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21st ieee International working conference on source code analysis and manipulation, SCAM 2021

作者： Nguempnang, Rodrigue Wete Berger, Bernhard J. Sohr, Karsten University of Bremen Bremen Germany

ISBN: (纸本)9781665448970

Which parts of a software system can be accessed by an attacker is a common question in software security. The answer to this question defines where to look for input validation vulnerabilities, which parts of a system to respect during Microsoft's Threat Modeling, or how to calculate security metrics. Identifying entry points of an application is, therefore, a frequently occurring problem. Additionally, identifying entry points is relevant when analysing many framework-based applications since they no longer have a simple main *** different analyses implement entry point detection, the presented tool eNYPD explicitly focuses on answering this question for Java-based systems in an analysis-independent manner. It extracts information on entry points statically and persists this information to a separate file. Therefore, it allows reusing the information in different analyses, and researchers do not need to implement a custom entry point detection for each *** presented tool is explained using Jakarta Server Faces, a user-interface technology for Web-based business applications implemented using Java. The paper presents the implemented extraction approach, the internal data model, and the results stored. Finally, in an evaluation, the statically assessed results of eNYPD are compared to a dynamically determined set of entry points. This comparison allows us to demonstrate the correctness of the extracted information. © 2021 ieee.

关键词： Static analysis

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CAWDOR: Compiler assisted worm defense

CAWDOR: Compiler assisted worm defense

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2012 ieee 12th International working conference on source code analysis and manipulation, SCAM 2012

作者： Yuan, Jun Johnson, Rob Department of Computer Science Stony Brook University Stony Brook NY 11790 United States

ISBN: (纸本)9780769547831

This paper explores how much the source code analysis can assist worm defense system. Previously-proposed worm defense systems have used disparate mechanisms to detect worms, analyze exploits, verify alerts, and apply mitigations. Furthermore, previous systems have not offered predictability, i.e. it is not possible to verify, in advance, that the defense system will never generate a mitigation that breaks the program. This paper describes a program transformation technique that makes collaborative worm defense systems easy to build, predictable and fast-responsive. Our transformation provides a single building block that can be used to perform worm detection, exploit analysis, alert verification, and mitigation application. In fact, our transformation makes most of these tasks trivial. Furthermore, software vendors and users can test, in advance, that the defense system will very unlikely apply a mitigation that breaks their software. Mitigations are vulnerability-specific not exploit-specific. Finally, our system can respond extremely quickly to a new worm. The exploit analysis becomes trivial so sentinel hosts can issue an alert the instant they detect a worm. We have implemented a prototype of our system based on the Jones and Kelly program transformation for memory safety. During normal operation, our system incurs only 5% overhead. We take advantage of static analysis to develop several optimizations and make the Jones and Kelly approach to memory safety efficient and practical. © 2012 ieee.

关键词： Static analysis

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CROP: Linking code Reviews to source code Changes 15

CROP: Linking Code Reviews to Source Code Changes

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ACM/ieee 15th International conference on Mining Software Repositories (MSR)

作者： Paixao, Matheus Krinke, Jens Han, Donggyun Harman, Mark UCL London England Facebook London England

ISBN: (纸本)9781450357166

code review has been widely adopted by both industrial and open source software development communities. Research in code review is highly dependant on real-world data, and although existing researchers have attempted to provide code review datasets, there is still no dataset that links code reviews with complete versions of the system's code base mainly because reviewed versions are not kept in the system's version control repository. Thus, we present CROP, the code Review Open Platform, the first curated code review repository that links review data with isolated complete versions (snapshots) of the source code at the time of review. CROP currently provides data for 8 software systems, 48,975 reviews and 112,617 patches, including versions of the systems that are inaccessible in the systems' original repositories. Moreover, CROP is extensible, and it will be continuously curated and extended.

关键词： code Review Repository Platform Software Change analysis

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Fuzzy Software Analyzer (FSA): A New Approach for Interpreting source code Versioning Repositories

Fuzzy Software Analyzer (FSA): A New Approach for Interpreti...

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ieee CIS International conference on Fuzzy Systems (FUZZ-ieee)

作者： Oliveira, Joao C. B. Rios, Ricardo A. de Almeida, Eduardo S. Sant'Anna, Claudio N. Rios, Tatiane Nogueira Univ Fed Bahia Dept Comp Sci Salvador BA Brazil

ISBN: (纸本)9781665444071

source code quality plays a key role in software quality mainly due to its impact on software maintainability. Software engineers have been using source code metrics to support them to assess source code quality. source code metrics quantify different source code characteristics. However, source code metric analysis still involves subjectivity. For instance, it is not trivial to decide whether a metric value is high or low. To reduce the eventual subjectivity of source code metrics analysis, several researchers are using Machine Learning algorithms. Therefore, in this paper, we designed a Fuzzy-based approach to extract characteristics and patterns present in source code versioning repositories in order to: i) assist the specialist in the interpretation of releases, especially when working with large volumes of source code;ii) from the release interpretation, specialists can improve the quality of the source code;and iii) monitor the evolution of the software as new releases are submitted to the repositories. We evaluated the proposed approach with the Linux Test Project repository, emphasizing the interpretability of large source code versioning repositories.

关键词： Measurement Machine learning algorithms Linux conferences Software quality Monitoring Fuzzy systems

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Classifying code comments in Java open-source software systems 14

Classifying code comments in Java open-source software syste...

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ieee/ACM 14th International conference on Mining Software Repositories (MSR)

作者： Pascarella, Luca Bacchelli, Alberto Delft Univ Technol Delft Netherlands

ISBN: (纸本)9781538615447

code comments are a key software component containing information about the underlying implementation. Several studies have shown that code comments enhance the readability of the code. Nevertheless, not all the comments have the same goal and target audience. In this paper, we investigate how six diverse Java OSS projects use code comments, with the aim of understanding their purpose. Through our analysis, we produce a taxonomy of source code comments;subsequently, we investigate how often each category occur by manually classifying more than 2,000 code comments from the aforementioned projects. In addition, we conduct an initial evaluation on how to automatically classify code comments at line level into our taxonomy using machine learning;initial results are promising and suggest that an accurate classification is within reach.

关键词： comment taxonomy software quality source code comments

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How They Relate and Leave: Understanding Atoms of Confusion in Open-source Java Projects 23

How They Relate and Leave: Understanding Atoms of Confusion ...

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23rd ieee International working conference on source code analysis and manipulation, SCAM 2023

作者： Pinheiro, Oton Rocha, Lincoln Viana, Windson Federal University of Ceará Department of Computing Fortaleza Ceará Brazil

ISBN: (纸本)9798350305067

Software comprehension is essential to improve understanding and avoid mistakes in the software development lifecycle. code confusion occurs when a developer and the computer reach different interpretations about the behavior of the same piece of code. Such pieces of code can be represented as small and isolated code patterns called Atoms of Confusion (ACs). In this study, we empirically investigated the effects of ACs in the software development lifecycle of 21 open-source Java projects. We built a dataset linking more than 8,000 commits, 4,000 reported issues, and 7,000 ACs from the subject projects. Our findings showed a positive correlation between the number of ACs and the number of reported bugs and improvements. We also investigated changes in commits, looking forward to gathering a better understanding of in what context ACs are removed. As each commit is linked to at least one reported issue (e.g., bug and improvement), we were able to compare the ratio of ACs removal regarding each kind of commit and use it as a proxy to indicate whether ACs are likely to be the cause behind a reported issue. We found a higher ratio of removed ACs in bug-fix and improvement commits than in the other kind of commits (task, sub-task, new feature, wish, and test) for 14 of the 19 studied projects, which had ACs removed in commits. Finally, to support our quantitative results, we conducted a qualitative analysis to understand better how often atoms of confusion contributed to the occurrence of a bug or improvement. We inspected ACs removed in these types of commits with up to ten lines removed, analyzing the source code, messages of each involved commit, and the title, description, and comments of related Jira issues. Out of a universe of 8,641 commits from 21 analyzed projects, 391 removed ACs. Among them, 53 met the condition for our qualitative analysis. In 7 of these commits, 9 removed ACs were likely to contributed directly to the occurrence of a bug or improvement. To th

关键词： Atoms

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Calibrating Deep Learning-based code Smell Detection using Human Feedback 23

Calibrating Deep Learning-based Code Smell Detection using H...

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23rd ieee International working conference on source code analysis and manipulation, SCAM 2023

作者： Nanadani, Himesh Saad, Mootez Sharma, Tushar Dalhousie University Canada

ISBN: (纸本)9798350305067

code smells are inherently subjective in nature. Software developers may have different opinions and perspectives on smelly code. While many attempts have been made to use deep learning-based models for code smell detection, they fail to consider each developer's subjective perspective while detecting smells. Ignoring this aspect defies the purpose of using deep learning-based smell detection methods because the models are not customized to the developer's context. This paper proposes a method that considers human feedback to account for such subjectivity. Towards this, we created a plugin for IntelliJ IDEA and developed a container-based web-server to offer services of our baseline deep learning model. The setup allowed developers to see code smells within the IDE and provide feedback. Using this setup, we conducted a controlled experiment with 14 participants divided into experimental and control groups. In the first round of our experiment, we show code smells predicted using the baseline deep learning model and collect feedback from the participants. In the second round, we fine-tune the model based on the experimental group's feedback and reevaluate its performance before and after adjustment. Our results show that using such calibration improves the performance of the smell detection model by 15.49% in F1 score on average across the participants of the experimental group. Our work carries implications for both researchers and practitioners. Practitioners can apply our approach to enhance the quality of their code in day-to-day development activities, aligning it with their own code smell definitions. Furthermore, software engineering researchers can leverage this study to adopt analogous approaches for addressing similar issues, including code review. © 2023 ieee.

关键词： Feedback

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