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On Twitter Bots Behaving Badly: A Manual and Automated Analysis of Python code patterns on GitHub

JOURNAL OF WEB ENGINEERING 2020年第8期18卷 801-835页

作者： Millimaggi, Andrea Daniel, Florian Politecn Milan Via Ponzio 34-5 I-20133 Milan Italy

Bots, i.e., algorithmically driven entities that behave like humans in online communications, are increasingly infiltrating social conversations on the Web. If not properly prevented, this presence of bots may cause harm to the humans they interact with. This article aims to understand which types of abuse may lead to harm and whether these can be considered intentional or not. We manually review a dataset of 60 Twitter bot code repositories on GitHub, derive a set of potentially abusive actions, characterize them using a taxonomy of abstract code patterns, and assess the potential abusiveness of the patterns. The article then describes the design and implementation of a code pattern recognizer and uses the pattern recognizer to automatically analyze a dataset of 786 Python bot code repositories. The study does not only reveal the existence of 28 communication-specific code patterns - which could be used to assess the harmfulness of bot code - but also their consistent presence throughout all studied repositories.

关键词： Bots Harm Abuse code patterns Pattern recognition GitHub Twitter Python

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On Twitter Bots Behaving Badly: Empirical Study of code patterns on GitHub 19th

On Twitter Bots Behaving Badly: Empirical Study of Code Patt...

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19th International Conference on Web Engineering (ICWE)

作者： Millimaggi, Andrea Daniel, Florian Politecn Milan Via Ponzio 34-5 I-20133 Milan Italy

ISBN: (纸本)9783030192747;9783030192730

Bots, i.e., algorithmically driven entities that behave like humans in online communications, are increasingly infiltrating social conversations on the Web. If not properly prevented, this presence of bots may cause harm to the humans they interact with. This paper aims to understand which types of abuse may lead to harm and whether these can be considered intentional or not. We manually review a dataset of 60 Twitter bot code repositories on GitHub, derive a set of potentially abusive actions, characterize them using a taxonomy of abstract code patterns, and assess the potential abusiveness of the patterns. The study does not only reveal the existence of 31 communication-specific code patterns - which could be used to assess the harmfulness of bot code - but also their presence throughout all studied repositories.

关键词： Bots Harm Abuse code patterns GitHub Twitter

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Visualizing code patterns in Novice Programmers 18

Visualizing Code Patterns in Novice Programmers

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23rd Western Canadian Conference on Computing Education

作者： Bulmer, Jeff Pinchbeck, Angie Hui, Bowen Univ British Columbia Dept Comp Sci Vancouver BC Canada

ISBN: (纸本)9781450358057

Many researchers have investigated the difficulties faced by novice programmers. However, these approaches have so far focused primarily on the identification and correction of common syntax errors, or that of topic difficulty in the CS1 curriculum. Meanwhile, poor coding practices adopted by students have gone mostly unaddressed. While these practices may not necessarily lead to erroneous code, they may nonetheless indicate areas of difficulty and lead to poorly structured programs. To address these issues, our project examines students' coding habits and common errors in CS1 exercises gathered from 77 first-year students. This data was collected in real time so that we may later reconstruct the thought process of the student while solving the programming exercises. To assist our analysis, we built a code visualizer that animates the programming process dynamically and summarizes error metrics simultaneously. Our ultimate goal is to use the code visualizer to help either an instructor or a student to identify poor programming practices during the coding process. With the error metrics gathered, an instructor can inspect potential improvements in coding behaviors for an individual student at a given point in time or over time, and identify bad coding habits common to populations of students.

关键词： Source code snapshot analysis programming session trace analysis code patterns programming behavior error diagnosis CS1 code metrics learning analytics self-regulation

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Advancements in automated program repair: a comprehensive review

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KNOWLEDGE AND INFORMATION SYSTEMS 2025年第6期67卷 4737-4783页

作者： Dikici, Sena Bilgin, Turgay Tugay Bursa Tech Univ Comp Engn Dept Bursa Turkiye

This review paper presents a comprehensive examination of automated program repair (APR) and its significant contribution to the field of modern software engineering. It elucidates how APR methodologies markedly mitigate manual debugging needs by automating the detection and resolution of software glitches. The study encompasses an in-depth exploration of three primary categories of APR techniques: template-based, machine learning, and deep learning approaches, drawing from an exhaustive evaluation of 41 APR tools. Each category showcases distinct strategies for managing diverse software errors, underscoring the breadth and effectiveness of current APR methodologies. Template-based APR solutions utilize pre-established patterns to efficiently tackle common coding issues, while machine learning-driven approaches dynamically devise repair strategies from historical bug-fix datasets. Deep learning methods extend error rectification boundaries by delving into the semantic context of code, yielding more precise adjustments. The ongoing advancement of APR technologies necessitates researchers to address critical challenges, including the integration of semantic-syntactic analyses, mitigation of data scarcity, optimization of cross-platform tools, development of context-aware approaches, enhancement of fault localization and patch validation processes, and establishment of standardized performance evaluation metrics. This comprehensive analysis underscores the pivotal role of APR in enhancing software efficiency and reliability, representing significant progress in software development and maintenance practices.

关键词： Automated program repair Software bugs Machine learning Deep learning code patterns

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Detecting Infeasible Branches Based on code patterns

Detecting Infeasible Branches Based on Code Patterns

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Software Evolution Week / IEEE Conference on Software Maintenance, Reengineering, and Reverse Engineering (CSMR-WCRE)

作者： Ding, Sun Zhang, Hongyu Tan, Hee Beng Kuan Nanyang Technol Univ Singapore 639798 Singapore Tsinghua Univ Beijing 100084 Peoples R China

ISBN: (纸本)9781479937523

Infeasible branches are program branches that can never be exercised regardless of the inputs of the program. Detecting infeasible branches is important to many software engineering tasks such as test case generation and test coverage measurement. Applying full-scale symbolic evaluation to infeasible branch detection could be very costly, especially for a large software system. In this work, we propose a code pattern based method for detecting infeasible branches. We first introduce two general patterns that can characterize the source code containing infeasible branches. We then develop a tool, called Pattern-based method for Infeasible branch Detection (PIND), to detect infeasible branches based on the discovered code patterns. PIND only performs symbolic evaluation for the branches that exhibit the identified code patterns, therefore significantly reduce the number of symbolic evaluations required. We evaluate PIND from two aspects: accuracy and efficiency. The experimental results show that PIND can effectively and efficiently detect infeasible branches in real-world Java and Android programs. We also explore the application of PIND in measuring test case coverage.

关键词： Infeasible branch test case coverage code patterns program analysis

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PRIVBENCH: A Benchmark Capturing Privilege Escalation Vulnerabilities in Android 21

PRIVBENCH: A Benchmark Capturing Privilege Escalation Vulner...

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21st International Conference on Privacy, Security and Trust

作者： Tebib, Mohammed El Amin Aktouf, Oum-El-Kheir Andre, Pascal Graa, Mariem Univ Grenoble Alpes Inst Engn UGA LCIS Lab Grenoble INP Valence France Nantes Univ LS2N UMR 6004 Nantes France

ISBN: (纸本)9798350367102;9798350367096

Security code smells are receiving increasing attention in the domain of Android app development. They serve as coding guidelines aimed at identifying vulnerabilities originating from the application's source code. Numerous related tools have been proposed to align with DevSecOps guidelines. However, they lack of comparable effort in creating benchmarks for open-source apps, making the thorough evaluation of these tools challenging, and requiring time-consuming manual effort. In this paper, we propose PRIVBENCH, an evolving benchmark that captures vulnerabilities related to the Android ecosystem. It incorporates multiple code patterns for each vulnerability. To showcase its significance, we used it to evaluate two well-known tools used to identify Android security code smells. This evaluation focused on Privilege Escalation (PE) vulnerabilities and we present their performance in detecting the vulnerabilities within their scopes. We believe that our benchmark can be useful for advancing the capabilities of state-of-the-art tools, enhancing their effectiveness in vulnerability detection, and increasing developers awareness to evade privilege escalation vulnerabilities.

关键词： Android PE vulnerabilities Benchmark code patterns Security Smells DevSecOps

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E-APK: Energy pattern detection in decompiled android applications

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JOURNAL OF COMPUTER LANGUAGES 2023年 76卷

作者： Gregorio, Nelson Bispo, Joao Fernandes, Joao Paulo de Medeiros, Sergio Queiroz Univ Porto Fac Engn Porto Portugal LIACC Porto Portugal INESC TEC Porto Portugal Univ Fed Rio Grande do Norte Natal Brazil

Energy efficiency is a non-functional requirement that developers must consider, particularly when building software for battery-operated devices like mobile ones: a long-lasting battery is an essential requirement for an enjoyable user *** previous studies, it has been shown that many mobile applications include inefficiencies that cause battery to be drained faster than necessary. Some of these inefficiencies result from software patterns that have been catalogued, and for which more energy-efficient alternatives are also *** existing catalogues, however, assume as a fundamental requirement that one has access to the source code of an application in order to be able to analyse it. This requirement makes independent energy analysis challenging, or even impossible, e.g. for a mobile user or, most significantly, an App Store trying to provide information on how efficient an application being submitted for publication *** study the viability of looking for known energy patterns in applications by decompiling them and analysing the resulting code. For this, we decompiled and analysed 420 open-source applications by extending an existing tool, which is now capable of transparently decompiling and analysing android applications. With the collected data, we performed a comparative study of the presence of four energy patterns between the source code and the decompiled *** performed two types of analysis: (i) comparing the total number of energy pattern detections;(ii) comparing the similarity between energy pattern detections. When comparing the total number of detections in source code against decompiled code, we found that 79.29% of the applications reported the same number of energy pattern *** test the similarity between source code and APKs, we calculated, for each application, a similarity score based on our four implemented detectors. Of all applications, 35.76% achieved a perfect similarity score of 4, and 89.40% got a score of 3 or

关键词： code patterns Energy efficiency Static analysis Decompiler Mobile Android Metaprogramming Compilers

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On the diversity and frequency of code related to mathematical formulas in real-world Java projects

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JOURNAL OF SYSTEMS AND SOFTWARE 2021年 172卷 110863-110863页

作者： Moseler, Oliver Lemmer, Felix Baltes, Sebastian Diehl, Stephan Univ Trier Comp Sci Trier Germany Univ Adelaide Sch Comp Sci Adelaide SA Australia

In this paper, the term formula code refers to fragments of source code that implement a mathematical formula. We present empirical studies that analyze the diversity and frequency of formula code in open-source-software projects. In an exploratory study, we investigated what kinds of formulas are implemented in real-world Java projects and derived syntactical patterns and constraints. We refined these patterns for sum and product formulas to automatically detect formula code in software archives and to reconstruct the implemented formula in mathematical notation. In a quantitative study of a large sample of engineered Java projects on GitHub we analyzed the frequency of formula code and estimated that one of 700 lines of code in this sample implements a sum or product formula. For a sample of scientific-computing projects, we found that one of 100 lines of code implements a sum or product formula. To assess the need for tool support, we investigated the helpfulness of comments for program understanding in a sample of formula-code fragments and performed an online survey. Our findings provide first insights into the characteristics of formula code, that can motivate further studies on the role of formula code in software projects and the design of formula-related tools. (C) 2020 Elsevier Inc. All rights reserved.

关键词： Formula code Qualitative study code patterns GitHub quantitative study

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Model-Driven Fault Injection in Java Source code 31

Model-Driven Fault Injection in Java Source Code

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IEEE 31st International Symposium on Software Reliability Engineering (ISSRE)

作者： Rodrigues Jr, Elder Montecchi, Leonardo Ceccarelli, Andrea Univ Estadual Campinas Campinas SP Brazil Univ Firenze Florence Italy

ISBN: (纸本)9781728198705

The injection of software faults in source code requires accurate knowledge of the programming language, both to craft faults and to identify injection locations. As such, fault injection and code mutation tools are typically tailored for a specific language and have limited extensibility. In this paper we present a model-driven approach to craft and inject software faults in source code. While its concrete application is presented for Java, the workflow we propose does not depend on a specific programming language. Following Model-Driven Engineering principles, the faults and the criteria to select injection locations are described using structured, machine-readable specifications based on a domain-specific language. Then, automated transformations craft artifacts based on OCL and Java, which represent the faults to be injected and are able to select the candidate injection locations. Finally, artifacts are executed against the target source code, performing the injection in the desired locations. We devise a supporting tool and exercise the approach injecting 13 different kinds of software faults in the Java source code of six different projects.

关键词： Software faults fault libraries metamodel OCL code patterns Java

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Energy Refactorings for Android in the Large and in the Wild 27

Energy Refactorings for Android in the Large and in the Wild

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27th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER)

作者： Couto, Marco Saraiva, Joao Fernandes, Joao Paulo Univ Minho HASLab INESC TEC Braga Portugal Univ Coimbra CISUC Coimbra Portugal

ISBN: (纸本)9781728151434

Improving the energy efficiency of mobile applications is a timely goal, as it can contribute to increase a device's usage time, which most often is powered by batteries. Recent studies have provided empirical evidence that refactoring energy-greedy code patterns can in fact reduce the energy consumed by an application. These studies, however, tested the impact of refactoring patterns individually, often locally (e.g., by measuring method-level gains) and using a small set of applications. We studied the application-level impact of refactorings, comparing individual refactorings, among themselves and against the combinations on which they appear. We use scenarios that simulate realistic application usage on a large-scale repository of Android applications. To fully automate the detection and refactoring procedure, as well as the execution of test cases, we developed a publicly available tool called Chimera. Our findings include statistical evidence that i) individual refactorings produce consistent gains, but with different impacts, ii) combining as much refactorings as possible most often, but not always, increases energy savings when compared to individual refactorings, and iii) a few combinations are harmful to energy savings, as they can actually produce more losses than gains. We prepared a set of guidelines for developers to follow, aiding them on deciding how to refactor and consistently reduce energy.

关键词： Android Energy code patterns Refactorings

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