System logs are vital for diagnosing system failures, with log parsing converting unstructured logs into structured data. Existing methods fall into two categories: non-deep-learning approaches cluster logs based on s...
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Drones are emerging technologies in agriculture, replacing manual pesticide spraying due to harmful side effects on personnel. It is designed to reduce time and labor costs for farmers. This paper aims to develop a so...
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As the importance of sustainability increases in various sectors due to the effects of climate change, environmental responsibility is expected to be prioritized in the software development sector. This study examines...
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Microservices architecture has advantages such as independent development, independent deployment, scalability, and reusability. However, faults are inevitable during the operation of microservices systems. This paper...
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software vulnerability detection aims to identify latent weaknesses in source code to protect software systems from attacks. Most of the current neural network-based approaches rely on preprocessing source codes using...
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ISBN:
(纸本)9798350395693;9798350395686
software vulnerability detection aims to identify latent weaknesses in source code to protect software systems from attacks. Most of the current neural network-based approaches rely on preprocessing source codes using code parsers to obtain program dependency graphs for downstream vulnerability detection tasks. However, as source codes may contain incorrect format and special functions, this paradigm may cause parsing errors due to their failure to satisfy the parser's presets or requirements. In addition, modern software development often involves the integration of multiple programming languages, presenting challenges for conventional code parsers that are designed for specific programming languages. To address these issues, we present a novel detection framework that can identify software vulnerabilities in a programming language-agnostic manner without relying on code parsers. We conduct extensive experiments on the CodeXGLUE, Reveal, and FUNDED public datasets and evaluate them against leading vulnerability detection benchmarks. Experimental results show that BABEL sets new performance standards, demonstrating superior accuracy and F1 scores across various tasks, including those in language-independent settings, demonstrating the applicability of BABEL in real-world application scenarios. Our code is available at https://***/gdufsnlp/BABEL
With the advancement of quantum computing technology, a pressing need arises to assess its potential implications on existing systems and infrastructures. In this paper, we delve into the interplay between quantum com...
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ISBN:
(纸本)9783031492686;9783031492693
With the advancement of quantum computing technology, a pressing need arises to assess its potential implications on existing systems and infrastructures. In this paper, we delve into the interplay between quantum computing and 5G technology, with a specific focus on its profound impact on cryptography and the emergence of post-quantum techniques. We analyse the potential vulnerabilities quantum computers pose to conventional cryptographic algorithms employed in 5G networks. Our research investigates the challenges and opportunities that arise at the intersection of quantum computing and 5G, ultimately aiming to contribute to the development of secure and future-proof communication systems.
This research proposal aims to employ machine learning techniques to analyze employee retention factors in software Companies, recognizing its crucial role in organizational success and the potential costs of high tur...
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We propose a method for automatically discovering likely program invariants for persistent memory (PM), which is a type of fast and byte-addressable storage device that can retain data after power loss. The invariants...
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ISBN:
(数字)9798400712487
ISBN:
(纸本)9798400712487
We propose a method for automatically discovering likely program invariants for persistent memory (PM), which is a type of fast and byte-addressable storage device that can retain data after power loss. The invariants, also called PM properties or PM requirements, specify which objects of the program should be made persistent and in what order. Our method relies on a combination of static and dynamic analysis techniques. Specifically, it relies on static analysis to compute dependence relations between LOAD/STORE instructions and instruments the information into the executable program. Then, it relies on dynamic analysis of the execution traces and counterfactual reasoning to infer PM properties. With precisely computed dependence relations, the inferred properties are necessary conditions for the program to behave correctly through power loss and recovery;with imprecise dependence relations, these are likely program invariants. We have evaluated our method on benchmark programs including eight persistent data structures and two distributed storage applications, Redis and Memcached. The results show that our method can infer PM properties quickly and these properties are of higher quality than those inferred by a state-of-the-art technique. We also demonstrate the usefulness of the inferred properties by leveraging them for PM bug detection, which significantly improves the performance of a state-of-the-art PM bug detection technique.
It is now commonplace for organizations to pay developers to work on specific open source software (OSS) projects to pursue their business goals. Such paid developers work alongside voluntary contributors, but given t...
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This study proposes a set of improved defect categorization criteria and analysis strategies based on a synthesis of a variety of commonly used software defect categorization methods, combined with the actual software...
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