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Prompt-Enhanced software Vulnerability Detection Using ChatGPT 24

Prompt-Enhanced Software Vulnerability Detection Using ChatG...

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46th international conference on software engineering: Companion, ICSE-Companion 2024

作者： Zhang, Chenyuan Liu, Hao Zeng, Jiutian Yang, Kejing Li, Yuhong Li, Hui Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China School of Informatics Xiamen University China Alibaba China

ISBN: (纸本)9798400705021

With the increase in software vulnerabilities that cause significant economic and social losses, automatic vulnerability detection has become essential in software development and maintenance. Recently, large language models (LLMs) have received considerable attention due to their stunning intelligence, and some studies consider using ChatGPT for vulnerability detection. However, they do not fully consider the characteristics of LLMs, since their designed questions to ChatGPT are simple without a prompt design tailored for vulnerability detection. this paper launches a study on the performance of software vulnerability detection using ChatGPT with different prompt designs. Firstly, we complement previous work by applying various improvements to the basic prompt. Moreover, we incorporate structural and sequential auxiliary information to improve the prompt design. Moreover, we leverage ChatGPT's ability of memorizing multi-round dialogue to design suitable prompts for vulnerability detection. We conduct extensive experiments on two vulnerability datasets to demonstrate the effectiveness of promptenhanced vulnerability detection using ChatGPT. © 2024 ieee Computer society. All rights reserved.

关键词： software design

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APICIA: An API Change Impact Analyzer for Android Apps 24

APICIA: An API Change Impact Analyzer for Android Apps

引用

46th international conference on software engineering: Companion, ICSE-Companion 2024

作者： Mahmud, Tarek Che, Meiru Rouijel, Jihan Khan, Mujahid Yang, Guowei Texas State University San MarcosTX United States Data61 CSIRO Brisbane Australia The University of Queensland Brisbane Australia

ISBN: (纸本)9798400705021

Android APIs are updated frequently, making it critical to analyze the impact of these updates on Android apps to ensure their reliability. In this paper, we introduce APICIA, a tool that can be used for analyzing the impact of API changes on Android apps. APICIA identifies program elements such as classes, methods, and statements that have been affected, along with affected tests and untested affected code following the target API update. Our evaluation on 31 real-world Android apps shows that APICIA can be cost-effective by pinpointing only 35.31% of tests per app on average that may exhibit different behaviors (e.g. app crashes) due to the API update. Furthermore, since many of the affected statements are not covered by existing tests, APICIA can also aid developers in expanding their test suite to cover these statements. APICIA is publicly available at https://***/TSUMahmud/apicia and a screencast presenting the demonstration of APICIA is available at https://***/apicia-tool. © 2024 ieee Computer society. All rights reserved.

关键词： software testing

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Refinery: Graph Solver as a Service: Refinement-based Generation and Analysis of Consistent Models 24

Refinery: Graph Solver as a Service: Refinement-based Genera...

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46th international conference on software engineering: Companion, ICSE-Companion 2024

作者： Marussy, Kristóf Ficsor, Attila Semeráth, Oszkár Varró, Dániel Budapest University of Technology and Economics Department of Measurement and Information Systems Budapest Hungary Linköping University Department of Computer and Information Science Linköping Sweden McGill University Department of Electrical and Computer Engineering Montreal Canada

ISBN: (纸本)9798400705021

Various software and systems engineering scenarios rely on the systematic construction of consistent graph models. However, automatically generating a diverse set of consistent graph models for complex domain specifications is challenging. First, the graph generation problem must be specified with mathematical precision. Moreover, graph generation is a computationally complex task, which necessitates specialized logic solvers. Refinery is a novel open-source software framework to automatically synthesize a diverse set of consistent domain-specific graph models. the framework offers an expressive high-level specification language using partial models to succinctly formulate a wide range of graph generation challenges. Moreover, it provides a modern cloud-based architecture for a scalable graph solver as a service, which uses logic reasoning rules to efficiently synthesize a diverse set of solutions to graph generation problems by partial model refinement. Applications include system-level architecture synthesis, test generation for modeling tools or traffic scenario synthesis for autonomous vehicles. Video demonstration: https://***/Qy-3udNsWsM. Continuously deployed at: https://***/. © 2024 ieee Computer society. All rights reserved.

关键词： Open source software

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Analyzing the Impact of Context Representation and Scope in Code Infilling 24

Analyzing the Impact of Context Representation and Scope in ...

引用

46th international conference on software engineering: Companion, ICSE-Companion 2024

作者： Heo, Jinseok Lee, Eunseok Department of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9798400705021

Existing studies solve software engineering tasks using code infilling through LLMC. they utilize context information, which refers to data near the target code of infilling, as input prompts. Although prompts are essential for infilling the target code, current studies use them without analyzing the impact of the representation and scope of context on code infilling. In this study, we analyzed how context representation and scope affect the performance of code infilling. We used XLCost, which contains code, comments, and a function comment for various programming languages. the combination of code and a function comment for context representation yielded the best code infilling performance. Furthermore, we found that the context scope is proportional to performance. Our analysis results can be applied in various tasks that involve code infilling in the future. © 2024 ieee Computer society. All rights reserved.

关键词： software engineering

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TypeEvalPy: A Micro-benchmarking Framework for Python Type Inference Tools 24

TypeEvalPy: A Micro-benchmarking Framework for Python Type I...

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46th international conference on software engineering: Companion, ICSE-Companion 2024

作者： Venkatesh, Ashwin Prasad S. Sabu, Samkutty Wang, Jiawei Mir, Amir M. Li, Li Bodden, Eric Heinz Nixdorf Institut Paderborn University Paderborn Germany Paderborn University Paderborn Germany Faculty of Information Technology Monash University Melbourne Australia Delft University of Technology Delft Netherlands School of Software Beihang University Beijing China Heinz Nixdorf Institut Fraunhofer IEM Paderborn University Paderborn Germany

ISBN: (纸本)9798400705021

In light of the growing interest in type inference research for Python, both researchers and practitioners require a standardized process to assess the performance of various type inference techniques. this paper introduces TypeEvalPy, a comprehensive microbenchmarking framework for evaluating type inference tools. Type- EvalPy contains 154 code snippets with 845 type annotations across 18 categories that target various Python features. the framework manages the execution of containerized tools, transforms inferred types into a standardized format, and produces meaningful metrics for assessment. through our analysis, we compare the performance of six type inference tools, highlighting their strengths and limitations. Our findings provide a foundation for further research and optimization in the domain of Python type inference. © 2024 ieee Computer society. All rights reserved.

关键词： Python

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Automated Model Quality Estimation and Change Impact Analysis on Model Histories 24

Automated Model Quality Estimation and Change Impact Analysi...

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46th international conference on software engineering: Companion, ICSE-Companion 2024

作者： Blaschke, Konstantin Rupert Fortiss Research Institute of the Free State of Bavaria Germany Blekinge Institute of Technology Sweden

ISBN: (纸本)9798400705021

Cyber-Physical Systems integrate hardware with software in complex applications. To mitigate the complexity, engineers rely on model-based systems engineering approaches. Updates and function enhancements lead to frequently changing design constraints and objectives. these changes increase the need to rework and extend model artifacts of the system. this can cause quality degradation over time due to modeling errors, knowledge disparities, or a lack of guidelines. To enable efficient collaboration and reduce maintenance costs in model-based systems engineering, the industry needs a cost-efficient, scalable approach to monitor model quality. the work outlines a doctoral thesis investigating the potential of automated data-driven quality assessment strategies using model artifact history and model changes. We will extract metrics and model changes to establish quality feedback for system engineers. We aim to use manual model quality assessments to incorporate domain-specific expert knowledge into the automated strategy. the main goals are to lower the effort of model quality assessments, to provide practitioners with foresight on quality development, and to estimate task effort to improve model quality. © 2024 ieee Computer society. All rights reserved.

关键词： Cost engineering

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Proceedings - 2024 ieee/acm 4th international Workshop on engineering and Cybersecurity of Critical Systems and 2024 ieee/acm 2nd international Workshop on software Vulnerability, EnCyCriS/SVM 2024

Proceedings - 2024 IEEE/ACM 4th International Workshop on En...

引用

4th international Workshop on engineering and Cybersecurity of Critical Systems and 2024 ieee/acm 2nd international Workshop on software Vulnerability, EnCyCriS/SVM 2024, held in conjunction with the 46th ieee/acm international conference on software engineering, ICSE 2024

ISBN: (纸本)9798400705656

the proceedings contain 9 papers. the topics discussed include: WasmCFuzz: structure-aware fuzzing for Wasm compilers;mitigating security issues in Github actions;trust in software supply chains: blockchain-enabled SBOM and the AIBOM future;interplay of digital twins and cyber deception: unraveling paths for technological advancements;building a cybersecurity knowledge graph with CyberGraph;training developers to code securely: theory and practice;on DevSecOps and risk management in critical infrastructures: practitioners’ insights on needs and goals;cyber-incident response in industrial control systems: practices and challenges in the petroleum industry;and cybersecurity and medical devices: a bull in a China shop.

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Broadly Enabling KLEE to Effortlessly Find Unrecoverable Errors in Rust 44

Broadly Enabling KLEE to Effortlessly Find Unrecoverable Err...

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acm/ieee 46th international conference on software engineering - software engineering in Practice (ICSE-SEIP)

作者： Zhang, Ying Li, Peng Ding, Yu Wang Lingxiang Williams, Dan Meng, Na Virginia Tech Blacksburg VA 24061 USA Zoox Foster City CA USA Google Mountain View CA USA Microsoft Redmond WA USA

ISBN: (纸本)9798400702174

Rust is a general-purpose programming language designed for performance and safety. Unrecoverable errors (e.g., Divide by Zero) in Rust programs are critical, as they signal bad program states and terminate programs abruptly. Previous work has contributed to utilizing KLEE, a dynamic symbolic test engine, to verify the program would not panic. However, it is difficult for engineers who lack domain expertise to write test code correctly. Besides, the effectiveness of KLEE in finding panics in production Rust code has not been evaluated. We created an approach, called PanicCheck, to hide the complexity of verifying Rust programs with KLEE. Using PanicCheck, engineers only need to annotate the function-to-verify with #[panic_check]. the annotation guides PanicCheck to generate test code, compile the function together with tests, and execute KLEE for verification. After applying PanicCheck to 21 open-source and 2 closed-source projects, we found 61 test inputs that triggered panics;59 of the 61 panics have been addressed by developers so far. Our research shows promising verification results by KLEE, while revealing technical challenges in using KLEE. Our experience will shed light on future practice and research in program verification.

关键词： software testing

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Path Complexity Analysis for Interprocedural Code 24

Path Complexity Analysis for Interprocedural Code

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46th international conference on software engineering: Companion, ICSE-Companion 2024

作者： Kaniyur, Mira Cavalcante-Studart, Ana Yang, Yihan Park, Sangeon Chen, David Lam, Duy Bang, Lucas Harvey Mudd College ClaremontCA United States

ISBN: (纸本)9798400705021

INTRODUCTION: Symbolic execution's path explosion is a critical issue in software testing, quantified by Asymptotic Path Complexity (APC) [3]. APC, more precise than cyclomatic [6] or NPAth [7] complexities, measures the effort to cover paths in code analysis [1]. It's vital for testing, setting limits on path growth for tools like Klee [4], focusing previously on intraprocedural code [2, 8]. Our advancement, APC-IP, extends APC to interprocedural analysis, enhancing scalability and encompassing earlier models. Contributions. We claim the following research contributions. (1) APC-IP Formalization: Extension of the theory and algorithms established for APC to account for interprocedural functions;(2) Optimization Over All Previous APC Approaches. Replacing theoretical steps in previous algorithms to improve performance for both interprocedural and intraprocedural code;(3) APC-IP Implementation. Implementing APC-IP atop Metrinome, an existing APC analysis tool;(4) APC-IP Experimental Validation. APC-IP computes accurate APC for both intraprocedural and interprocedural, and is the fastest option to process complex source code. © 2024 ieee Computer society. All rights reserved.

关键词： software testing

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Proceedings - 2024 ieee/acm 12th international Workshop on software engineering for Systems-of-Systems and software Ecosystems, SESoS 2024

Proceedings - 2024 IEEE/ACM 12th International Workshop on S...

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12th international Workshop on software engineering for Systems-of-Systems and software Ecosystems, SESoS 2024, in conjunction with the 46th ieee/acm international conference on software engineering, ICSE 2024

ISBN: (纸本)9798400705571

the proceedings contain 10 papers. the topics discussed include: employing discrete controller synthesis for developing systems-of-systems controllers;towards model-driven dashboard generation for systems-of-systems;sandboxing adoption in open source ecosystems;mediators in systems-of-systems and ecosystems: a systematic literature review and conceptualization;towards automatic generation of systems-of-systems architectural configurations;self-adaptation of loosely coupled systems across a system of small uncrewed aerial systems;exploring transparency as a sustainability goal in software ecosystems;on an exemplar supporting model-based quality assurance research on healthcare systems-of-systems;and a multilevel modelling framework for quarry site operations.

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