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SENSA: Sensitivity analysis for Quantitative Change-impact Prediction 14

SENSA: Sensitivity Analysis for Quantitative Change-impact P...

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14th ieee International working conference on source code analysis and manipulation (SCAM)

作者： Cai, Haipeng Jiang, Siyuan Santelices, Raul Zhang, Ying-jie Zhang, Yiji Univ Notre Dame Notre Dame IN 46556 USA Tsinghua Univ Beijing 100084 Peoples R China

ISBN: (纸本)9780769553047

Sensitivity analysis determines how a system responds to stimuli variations, which can benefit important software-engineering tasks such as change-impact analysis. We present SENSA, a novel dynamic-analysis technique and tool that combines sensitivity analysis and execution differencing to estimate the dependencies among statements that occur in practice. In addition to identifying dependencies, SENSA quantifies them to estimate how much or how likely a statement depends on another. Quantifying dependencies helps developers prioritize and focus their inspection of code relationships. To assess the benefits of quantifying dependencies with SENSA, we applied it to various statements across Java subjects to find and prioritize the potential impacts of changing those statements. We found that SENSA predicts the actual impacts of changes to those statements more accurately than static and dynamic forward slicing. Our SENSA prototype tool is freely available for download.

关键词： Change-impact prediction dependence analysis execution differencing sensitivity analysis

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Behave Nicely! Automatic Generation of code for Behaviour Driven Development Test Suites 19

Behave Nicely! Automatic Generation of Code for Behaviour Dr...

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

作者： Bob, Ruxandra Storer, Tim Univ Glasgow Sch Comp Sci Glasgow Lanark Scotland

ISBN: (纸本)9781728149370

Behaviour driven development (BDD) has gained widespread use in the software industry. System specifications can be expressed as test scenarios, describing the circumstances, actions and expected outcomes. These scenarios are written in a structured natural language (Gherkin), with each step in the scenario associated with a corresponding step implementation function in the underlying programming language. A challenge recognised by industry is ensuring that the natural language scenarios, step implementation functions and underlying system implementation remain consistent with one another, requiring on-going maintenance effort as changes are made to a system. To address this, we have developed behave_nicely, a tool, for automatically generating step implementation functions from structured natural language steps, with the intention of eliminating the need for maintaining step implementation functions. We evaluated our approach on a sample of 20 white box and 50 black box projects using behaviour driven development, drawn from GitHub. Our results show that behave_nicely can generate step implementation functions for 80% of the white box and 17% of black box projects. We conclude that (a) there is significant potential for automating the process of code generation for BDD tests and (b) that the development of guidelines for writing tests in Gherkin would significantly improve the results.

关键词： Behaviour driven development code generation

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On the Use of Machine Learning Techniques Towards the Design of Cloud Based Automatic code Clone Validation Tools 18

On the Use of Machine Learning Techniques Towards the Design...

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

作者： Mostaeen, Golam Svajlenko, Jeffrey Roy, Banani Roy, Chanchal K. Schneider, Kevin Univ Saskatchewan Dept Comp Sci Saskatoon SK Canada

ISBN: (纸本)9781538682906

A code clone is a pair of code fragments, within or between software systems that are similar. Since code clones often negatively impact the maintainability of a software system, a great many numbers of code clone detection techniques and tools have been proposed and studied over the last decade. To detect all possible similar source code patterns in general, the clone detection tools work on syntax level (such as texts, tokens, AST and so on) while lacking user-specific preferences. This often means the reported clones must be manually validated prior to any analysis in order to filter out the true positive clones from task or user-specific considerations. This manual clone validation effort is very time-consuming and often error-prone, in particular for large-scale clone detection. In this paper, we propose a machine learning based approach for automating the validation process. In an experiment with clones detected by several clone detectors in several different software systems, we found our approach has an accuracy of up to 87.4% when compared against the manual validation by multiple expert judges. The proposed method shows promising results in several comparative studies with the existing related approaches for automatic code clone validation. We also present our experimental results in terms of different code clone detection tools, machine learning algorithms and open source software systems.

关键词： code clones validation Machine Learning Clone Management

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A Tool for Optimizing Java 8 Stream Software via Automated Refactoring 18

A Tool for Optimizing Java 8 Stream Software via Automated R...

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

作者： Khatchadourian, Raffi Tang, Yiming Bagherzadeh, Mehdi Ahmed, Syed CUNY New York NY 10021 USA Oakland Univ Rochester MI 48063 USA

ISBN: (纸本)9781538682906

Streaming APIs are pervasive in mainstream Object-Oriented languages. For example, the Java 8 Stream API allows for functional-like, MapReduce-style operations in processing both finite and infinite data structures. However, using this API efficiently involves subtle considerations like determining when it is best for stream operations to run in parallel, when running operations in parallel can be less efficient, and when it is safe to run in parallel due to possible lambda expression side-effects. In this paper, we describe the engineering aspects of an open source automated refactoring tool called OPTIMIZE STREAMS that assists developers in writing optimal stream software in an (observable) semantics-preserving fashion. Based on a novel ordering and typestate analysis, the tool is implemented as a plug-in to the Eclipse IDE, using both the WALA and SAFE frameworks. It was evaluated on 11 Java projects consisting of similar to 642 thousand lines of code, where we found that 36.31% of candidate streams were refactorable, and an average speedup of 1.55 on a performance suite was observed. We also describe experiences gained from integrating three very different static analysis frameworks to provide developers with an easy-to-use interface for optimizing their stream code to its full potential.

关键词： refactoring automatic parallelization typestate analysis ordering Java 8 streams eclipse WALA SAFE

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Does code review really remove coding convention violations? 20

Does code review really remove coding convention violations?

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20th ieee International working conference on source code analysis and manipulation (SCAM)

作者： Han, DongGyun Ragkhitwetsagul, Chaiyong Krinke, Jens Paixao, Matheus Rosa, Giovanni Amazon Munich Germany Mahidol Univ SERU Fac ICT Bangkok Thailand UCL London England Univ Fortaleza Fortaleza Ceara Brazil Univ Molise Campobasso CB Italy

ISBN: (纸本)9781728192482

Many software developers perceive technical debt as the biggest problems in their projects. They also perceive code reviews as the most important process to increase code quality. As inconsistent coding style is one source of technical debt, it is no surprise that coding convention violations can lead to patch rejection during code review. However, as most research has focused on developer's perception, it is not clear whether code reviews actually prevent the introduction of coding convention violations and the corresponding technical debt. Therefore, we investigated how coding convention violations are introduced, addressed, and removed during code review by developers. To do this, we analysed 16,442 code review requests from four projects of the Eclipse community for the introduction of convention violations. Our result shows that convention violations accumulate as code size increases despite changes being reviewed. We also manually investigated 1,268 code review requests in which convention violations disappear and observed that only a minority of them have been removed because a convention violation has been flagged in a review comment. The investigation results also highlight that one can speed up the code review process by adopting tools for code convention violation detection.

关键词： code review coding conventions coding style

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Don't DIY: Automatically transform legacy Python code to support structural pattern matching 22

Don't DIY: Automatically transform legacy Python code to sup...

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ieee 22nd International working conference on source code analysis and manipulation (SCAM)

作者： Rozsa, Balazs Antal, Gabor Ferenc, Rudolf Univ Szeged Dept Software Engn Szeged Hungary

ISBN: (纸本)9781665496094

As data becomes more and more complex as technology evolves, the need to support more complex data types in programming languages has grown. However, without proper storage and manipulation capabilities, handling such data can result in hard-to-read, difficult-to-maintain code. Therefore, programming languages continuously evolve to provide more and more ways to handle complex data. Python 3.10 introduced structural pattern matching, which serves this exact purpose: we can split complex data into relevant parts by examining its structure, and store them for later processing. Previously, we could only use the traditional conditional branching, which could have led to long chains of nested conditionals. Maintaining such code fragments can be cumbersome. In this paper, we present a complete framework to solve the aforementioned problem. Our software is capable of examining Python source code and transforming relevant conditionals into structural pattern matching. Moreover, it is able to handle nested conditionals and it is also easily extensible, thus the set of possible transformations can be easily increased.

关键词： Python AST structural pattern matching code transformation

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Automatic Detection of sources and Sinks in Arbitrary Java Libraries 18

Automatic Detection of Sources and Sinks in Arbitrary Java L...

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

作者： Sas, Darius Bessi, Marco Fontana, Francesca Arcelli Univ Milano Bicocca Dipartimento Informat Sistemist & Comunicaz Milan Italy CAST Software Italia Milan Italy

ISBN: (纸本)9781538682906

In the last decade, data security has become a primary concern for an increasing amount of companies around the world. Protecting the customer's privacy is now at the core of many businesses operating in any kind of market. Thus, the demand for new technologies to safeguard user data and prevent data breaches has increased accordingly. In this work, we investigate a machine learning-based approach to automatically extract sources and sinks from arbitrary Java libraries. Our method exploits several different features based on semantic, syntactic, intra-procedural dataflow and class-hierarchy traits embedded into the bytecode to distinguish sources and sinks. The performed experiments show that, under certain conditions and after some preprocessing, sources and sinks across different libraries share common characteristics that allow a machine learning model to distinguish them from the other library methods. The prototype model achieved remarkable results of 86% accuracy and 81% F-measure on our validation set of roughly 600 methods.

关键词： Java Static analysis sources Sink Machine Learning

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QSES: Quasi-Static Executable Slices 21

QSES: Quasi-Static Executable Slices

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

作者： Stievenart, Quentin Binkley, David De Roover, Coen Vrije Univ Brussel Brussels Belgium Loyola Univ Baltimore Baltimore MD USA

ISBN: (纸本)9781665448970

Program slicing aims to reduce a program to a minimal form that produces the same output for a given slicing criterion. Program slicing approaches divide into static and dynamic approaches: whereas static approaches generate an over-approximation of the slice that is valid for all possible program inputs, dynamic approaches rely on executing the program and thus generate an under-approximation of the slice that is valid for only a subset of the inputs. An important limitation of static approaches is that they often do not generate an executable program, but rather identify only those program components upon which the slicing criterion depends (referred to as a closure slice). In order to overcome this limitation, we propose a novel approach that combines static and dynamic slicing. We rely on observation-based slicing, a dynamic approach, but protect all statements that have been identified as part of the static slice by the static slicer codeSurfer. As a result, we obtain slices that cover at least the behavior of the static slice, but that can be compiled and executed. We evaluated this new approach on a set of 57 C programs and report our preliminary findings.

关键词： program slicing static slicing dynamic slicing program dependence analysis

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Into the Woods: Experiences from Building a Dataflow analysis Framework for C/C plus 21

Into the Woods: Experiences from Building a Dataflow Analysi...

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

作者： Schubert, Philipp Dominik Leer, Richard Hermann, Ben Bodden, Eric Paderborn Univ Paderborn Germany Tech Univ Dortmund Dortmund Germany Fraunhofer IEM Paderborn Germany

ISBN: (纸本)9781665448970

While traditional static analysis-albeit its complexity-is a topic that is well understood, we especially struggle when it comes to implementing its concepts. Designing and modeling software that implements static analysis is a challenging task. However, developing usable static analysis implementations and providing toolboxes to researchers and practitioners is key to advance the overall progress in this field. This paper reports on the lessons learned from developing the PhASAR and Soot static data-flow analysis frameworks. We present some of the key mistakes of our first implementations of PhASAR and their corrections. From those corrections we distill guidelines that will be helpful to static analysis developers and their users. In our work, we identified modularity as the key guiding principle supported-directly or indirectly-by virtually all other guidelines.

关键词： static analysis guidelines framework C/C plus LLVM

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Analyzing the Evolution of Preprocessor-Based Variability: A Tale of a Thousand and One Scripts 18

Analyzing the Evolution of Preprocessor-Based Variability: A...

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

作者： Schulze, Sandro Fenske, Wolfram Otto von Guericke Univ Fac Comp Sci Magdeburg Germany

ISBN: (纸本)9781538682906

Highly configurable software systems allow the efficient and reliable development of similar software variants based on a common code base. The C preprocessor CPP, which uses source code annotations that enable conditional compilation, is a simple yet powerful text-based tool for implementing such systems. However, since annotations interfere with the actual source code, the CPP has often been accused of being a source of errors and increased maintenance effort. In our research, we have been curious about whether high-level patterns of CPP misuse (i.e., code smells) can be identified, how they evolve, and whether they really hinder maintenance. To support this research, we started a simple tool which over the years evolved into a powerful toolchain. This evolution was possible because our toolchain is not monolithic, but is composed of many small tools connected by scripts and communicating via files. Moreover, we reused existing tools whenever possible and developed our own solutions only as a last resort. In this paper, we report our experiences of building this toolchain. In particular, we present design decisions we made and lessons learned, both positive and negative ones. We hope that this not only stimulates discussion and (in the best case) attracts more researchers in using our tools. Rather, we also want to encourage others to put emphasis on building tools instead of considering them "yet another research prototype".

关键词： source code analysis software evolution software maintenance C preprocessor annotations

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