An empirical study of developers’ discussions about security challenges of different programming languages

Croft, Roland; Xie, Yongzheng; Zahedi, Mansooreh; Babar, Muhammad Ali

doi:10.1007/s10664-021-10054-w

Cited by 11 publications

(14 citation statements)

References 71 publications

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“…Therefore, we clean up the code snippets marked with <code></code> from posts using a similar approach to previous work. Since HTML tags ( e.g ., <p>, <pre>, and <b>) and URLs do not contribute to the creation of nautical topics in the topic modeling process, we remove all HTML tags and URLs from the text in the corpus ( Croft et al, 2022 ). In step three, we continue to remove numbers, punctuation, and other non-alphabetic characters from the dataset to enable better topic modeling results.…”

Section: Methodsmentioning

confidence: 99%

“…In this empirical process, we systematically varied the K range from 5 to 60, increasing by 1 at each iteration ( e.g ., 5, 6, 7,…, 60). In this way, we identified the optimal K value that generates topics with high coherence scores ( Croft et al, 2022 ). Concurrently, we computed a coherence score that is tailored to the LDA model for each experiment that is fitted with the K value.…”

Section: Methodsmentioning

confidence: 99%

“…From this perspective, numerous academics have recently conducted research using data from Stack Overflow to explore certain aspects of software design and development, including chatbot development, security, testing, mobile development, and IOT development ( Vasilescu, 2014 ; Ahmad et al, 2018 ). Although there have been some valuable initiatives, there is currently a lack of comprehensive studies that investigate the entire field of information security utilizing topic modeling-based semantic content analysis of data from online Q&A platforms ( Vasilescu, 2014 ), with only a few notable exceptions ( Yang et al, 2016 ; Lopez et al, 2018 , 2019 ; Croft et al, 2022 ). Undoubtedly, we anticipate that the analysis of data from interactive Q&A communities will have noteworthy inferences and insights for comprehending the chronological progression of information security.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, numerous studies have focused on online Q&A forums similar to Stack Overflow (Stack Exchange, Quora, Kaggle, and Reddit), which is a crucial venue for developers from diverse backgrounds in the IT industry to share knowledge and experiences ( Vasilescu, 2014 ; Ahmad et al, 2018 ; Croft et al, 2022 ). In particular, several studies have been carried out based on the examination of posts from Q&A forums to investigate the issues and difficulties faced by developers and security specialists in various cybersecurity scenarios ( Yang et al, 2016 ; Lopez et al, 2018 , 2019 ; Croft et al, 2022 ). Yang et al (2016) analyzed the security-related posts of developers on the Stack Overflow Q&A website with a topic modeling approach.…”

Section: Introductionmentioning

confidence: 99%

“…From a similar perspective, Lopez et al (2018) analyzed a series of questions in the security channel of Stack Overflow to draw inferences about how developers use Q&A resources to solve security problems. Croft et al (2022) conducted a large-scale study of the security challenges of 15 programming languages by analyzing developers’ discussions on Stack Overflow and GitHub using a topic modeling approach.…”

Section: Introductionmentioning

confidence: 99%

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What are developers talking about information security? A large-scale study using semantic analysis of Q&A posts

Gurcan

2024

PeerJ Computer Science

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Background Digitalization and rapid technological improvement in the present day bring numerous benefits, but they also raise the complexity and diversity of cyber security risks, putting critical information security issues on the agenda. Growing issues and worries about information security endanger not only the security of individuals and organizations but also global social and economic stability. Methods This study investigates the issues and challenges regarding information security by analyzing all the postings on ISSE (Information Security Stack Exchange), a Q&A website focused on information security. In order to identify the primary topics addressed in postings shared on the ISSE platform, we employed a probabilistic topic modeling method called latent Dirichlet allocation (LDA), which is generative in nature and relies on unsupervised machine learning processes. Results Through this investigation, a total of 38 topics were identified, demonstrating the present state of information security issues and challenges. Considering these topics, a comprehensive taxonomy of seven categories was devised to address information security issues, taking into account their backgrounds and perspectives. Subsequently, we conducted an examination of the prevalence and complexity of the matters at hand. In addition, we have defined the prevailing technologies utilized in the realm of information security, including tasks, certifications, standards, methods, tools, threats, and defenses. We have provided a number of implications for different stakeholders, including academics, developers, educators, and practitioners, who are working towards advancing the field of information security.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%