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ieee international workshop on source code analysis and manipulation

作者： Luke Swearngan Mark Hills Appalachian State University Boone NC USA

In this paper, we present early work on the foundation of a program analysis framework for the Go programming language. This framework, named Go AiR (analysis in Rascal), currently provides support for extracting abstract syntax trees from Go source code, working with multiple Go projects and multiple versions of a single Go project (based on Git version history), and code exploration through the use of Rascal features for working with representations of source code. We discuss the structure of the framework, describe the mapping from Go to Rascal and how this was tested, present sample code showing how the framework can be used to explore Go source code, and discuss future extensions to the framework to support program analysis and verification.

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A static analyzer for model transformations

A static analyzer for model transformations

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3rd international workshop on Model Transformation with ATL, MtATL 2011 - Co-located with TOOLS 2011 Federated Conferences

作者： Vieira, Andreza Ramalho, Franklin Federal University of Campina Grande Campina Grande Paraíba Brazil

Adoption of the Model-Driven Architecture approach is increasing each day. As any other software development project, a MDA-based project is constantly evolving given that software requirements change along their lifecycle. Thus, changes in MDA transformations are also frequent. These changes are hard and error-prone tasks when manually accomplished. We propose a static analyzer for inspecting the source code of ATL transformations. It provides an API comprising methods to extract and handle diverse elements from ATL transformations. Therefore, the proposed static analyzer can be useful during several development tasks of MDA-based projects, such as maintenance and debugging, since it enables developers to save effort and development time by automatically identifying dependences and relations from transformation elements.

关键词： Static analysis

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Support for Static Concept Location with sv3D

Support for Static Concept Location with sv3D

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ieee international workshop on Visualizing Software for Understanding and analysis (VISSOFT)

作者： Xinrong Xie D. Poshyvanyk A. Marcus Department of Computer Science Wayne State University Detroit MI USA

The paper presents a new visualization approach to support static concept location in source code. The approach is realized through the combination of two existing tools: IRiSS, which is an information retrieval based tool that support source code searching and browsing; and sv3D, which is a software visualization front end. Both tools are integrated into MS Visual Studio .NET. The motivation behind the approach, the definition of the visual mappings, and usage examples are also presented in the paper, together with an outline of future and related work

关键词： Software tools Data visualization Information retrieval Software systems Software metrics Software engineering Application software Filtering Displays Containers

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An analysis of the feasibility and benefits of GPU/multicore acceleration of the Weather Research and Forecasting model

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2016年第7期28卷 2052-2072页

作者： Vanderbauwhede, Wim Takemi, Tetsuya Univ Glasgow Sch Comp Sci Glasgow G12 8QQ Lanark Scotland Kyoto Univ Disaster Prevent Res Inst Uji Kyoto Japan

There is a growing need for ever more accurate climate and weather simulations to be delivered in shorter timescales, in particular, to guard against severe weather events such as hurricanes and heavy rainfall. Due to climate change, the severity and frequency of such events - and thus the economic impact - are set to rise dramatically. Hardware acceleration using graphics processing units (GPUs) or Field-Programmable Gate Arrays (FPGAs) could potentially result in much reduced run times or higher accuracy simulations. In this paper, we present the results of a study of the Weather Research and Forecasting (WRF) model undertaken in order to assess if GPU and multicore acceleration of this type of numerical weather prediction (NWP) code is both feasible and worthwhile. The focus of this paper is on acceleration of code running on a single compute node through offloading of parts of the code to an accelerator such as a GPU. The governing equations set of the WRF model is based on the compressible, non-hydrostatic atmospheric motion with multi-physics processes. We put this work into context by discussing its more general applicability to multi-physics fluid dynamics codes: in many fluid dynamics codes, the numerical schemes of the advection terms are based on finite differences between neighboring cells, similar to the WRF code. For fluid systems including multi-physics processes, there are many calls to these advection routines. This class of numerical codes will benefit from hardware acceleration. We studied the performance of the original code of the WRF model and proposed a simple model for comparing multicore CPU and GPU performance. Based on the results of extensive profiling of representative WRF runs, we focused on the acceleration of the scalar advection module. We discuss the implementation of this module as a data-parallel kernel in both OpenCL and OpenMP. We show that our data-parallel kernel version of the scalar advection module runs up to seven times fa

关键词： general-purpose computation on graphics processing units (GPGPU) parallelization of simulation large-scale scientific computing

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Quality Assurance Awareness in Open source Software Projects on GitHub

Quality Assurance Awareness in Open Source Software Projects...

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ieee international workshop on source code analysis and manipulation

作者： Ali Khatami Andy Zaidman Delft University of Technology Delft The Netherlands

Software engineers employ a variety of approaches to ensure the quality of software systems, including software testing, modern code review, automated static analysis, build automation, and continuous integration. To make effective decisions regarding quality assurance (QA), software engineers need to have an awareness of (1) the QA approaches that are in use in a project, and (2) how they are used. Through an exploratory, mixed-methods investigation we set out to better understand the awareness of software engineers in open-source software (OSS) development with regard to QA practices. This involved a largescale survey of 471 maintainers and contributors on GitHub. Our findings indicate that a high-level awareness among the respondents is common, but also that the respondents are less certain about how the practices are adopted; we further consider the perspective of both the contributor and the maintainer.

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WinkFuzz: Model-based Script Synthesis for Fuzzing 3

WinkFuzz: Model-based Script Synthesis for Fuzzing

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3rd international workshop on Advanced Security on Software and Systems (ACM ASSS)

作者： Liu, Zian Chen, Chao Ahmed, Ejaz Zhang, Jun Liu, Dongxi Swinburne Univ Technol Melbourne Vic Australia CSIRO Data61 Melbourne Vic Australia RMIT Univ Melbourne Vic Australia

ISBN: (纸本)9798400701825

Kernel fuzzing is important for finding critical kernel vulnerabilities. Close-source (e.g., Windows) operating system kernel fuzzing is even more challenging due to the lack of source code. Existing approaches fuzz the kernel by modeling syscall sequences from traces or static analysis of system codes. However, a common limitation is that they do not learn and mutate the syscall sequences to reach different kernel states, which can potentially result in more bugs or crashes. In this paper, we propose WinkFuzz, an approach to learn and mutate traced syscall sequences in order to reach different kernel states. WinkFuzz learns syscall dependencies from the trace, identifies potential syscalls in the trace that can have dependent subsequent syscalls, and applies the dependencies to insert more syscalls while preserving the dependencies into the trace. Then WinkFuzz fuzzes the synthesized new syscall sequence to find system crashes. We applied WinkFuzz to four seed applications and found a total increase in syscall number of 70.8%, with a success rate of 61%, within three insert levels. The average time for tracing, dependency analysis, recovering model script, and synthesizing script was 600, 39, 34, and 129 seconds respectively. The instant fuzzing rate is 3742 syscall executions per second. However, the average fuzz efficiency dropped to 155 syscall executions per second when the initializing time, waiting time, and other factors were taken into account. We fuzzed each seed application for 24 seconds and, on average, obtained 12.25 crashes within that time frame.

关键词： Static analysis

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An analysis of the feasibility and benefits of GPU/multicore acceleration of the Weather Research and Forecasting model

An analysis of the feasibility and benefits of GPU/multicore...

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10th international workshop on Science Gateways Computing Environments (GCE) held in conjunction with the 3rd workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE)

作者： Vanderbauwhede, Wim Takemi, Tetsuya Univ Glasgow Sch Comp Sci Glasgow G12 8QQ Lanark Scotland Kyoto Univ Disaster Prevent Res Inst Uji Kyoto Japan

关键词： general-purpose computation on graphics processing units (GPGPU) parallelization of simulation large-scale scientific computing

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Explaining Transformer-based code Models: What Do They Learn? When They Do Not Work?

Explaining Transformer-based Code Models: What Do They Learn...

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ieee international workshop on source code analysis and manipulation

作者： Ahmad Haji Mohammadkhani Chakkrit Tantithamthavorn Hadi Hemmatif University of Calgary Calgary Canada Monash University Melbourne Australia York University Toronto Canada

In recent years, there has been a wide interest in designing deep neural network-based models that automate downstream software engineering tasks on source code, such as code document generation, code search, and program repair. Although the main objective of these studies is to improve the effectiveness of the downstream task, many studies only attempt to employ the next best neural network model, without a proper in-depth analysis of why a particular solution works or does not, on particular tasks or scenarios. In this paper, using an example eXplainable AI (XAI) method (attention mechanism), we study two recent large language models (LLMs) for code (codeBERT and GraphcodeBERT) on a set of software engineering downstream tasks: code document generation (CDG), code refinement (CR), and code translation (CT). Through quantitative and qualitative studies, we identify what codeBERT and GraphcodeBERT learn (put the highest attention on, in terms of source code token types), on these tasks. We also show some of the common patterns when the model does not work as expected (performs poorly even on easy problems) and suggest recommendations that may alleviate the observed challenges.

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Change Pattern Detection for Optimising Incremental Static analysis

Change Pattern Detection for Optimising Incremental Static A...

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ieee international workshop on source code analysis and manipulation

作者： Cindy Wauters Jens Van der Plas Quentin Stiévenart Coen De Roover Vrije Universiteit Brussel Brussels Belgium Université du Québec à Montréal Montréal Canada

Static analyses can be used by developers to compute properties of a program, enabling e.g., bug detection and program verification. However, reanalysing a program from scratch upon every change is time-consuming, especially in settings where code changes often, such as within IDEs. To avoid such full reanalyses, incremental analyses instead reuse parts of the previous analysis result, and reanalyse the changed code as necessary. While incrementality improves the analysis time, we introduce a complementary approach that further reduces the analysis time. A traditional incremental analysis updates previous analysis results without domain-specific knowledge. However, the effect of particular source code changes on analysis results can be predicted. Performing a traditional incremental analysis of the changed code might therefore be unnecessary. Instead, we propose to detect code change patterns of which the effect on analysis results can be predicted and to update these results accordingly, saving potentially expensive computations. In this paper, we explore the idea of adapting the analysis results for behaviour-preserving change patterns. In particular, we consider consistent renamings, inverted conditionals, and moved function definitions within Scheme programs. We implemented our approach and evaluated it on 30 programs. We show decreases in incremental analysis time between 3% and 99% on 25 programs that contain at least one behaviour-preserving change pattern.

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Semi-Automatic Refactoring to C++20 Modules: A Semi-Success Story

Semi-Automatic Refactoring to C++20 Modules: A Semi-Success ...

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ieee international workshop on source code analysis and manipulation

作者： Richárd Szalay Zoltán Porkoláb Department of Programming Languages and Compilers Faculty of Informatics Eötvös Loránd University Budapest Hungary

ISBN: (纸本)9781665496100

The component-based design of software projects is a desired property both for development and ease of code comprehension. Programming languages have long allowed component-based development (e.g., Java packages, Python modules); however, other languages, especially C and C++, had stuck to the “translation unit” model where every source file is individually compiled. The Modules system of C++20 was expected to allow cleaner encapsulation of concern. In this paper, we investigate the effort of a (semi-)automatic modularisation of existing C++ projects. Based on our investigation, upgrading existing software systems to the new Modules feature is extremely hard due to coupling issues arising from necessarily legacy design. Implementing real transition requires a significant redesign of both project-internal and user-facing programming interfaces.

关键词： Java codes Pain source coding Symbols C++ languages Programming

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