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A systematic mapping study on graph machine learning for static source code analysis

INFORMATION AND SOFTWARE TECHNOLOGY 2025年 183卷

作者： Maarleveld, Jesse Guo, Jiapan Feitosa, Daniel Univ Groningen Bernoulli Inst Math Comp Sci & Artificial Intellig Nijenborgh 9 NL-9747 AG Groningen Netherlands

Context: In recent years, graph machine learning and particularly graph neural networks have seen successful and widespread applications in many fields, including static source code analysis. Such machine learning techniques enable learning on rich information networks capable of representing different relations and entities. However, there have been no comprehensive studies investigating the use of graph machine learning for static source code analysis. There is no complete systematic picture of what techniques may be considered tried and tested, and where opportunities for future improvements can still be found. Objective: The main goal of this study is to provide a broad overview of the state of the art of static source code analysis using graph machine learning. Methods: A systematic mapping was performed covering 4499 studies, presenting a final selection of 323 primary studies. Results: Among the selected studies, seven major sub-domains were identified. The use and combinations of artefacts, different graph representations, different features, and different machine learning models used were collected and categorised. Conclusions: The use of graph learning, and in particular graph neural networks, has increased significantly since 2018. Although a wide variety of methods is used, across every dimension we investigated (artefacts, graphs, features, models), we found small sets of technologies which are used in the vast majority of studies. Future opportunities lie in exploring under-explored domains more thoroughly, exploring the use of additional artefacts alongside source code, and paying more attention to interpretability and explainability.

关键词： Graph machine learning Graph neural networks static source code analysis Systematic mapping study

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The analysis of Safety Critical Software Systems

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2025年第3期51卷 774-777页

作者： Holzmann, Gerard J. Nimble Res Monrovia CA 91016 USA

We reflect on the impact of software verification techniques, as implemented in the logic model checking tool SPIN, on the development of modern safety critical software systems and reflect on future developments in the application of formal verification techniques, especially in the context of the new generation of AI-based systems and tools.

关键词： codes source coding Model checking Logic Pattern matching Analytical models Symbols Memory management Standards Software systems Formal methods program verification design verification model checking static source code analysis distributed systems concurrency the SPIN model checker the Cobra static source code analyzer artificial intelligence

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SCRUB: a tool for code reviews

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INNOVATIONS IN SYSTEMS AND SOFTWARE ENGINEERING 2010年第4期6卷 311-318页

作者： Holzmann, Gerard J. CALTECH Jet Prop Laboratory Lab Reliable Software Pasadena CA 91109 USA

This paper describes a tool called source code Review User Browser (SCRUB) that was developed to support a more effective and tool-based code review process. The tool was designed to support a large team-based software development effort of mission critical software at JPL, but can also be used for individual software development on small projects. The tool combines classic peer code review with machine-generated analyses from a customizable range of source code analyzers. All reports, whether generated by humans or by background tools, are accessed through a single uniform interface provided by SCRUB.

关键词： Peer code review static source code analysis Coding rules Coding guidelines Coding standards Compliance verification

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Exploring Violations of Programming Styles: Insights from Open source Projects 18

Exploring Violations of Programming Styles: Insights from Op...

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2nd International Conference on Computer Science and Artificial Intelligence (CSAI) / 10th International Conference on Information and Multimedia Technology (ICIMT)

作者： Yang, Chunyu Liu, Yan Yu, Jia Tongji Univ Sch Software Engn 4800 Caoan Highway Shanghai Peoples R China SEEBURGER China Inc Shanghai Peoples R China

ISBN: (纸本)9781450366069

Software project is usually a huge cooperative teamwork, programmers in the project usually have to read the code written by others and understand its implementation. A uniform and clean programming style could ensure the readability and maintainability of the project source code, especially when it becomes a legacy project. However, each programmer has his own programming habit and because of the heavy developing tasks, the programming style of the software project is far from satisfactory. Programming style does not resemble software defects which has a serious effect on program executing. Therefore, many programmers ignore the programming style directly instead of improving it. Programming style should be checked before new features are merged into software projects, just like software testing. Developing with the size of software project, some special programming style rules are violated more seriously, which need be highly focused. Furthermore, one of ultimate targets in software quality engineering is to check the programming style automatically with analysis tools because the software projects usually have an enormous quantity of source code. In this paper, static source code analysis is used for detecting the programming style problems. The source file directly or the. class files generated by the compiler are scanned then the abstract syntax tree for the source code is generated. With the help of abstract syntax tree, it is possible to detect code snippets that violate the programming style rules by traverse the tree. Our method employs the static code analysis tools to analyze several Java open source projects, and find that the programming style problems which are violated most. According to our method, each problem is also explained from personal habits, JDK version, and other aspects later. Considering all of the analysis results, a special ruleset that is recommended to pay more attention to in the future software developing is proposed. At last, progr

关键词： Programming style static source code analysis code review

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GLICE: Combining Graph Neural Networks and Program Slicing to Improve Software Vulnerability Detection 8

GLICE: Combining Graph Neural Networks and Program Slicing t...

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8th IEEE European Symposium on Security and Privacy (EuroS and P)

作者： de Kraker, Wesley Vranken, Harald Hommmersom, Arjen Open Univ Netherlands Fox IT Heerlen Netherlands Open Univ Netherlands Heerlen Netherlands Radboud Univ Nijmegen Nijmegen Netherlands

ISBN: (纸本)9798350327205

This paper introduces the GLICE (Graph Neural Network with program slice) model for static code analysis to detect vulnerabilities in source code. GLICE combines inter-procedural program slicing with a Graph Neural Network. It builds upon and extends prior work that applies program slicing (as in the SySeVR model) and Graph Neural Networks (as in the FUNDED model) for vulnerability detection. We apply GLICE on a data set of C/C++ code samples with out-of-bounds write (CWE-787) and out-ofbounds read (CWE-125) buffer overflow vulnerabilities. We perform experiments with GLICE to evaluate trade-offs in the depth of the inter-procedural analysis, and to compare GLICE with prior models by evaluating the effectiveness for vulnerability detection and the usage of resources. Our experimental results show that detection accuracy of GLICE improves up to 13% when compared to FUNDED, while the time required to train the GLICE model is about 9 times smaller. GLICE allows configuring the depth of the interprocedural analysis. Our experimental results show that increasing the depth will improve detection, which however requires more computing resources. This allows a user of GLICE to steer the trade-off between detection accuracy and computational efficiency.

关键词： Graph neural network Program slicing static source code analysis Vulnerability detection

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An Assessment of Vulnerable Detection source code Tools 50th

An Assessment of Vulnerable Detection Source Code Tools

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50th Annual Convention of the Computer-Society-of-India (CSI) on Digital Life

作者： Verma, Anoop Kumar Sharma, Aman Kumar Himachal Pradesh Univ Dept Comp Sci Shimla India

ISBN: (纸本)9789811088483;9789811088476

The commonly used programming language includes C and C++ for the software development and even introduced as a course contents in computer applications in number of institutions. As software development proceeds through various phases of system development life cycle, the design phase and coding phase have the greatest impact of the rest of phases, so every software development should have a good user interface and database design including writing a source code in order to make user interface active.

关键词： Vulnerabilities Software development source code static source code analysis Software tools

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Cobra: Fast Structural code Checking 24

Cobra: Fast Structural Code Checking

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24th ACM SIGSOFT International SPIN Symposium on Model Checking of Software (SPIN)

作者： Holzmann, Gerard J. Nimble Res Monrovia CA 91016 USA

ISBN: (纸本)9781450350778

In so % ware analysis most research has traditionally been focused on the development of tools and techniques that can be used to formally prove key correctness properties of a so % ware design. Design errors can be hard to catch without the right tools, and even a % er decades of development, the right tools can still be frustratingly hard to use. Most so % ware developers know, though, that the number of coding errors is usually much larger than the number of design errors. If something is wrong, the problem can usually be traced back to a coding mistake, and less frequently to an algorithmic error. Tools for chasing down those types of errors are indeed widely used. They are simple to use, and considered effective, although they do not offer much more than sophisticated types of trial and error. The first commercial static source code analyzers hit the market a little over a decade ago, aiming to fill the gap between ease of use and more meaningful types of code analysis. Today these tools are mature, and their use is widespread in commercial so % ware development, but they tend to be big and slow. There does not seem to be any tool of this type yet that can be used for interactive code analysis. We'll describe the design and use of a different type of static analysis tool, that is designed to be simple, small, and fast enough that it can effectively be used for interactive code analysis even for large code bases.

关键词： static source code analysis interactive analysis lexical analysis structural code analysis regular expressions token expressions

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PCLocator: A Tool Suite to Automatically Identify Configurations for code Locations 18

PCLocator: A Tool Suite to Automatically Identify Configurat...

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22nd International Systems and Software Product Line Conference (SPLC)

作者： Kuiter, Elias Krieter, Sebastian Krueger, Jacob Ludwig, Kai Leich, Thomas Saake, Gunter Otto von Guericke Univ Magdeburg Germany Harz Univ Appl Sci Wernigerode Germany METOP GmbH Magdeburg Germany

ISBN: (纸本)9781450364645

The source code of highly-configurable software is challenging to comprehend, analyze, and test. In particular, it is hard to identify all configurations that comprise a certain code location. We contribute PCLocator, a tool suite that solves this problem by utilizing static analysis tools for compile-time variability. Using BusyBox and the Variability Bugs Database (VBDb), we evaluate the correctness and performance of PCLocator. The results show that we are able to analyze files in a matter of seconds and derive correct configurations in 95% of all cases.

关键词： Software Product Line Configuration static source code analysis Preprocessor Build System

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Software Reliability Modeling and analysis via Kernel-based Approach 22

Software Reliability Modeling and Analysis via Kernel-based ...

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22nd International Conference on Engineering of Complex Computer Systems (ICECCS)

作者： Okumura, Kei Okamura, Hiroyuki Dohi, Tadashi Hiroshima Univ Grad Sch Engn Dept Informat Engn 1-4-1 Kagamiyama Higashihiroshima 7398527 Japan

ISBN: (纸本)9781538624319

Traditional software reliability analysis utilizes only the fault count data observed in testing phase, and is done independently of the source code itself. Recently, it is known that utilization of software metrics in software reliability modeling and analysis can lead to more accurate reliability estimation and fault prediction through many empirical studies. However, such a metrics-based modeling also requires a careful selection of software metrics and their measurement, which are often troublesome and cost-consuming in practice. In this paper, we propose a kernel-based approach to estimate the quantitative software reliability, where two cases are considered;multiple software metrics are used and not. In the former case, we combine the kernel regression with the well-known non-homogeneous Poisson process-based software reliability growth model (SRGM), and propose a new metrics-based SRGM. In the latter case, we perform a similarity-based analysis through a source code transformation algorithm and try to estimate the quantitative software reliability from the source code directly without measuring multiple software metrics. Numerical examples with real application programs are presented to validate our kernel-based approach in the above two cases.

关键词： software reliability software reliability growth model kernel method non-homogeneous Poisson process similarity analysis static source code analysis statistical estimation regularization fault-free probability

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Development of an Eclipse plug-in for automated detection of software maintainability problems

Development of an Eclipse plug-in for automated detection of...

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作者： Lars Alberto Vangsnes University of Bergen

学位级别：硕士

Software quality can make a large impact on the cost and speed of development, as well as on what functionality can be delivered in time. Techniques, tools and models exist for measuring and improving software quality. static code analyzers are programs which can be used to identify quality problems in the source code of software. The CISQ Specifications for Automated Quality Characteristic Measures provide a set of measures for automatic analysis, which can be implemented into a static code analyzer. Maintainability is a characteristic of software quality, and is one of four characteristics in the CISQ specification. Two implementations of the CISQ specification exist, where one of them, called MUSE, implements the maintainability characteristic. However, neither are available as plug-ins for an Integrated Development Environment (IDE). In this study, a software artifact named SQ U IDS (Software Quality Issue Detection System) was developed as a plug-in for the Eclipse IDE. This was done in order to find out how a static code analyzer can be developed to find maintainability problems in software source code, based on a standard, with focus on correctness, usability and performance. SQ U IDS analyzes Java source code, finds maintainability problems defined by the CISQ specification, marks the problems in the source code editor, and provides a software quality score according to the specification. The software artifact was evaluated by comparing results with the MUSE software (Plosch, Schurz, and Korner, 2015), providing an example of and discussing how maintainability problems can be visualized to the user, and evaluating performance by measuring the time it takes SQ U IDS to analyze five existing open-source software projects. The results show that SQ U IDS and MUSE find different problems for most of the CISQ measures, that the way SQ U IDS visualizes maintainability problems works, but may not be optimal for a larger number of problems, and that although the perf

关键词： Software Quality Maintainability CISQ Eclipse plug-in static source code analysis usability performance Abstract Syntax Tree (AST) Java

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