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18th International Conference on Advanced Computing and Analytics, ACOMPA 2024

作者： Dang, Tran Tri Le, Lam-Son RMIT University Vietnam School of Science Engineering & Technology Ho Chi Minh City Viet Nam Vietnamese-German University Faculty of Engineering Ben Cat City Binh Duong75911 Viet Nam

ISBN: (纸本)9798331542467

Due to the increasing complexity of business processes and the growing number of required features, modern software rarely operates independently. Rather, it often relies on third-party services, many of which are available in the form of API calls, to perform recurring computing tasks. While software developers and programmers alike may enjoy the benefits of API calls (e.g., integrability, efficiency, shorter time-to-market), it is crucial for them to have a thorough understanding of API usage in the entire software code. Research in API usage analysis ranges from supporting the understanding of codebase semantics to identifying important software dependencies and recognizing threats from suspicious API calls. To our knowledge, most existing work in the realm is focused on the statistical properties of large codebases. While understanding these large codebases as a whole is important, gaining knowledge of how specific software utilizes APIs is equally crucial. In this work, we propose a tool proposal for visualizing API usage of a software project. To evaluate the effectiveness of our visualization techniques, we demonstrate using a couple of open-source programs in C#. The experimental results revealed some promising aspects as well as some issues that may be addressed in future research with regard to understanding API usage. © 2024 IEEE.

关键词： API usage code analysis code visualization information visualization software visualization

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Developers' Visuo-spatial Mental Model and Program Comprehension 23

Developers' Visuo-spatial Mental Model and Program Comprehen...

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45th IEEE/ACM International Conference on Software Engineering (ICSE)

作者： Bouraffa, Abir Fuhrmann, Gian-Luca Maalej, Walid Univ Hamburg Appl Software Technol Hamburg Germany

ISBN: (纸本)9781665457019

Previous works from research and industry have proposed a spatial representation of code in a canvas, arguing that a navigational code space confers developers the freedom to organise elements according to their understanding. By allowing developers to translate logical relatedness into spatial proximity, this code representation could aid in code navigation and comprehension. However, the association between developers' code comprehension and their visuo-spatial mental model of the code is not yet well understood. This mental model is affected on the one hand by the spatial code representation and on the other by the visuo-spatial working memory of developers. We address this knowledge gap by conducting an online experiment with 20 developers following a between-subject design. The control group used a conventional tab-based code visualization, while the experimental group used a code canvas to complete three code comprehension tasks. Furthermore, we measure the participants' visuo-spatial working memory using a Corsi Block test at the end of the tasks. Our results suggest that, overall, neither the spatial representation of code nor the visuo-spatial working memory of developers has a significant impact on comprehension performance. However, we identified significant differences in the time dedicated to different comprehension activities such as navigation, annotation, and UI interactions.

关键词： code comprehension code navigation developer productivity IDE design code visualization cognitive studies

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VizProg: Identifying Misunderstandings By Visualizing Students' Coding Progress 23

VizProg: Identifying Misunderstandings By Visualizing Studen...

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CHI conference on Human Factors in Computing Systems (CHI)

作者： Zhang, Ashley Chen, Yan Oney, Steve Univ Michigan Ann Arbor MI USA Virginia Tech Blacksburg VA USA

ISBN: (纸本)9781450394215

Programming instructors often conduct in-class exercises to help them identify students that are falling behind and surface students' misconceptions. However, as we found in interviews with programming instructors, monitoring students' progress during exercises is difficult, particularly for large classes. We present VizProg, a system that allows instructors to monitor and inspect students' coding progress in real-time during in-class exercises. VizProg represents students' statuses as a 2D Euclidean spatial map that encodes the students' problem-solving approaches and progress in real-time. VizProg allows instructors to navigate the temporal and structural evolution of students' code, understand relationships between code, and determine when to provide feedback. A comparison experiment showed that VizProg helped to identify more students' problems than a baseline system. VizProg also provides richer and more comprehensive information for identifying important student behavior. By managing students' activities at scale, this work presents a new paradigm for improving the quality of live learning.

关键词： programming education at scale code visualization

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visualization of codes and code Smells with 3D Mushroom Farm Metaphor 7

Visualization of Codes and Code Smells with 3D Mushroom Farm...

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7th International Conference on Electrical Engineering and Informatics (ICEEI)

作者： Nababan, Anandhini Medianty Hendradjaya, Bayu Inst Teknol Bandung Sch Elect Engn & Informat Bandung Indonesia

ISBN: (纸本)9781728124186

code visualization presents a visual representation of the state of the code to support code comprehension activities. In addition to representing code elements (for example, methods, classes and packages) and relationships between them, previous studies of code visualization also represent metrics to indicate code smell. However, the metric value only shows vague symptoms in describing the code smell behind it. This study tries to visualize the code smell directly using detection strategies, which are formulation of one or more than one metric and its threshold value for each type of code smell. 'Smelly' elements are immediately shown in code visualization according to the predetermined detection strategies. 3D mushroom farm metaphor is a new metaphor proposed in this study for code visualization. Through code visualization in a familiar natural 3D environment, code properties are displayed in an attractive manner. The presented code properties are chosen by considering object-oriented paradigm key ideas. During this time, there has never been a fundamental reason as to why a specific property was chosen to be included in a code visualization metaphor. Therefore, this study questioned code properties visualized to participants of the evaluation: is the early comprehension of the code sufficient enough or should it be added /reduced. The evaluation results showed that the code smell that was immediately shown in the visualization could be captured by the user correctly. All evaluated participants managed to identify all the smelly elements. Broadly speaking, participants understood the purpose of visualization and agreed that code visualization with the 3D mushroom farm metaphor is intuitive and easy to use. All participants stated that they needed all code properties displayed in code visualization with the 3D mushroom farm metaphor, although there were participants who proposed several properties to be added to the visualization.

关键词： code visualization 3D mushroom farm metaphor detection strategy code smell

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Causette: User-Controlled Rearrangement of Causal Constructs in a code Editor 30

Causette: User-Controlled Rearrangement of Causal Constructs...

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30th IEEE/ACM International Conference on Program Comprehension (ICPC)

作者： Martin, Alice Magnaudet, Mathieu Conversy, Stephane Univ Toulouse ENAC Toulouse France

ISBN: (纸本)9781450392983

Programming interaction usually involves specifying causal relationships such as input events triggering a state change or the propagation of values. Such code may reside in several locations and its execution is driven by multiple causal chains, which hinders the programmer's ability to understand and fix it. We designed Causette, a set of four novel interaction techniques for a code editor. They consist in rearranging causal constructs on demand to make the code representation consistent with the causal chain being analyzed by the user. We ran an experiment showing that Causette may be more usable than a regular editor for some code understanding tasks. This work suggests that rearranging interaction code may help developers better understand and fix it.

关键词： Interaction programming code visualization causality

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Machine Learning Classification of Obfuscation using Image visualization 18

Machine Learning Classification of Obfuscation using Image V...

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18th International Conference on Security and Cryptography (SECRYPT)

作者： Parker, Colby B. McDonald, J. Todd Damopoulos, Dimitrios Univ S Alabama Dept Comp Sci Mobile AL 36688 USA

ISBN: (纸本)9789897585241

As the need for new techniques to analyze obfuscated software has grown, recent work has shown the ability to analyze programs via machine learning in order to perform automated metadata recovery. Often these techniques really on disassembly or other means of direct code analysis. We showcase an approach combining code visualization and image analysis via convolutional neural networks capable of statically classifying obfuscation transformations. By first turning samples into gray scale images, we are able to analyze the structure and side effects of transformations used in the software with no heavy code analysis or feature preparation. With experimental results samples produced with the Tigress and OLLVM obfuscators, our models are capable of labeling transformations with F1-scores between 90% and 100% across all tests. We showcase our approach via models designed as both a binary classification problem as well as a multi label and multi output problem. We retain high performance even in the presence of multiple transformations in a file.

关键词： Software Protection MATE Attacks code visualization Neural Networks Obfuscation

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Automatically Generated Visual Profiles of code Solutions as Feedback for Students

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INFORMATION 2022年第9期13卷 415-415页

作者： Swacha, Jakub Univ Szczecin Dept IT Management PL-71004 Szczecin Poland

Providing students feedback on their exercise solutions is a crucial element of computer programming education. Such feedback can be generated automatically and can take various forms. This paper introduces and proposes the use of visual profiles of code solutions as a form of automatically generated feedback to programming students. The visual profiles are based on the frequency of code elements belonging to six distinct classes. The core idea is to visually compare a profile of a student-submitted solution code to the range of profiles of accepted solutions (including both reference solutions provided by instructors and solutions submitted by students who successfully passed the same exercise earlier). The advantages of the proposed approach are demonstrated on a number of examples based on real-world data.

关键词： interactive learning environments computer programming education code visualization automatic feedback

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RefacTutor: An Interactive Tutoring System for Software Refactoring 1

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11th International Conference on Computer Supported Education

作者： Haendler, Thorsten Neumann, Gustaf Smirnov, Fiodor Vienna Univ Econ & Business WU Vienna Inst Informat Syst & New Media Vienna Austria

ISBN: (数字)9783030584597

ISBN: (纸本)9783030584580;9783030584597

While software refactoring is considered important to manage software complexity, it is often perceived as difficult and risky by software developers and thus neglected in practice. In this article, we present refacTutor, an interactive tutoring system for promoting software developers' practical competences in software refactoring. The tutoring system provides immediate feedback to the users regarding the quality of the software design and the functional correctness of the (modified) source code. In particular, after each code modification (refactoring step), the user can review the results of run-time regression tests and compare the actual software design (as-is) with the targeted design (to-be) in order to check quality improvement. For this purpose, structural and behavioral diagrams of the Unified Modeling Language (UML2) representing the as-is software design are automatically reverse-engineered from source code. The to-be UML design diagrams can be pre-specified by the instructor. To demonstrate the technical feasibility of the approach, we provide a browser-based software prototype in Java accompanied by a collection of exercise examples. Moreover, we specify a viewpoint model for software refactoring, allocate exercises to competence levels and describe an exemplary path for teaching and training.

关键词： Intelligent tutoring system Software refactoring Software design code visualization Unified Modeling Language (UML2) Software-engineering education and training Interactive training environment

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KernelGraph: Understanding the kernel in a graph

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INFORMATION visualization 2019年第3期18卷 283-296页

作者： Shi, Jianjun Ji, Weixing Zhang, Jingjing Gao, Zhiwei Wang, Yizhuo Shi, Feng Beijing Inst Technol Sch Comp Sci & Technol 5 South Zhongguancun St Beijing 100081 Peoples R China

The Linux kernel has grown to 20 million lines of code, which have been contributed by almost 14,000 programmers. The complexity of the Linux kernel challenges the kernel maintenance and makes comprehending the kernel more difficult for developers learning the kernel. Automated tool support is crucial for comprehending such a large-scale program involving a high volume of code. In this article, we present KernelGraph, which enhances understanding of the Linux kernel by providing a visual representation of kernel internals. KernelGraph resembles online map systems and facilitates kernel code navigation in an intuitive and interactive way. We describe the key techniques used in KernelGraph to process the vast amount of information in the kernel codebase quickly. We also implemented two applications built atop KernelGraph to enhance kernel comprehension. KernelGraph was presented to 30 participants, who were asked several questions about their kernel comprehension in a controlled study. Our experimental results show that, compared with other source code comprehension tools, KernelGraph improves kernel comprehension by enabling people to visually browse the kernel code and by providing an effective means for exploring the kernel structure. The ability to switch seamlessly between high-level views and source code significantly reduces the gap between source code and high-level mental representation. KernelGraph can be easily extended to support visualizations of other large-scale codebases.

关键词： Linux kernel code visualization program comprehension

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A Deep Learning Approach to Program Similarity 1

A Deep Learning Approach to Program Similarity

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1st International Workshop on Machine Learning and Software Engineering in Symbiosis (MASES)

作者： Marastoni, Niccolo Giacobazzi, Roberto Dalla Preda, Mila Univ Verona Verona Italy

ISBN: (纸本)9781450359726

In this work we tackle the problem of binary code similarity by using deep learning applied to binary code visualization techniques. Our idea is to represent binaries as images and then to investigate whether it is possible to recognize similar binaries by applying deep learning algorithms for image classification. In particular, we apply the proposed deep learning framework to a dataset of binary code variants obtained through code obfuscation. These binary variants exhibit similar behaviours while being syntactically different. Our results show that the problem of binary code recognition is strictly separated from simple image recognition problems. Moreover, the analysis of the results of the experiments conducted in this work lead us to the identification of interesting research challenges. For example, in order to use image recognition approaches to recognize similar binary code samples it is important to further investigate how to build a suitable mapping from executables to images.

关键词： code similarity deep-learning obfuscation code visualization

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