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29th Asia-Pacific Software Engineering Conference (APSEC)

作者： Kim, Kicheol Kim, Misoo Lee, Eunseok Sungkyunkwan Univ Coll Comp & Informat Suwon South Korea Sungkyunkwan Univ Inst Software Convergence Suwon South Korea

ISBN: (纸本)9781665455374

Automated program repair(APR) is in the spotlight in academia and the field to reduce the time and cost of maintenance for developers. Recently, APR has continued to study based on deep-learning models to understand and learn how to fix software bugs. Text-to-Text Transfer Transformer(T5), which scored state-of-the-art in natural language processing benchmarks, also showed promising results on program repair in recent studies. In deep-learning-based program repair studies, studies commonly propose code abstraction techniques to avoid vocabulary problems and learn fine code transformation to generate bug-fixing patches. However, there is not enough systematic analysis of code abstraction according to each bug type in deep-learning-based program repair. Therefore, We leverage TFix, T5-based program repair, to evaluate how code abstraction techniques affect neural program repair. Our experimental results showed that defect-specific code abstraction achives a higher average BLEU score than the existing code abstraction technique in both T5 and multilingual-T5(mT5) model-based TFix results. Also, mT5 model-based TFix, which is applied defect-specific code abstraction, gets a higher BLEU score in 37 error types of 52 ESLint error types than TFix.

关键词： Automated program repair code abstraction Transformers Deep learning

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Enhancing Dynamic Abstract Generation for code Summarization using code-OAN Models and DBWTFF Frames 2

Enhancing Dynamic Abstract Generation for Code Summarization...

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Bhatt, Chandradeep Sharma, Manish Sharma, Sanjay Gupta, Shefali Singh, Teekam Kumar, Mukesh Computer Science and Engineering Graphic Era Hill University Uttarakhand Dehradun248002 India Computer Science & Engineering Graphic Era Deemed to Be University Uttarakhand Dehradun248002 India Sgrr Univeristy Computer Application Department Dehradun India Chitkara University Institute of Engineering and Tech Chitkara University Punjab India

ISBN: (纸本)9798350306415

This research presents a robustness code abstraction generation method based on an attention mechanism. The method involves extracting high-quality code and its corresponding description language material from the programming community, specifically focusing on the text of query specifications and code responses. Redundant code and its description language material are filtered out, and the query specifications are transformed into declarative sentences for code conversion. Finally, a series model based on the attention mechanism is utilized to generate code summaries. The method effectively eliminates redundancy and noise in the code, leading to improved accuracy rates in automatic judgment, artificial evaluation, and testing. The evaluation results demonstrate superior performance compared to existing baseline methods. © 2024 IEEE.

关键词： accuracy rate attention mechanism code abstraction code summarization declarative sentences description language high-quality code redundancy filtering robustness

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A Large-scale Study on API Misuses in the Wild 14

A Large-scale Study on API Misuses in the Wild

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14th IEEE Conference on Software Testing, Verification and Validation (ICST)

作者： Li, Xia Jiang, Jiajun Benton, Samuel Xiong, Yingfei Zhang, Lingming Kennesaw State Univ Dept Software Engn & Game Design Kennesaw GA 30144 USA Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China Univ Texas Dallas Dept Comp Sci Dallas TX USA Peking Univ Key Lab High Confidence Software Technol MoE Beijing Peoples R China Peking Univ DCST Beijing Peoples R China Univ Illinois Dept Comp Sci Champaign IL USA

ISBN: (纸本)9781728168364

API misuses are prevalent and extremely harmful. Despite various techniques have been proposed for API-misuse detection, it is not even clear how different types of API misuses distribute and whether existing techniques have covered all major types of API misuses. Therefore, in this paper, we conduct the first large-scale empirical study on API misuses based on 528,546 historical bug-fixing commits from GitHub (from 2011 to 2018). By leveraging a state-of-the-art fine-grained AST differencing tool, GumTree, we extract more than one million bug-fixing edit operations, 51.7% of which are API misuses. We further systematically classify API misuses into nine different categories according to the edit operations and context. We also extract various frequent API-misuse patterns based on the categories and corresponding operations, which can be complementary to existing API-misuse detection tools. Our study reveals various practical guidelines regarding the importance of different types of API misuses. Furthermore, based on our dataset, we perform a user study to manually analyze the usage constraints of 10 patterns to explore whether the mined patterns can guide the design of future API-misuse detection tools. Specifically, we find that 7,541 potential misuses still exist in latest Apache projects and 149 of them have been reported to developers. To date, 57 have already been confirmed and fixed (with 15 rejected misuses correspondingly). The results indicate the importance of studying historical API misuses and the promising future of employing our mined patterns for detecting unknown API misuses.

关键词： Pattern generation Program adaptation code abstraction

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Towards Transparency-Encouraging Partial Software Disclosure to Enable Trust in Data Usage 35

Towards Transparency-Encouraging Partial Software Disclosure...

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35th IEEE/ACM International Conference on Automated Software Engineering (ASE)

作者： Schindler, Christian Univ Mannheim Inst Enterprise Syst Mannheim Germany

ISBN: (纸本)9781450367684

Whenever software components process personal or private data, appropriate data protection mechanisms are mandatory. An essential factor in achieving trust and transparency is not to give preference to a single party but to make it possible to audit the data usage in an unbiased way. The scenario in mind for this contribution contains (i) users bringing in sensitive data they want to be safe, (ii) developers building software-based services whose Intellectual Properties (IPs) they desire to protect, and (iii) platform providers wanting to be trusted and to be able to rely on the developers integrity. The authors see these interests as an insufficiently solved field of tension that can be relaxed by a suitable level of transparently represented software components to give insights without exposing every detail.

关键词： transparency trust data privacy code abstraction

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Towards transparency-encouraging partial software disclosure to enable trust in data usage 20

Towards transparency-encouraging partial software disclosure...

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Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering

作者： Christian Schindler University of Mannheim Mannheim Germany

ISBN: (纸本)9781450367684

关键词： data privacy trust code abstraction transparency

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Inferring Program Transformations From Singular Examples via Big code 34

Inferring Program Transformations From Singular Examples via...

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34th IEEE/ACM International Conference on Automated Software Engineering (ASE)

作者： Jiang, Jiajun Ren, Luyao Xiong, Yingfei Zhang, Lingming Minist Educ PKU Key Lab High Confidence Software Technol Beijing Peoples R China Peking Univ EECS Dept Comp Sci & Technol Beijing Peoples R China Univ Texas Dallas Richardson TX 75083 USA

ISBN: (纸本)9781728125084

Inferring program transformations from concrete program changes has many potential uses, such as applying systematic program edits, refactoring, and automated program repair. Existing work for inferring program transformations usually rely on statistical information over a potentially large set of program-change examples. However, in many practical scenarios we do not have such a large set of program-change examples. In this paper, we address the challenge of inferring a program transformation from one single example. Our core insight is that "big code" can provide effective guide for the generalization of a concrete change into a program transformation, i.e., code elements appearing in many files are general and should not be abstracted away. We first propose a framework for transformation inference, where programs are represented as hypergraphs to enable fine-grained generalization of transformations. We then design a transformation inference approach, GENPAT, that infers a program transformation based on code context and statistics from a big code corpus. We have evaluated GENPAT under two distinct application scenarios, systematic editing and program repair. The evaluation on systematic editing shows that GENPAT significantly outperforms a state-of-the-art approach, SYDIT, with up to 5.5x correctly transformed cases. The evaluation on program repair suggests that GENPAT has the potential to be integrated in advanced program repair tools GENPAT successfully repaired 19 real-world bugs in the Defects4J benchmark by simply applying transformations inferred from existing patches, where 4 bugs have never been repaired by any existing technique. Overall, the evaluation results suggest that GENPAT is effective for transformation inference and can potentially be adopted for many different applications.

关键词： Pattern generation Program adaptation code abstraction

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Inferring program transformations from singular examples via big code 19

Inferring program transformations from singular examples via...

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Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering

作者： Jiajun Jiang Luyao Ren Yingfei Xiong Lingming Zhang Peking University Beijing China University of Texas at Dallas

ISBN: (纸本)9781728125084

Inferring program transformations from concrete program changes has many potential uses, such as applying systematic program edits, refactoring, and automated program repair. Existing work for inferring program transformations usually rely on statistical information over a potentially large set of program-change examples. However, in many practical scenarios we do not have such a large set of program-change *** this paper, we address the challenge of inferring a program transformation from one single example. Our core insight is that "big code" can provide effective guide for the generalization of a concrete change into a program transformation, i.e., code elements appearing in many files are general and should not be abstracted away. We first propose a framework for transformation inference, where programs are represented as hypergraphs to enable fine-grained generalization of transformations. We then design a transformation inference approach, GenPat, that infers a program transformation based on code context and statistics from a big code *** have evaluated GenPat under two distinct application scenarios, systematic editing and program repair. The evaluation on systematic editing shows that GenPat significantly outperforms a state-of-the-art approach, Sydit, with up to 5.5x correctly transformed cases. The evaluation on program repair suggests that GenPat has the potential to be integrated in advanced program repair tools - GenPat successfully repaired 19 real-world bugs in the Defects4J benchmark by simply applying transformations inferred from existing patches, where 4 bugs have never been repaired by any existing technique. Overall, the evaluation results suggest that GenPat is effective for transformation inference and can potentially be adopted for many different applications.

关键词： code abstraction pattern generation program adaptation

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A Cross-level Verification Methodology for Digital IPs Augmented with Embedded Timing Monitors

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ACM TRANSACTIONS ON DESIGN AUTOMATION OF ELECTRONIC SYSTEMS 2019年第3期24卷 27-27页

作者： Vinco, Sara Bombieri, Nicola Pagliari, Daniele Jahier Fummi, Franco Macii, Enrico Poncino, Massimo Politecn Torino Dept Control & Comp Engn Turin Italy Univ Verona Dept Comp Sci Verona Italy Politecn Torino Interuniv Dept Reg & Urban Studies & Planning Turin Italy

Smart systems are characterized by the integration in a single device of multi-domain subsystems of different technological domains, namely, analog, digital, discrete and power devices, MEMS, and power sources. Such challenges, emerging from the heterogeneous nature of the whole system, combined with the traditional challenges of digital design, directly impact on performance and on propagation delay of digital components. This article proposes a design approach to enhance the RTL model of a given digital component for the integration in smart systems with the automatic insertion of delay sensors, which can detect and correct timing failures. The article then proposes a methodology to verify such added features at system level. The augmented model is abstracted to SystemC TLM, which is automatically injected with mutants (i.e., code mutations) to emulate delays and timing failures. The resulting TLM model is finally simulated to identify timing failures and to verify the correctness of the inserted delay monitors. Experimental results demonstrate the applicability of the proposed design and verification methodology, thanks to an efficient sensor-aware abstraction methodology, by applying the flow to three complex case studies.

关键词： Timing monitors code abstraction systemc TLM razor sensor verification

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Practicing Domain-Specific Languages: From code to Models 18

Practicing Domain-Specific Languages: From Code to Models

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21st ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS)

作者： Gonnord, Laure Mosser, Sebastien Univ Claude Bernard Lyon 1 LIP CNRS ENS LyonINRIA F-69342 Lyon 07 France Univ Cote dAzur CNRS I3S Sophia Antipolis France

ISBN: (纸本)9781450359658

This paper describes our experience in constructing a new Domain-Specific Language course at the graduate level whose objectives is to reconciliate concepts coming from Language Design as well as Modeling domains. We illustrate the course using the reactive systems application domain, which prevents us to fall back in a toy example pitfall. This paper describes the nine stages used to guide students through a journey starting at low-level C code to end with the usage of a language design workbench. This course was given as a graduate course available at Universite Cote d'Azur (8 weeks, engineering-oriented) and Ecole Normale Superieure de Lyon (13 weeks, research-oriented).

关键词： Software Modeling Domain-Specific Languages code Generation code abstraction Reactive Systems

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On the side-effects of code abstraction 03

On the side-effects of code abstraction

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Association-for-Computing-Machinery SIGPLAN Conference on Languages Compilers and Tools for Embedded Systems (LCTES 03)

作者： De Sutter, B Vandierendonck, H De Bus, B De Bosschere, K Univ Ghent Dept Elect & Informat Syst B-9000 Ghent Belgium

ISBN: (纸本)9781581136470

More and more devices contain computers with limited amounts of memory. As a result, code compaction techniques are gaining popularity, especially when they also improve performance and power consumption, or at least not degrade it. This paper quantifies the side-effects of code abstraction on performance using extensive measurements and simulations on the SPECint2000 benchmark suite and some additional C++ programs. We show how to use profile information in order to obtain almost all the code size reduction benefits of code abstraction, yet experience almost none of its disadvantages.

关键词： experimentation performance performance code abstraction code compaction

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