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Journal articles on the topic 'Stackoverflow'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Joorabchi, Arash, Michael English, and Abdulhussain E. Mahdi. "Text mining stackoverflow." Journal of Enterprise Information Management 29, no. 2 (2016): 255–75. http://dx.doi.org/10.1108/jeim-11-2014-0109.

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Purpose – The use of social media and in particular community Question Answering (Q & A) websites by learners has increased significantly in recent years. The vast amounts of data posted on these sites provide an opportunity to investigate the topics under discussion and those receiving most attention. The purpose of this paper is to automatically analyse the content of a popular computer programming Q & A website, StackOverflow (SO), determine the exact topics of posted Q & As, and narrow down their categories to help determine subject difficulties of learners. By doing so, the au

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Xiong, Yunxiang, Zhangyuan Meng, Beijun Shen, and Wei Yin. "Developer Identity Linkage and Behavior Mining Across GitHub and StackOverflow." International Journal of Software Engineering and Knowledge Engineering 27, no. 09n10 (2017): 1409–25. http://dx.doi.org/10.1142/s0218194017400034.

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Nowadays, software developers are increasingly involved in GitHub and StackOverflow, creating a lot of valuable data in the two communities. Researchers mine the information in these software communities to understand developer behaviors, while previous works mainly focus on mining data within a single community. In this paper, we propose a novel approach to developer identity linkage and behavior mining across GitHub and StackOverflow. This approach links the accounts from two communities using a CART decision tree, leveraging the features from usernames, user behaviors and writing styles. Th

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Putra, Bagus Geriansyah, and Naim Rochmawati. "Klasifikasi Berdasarkan Question dalam Stack Overflow Menggunakan Algoritma Naïve Bayes." Journal of Informatics and Computer Science (JINACS) 2, no. 04 (2021): 259–67. http://dx.doi.org/10.26740/jinacs.v2n04.p259-267.

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Abstrak—Stackoverflow merupakan sebuah website yang menyediakan banyak informasi tentang pemrograman. Pengguna dapat berinteraksi dengan pengguna lainnya dalam sebuah forum diskusi yang diajukan. Pengguna dapat mengajukan sebuah pertanyaan yang kemudian akan ditanggapi oleh pengguna lain. Ketika mengajukan sebuah pertanyaan, pengguna harus memasukkan kategori yang tepat pada pertanyaan yang diajukan agar mendapatkan respons atau jawaban yang sesuai. Berdasarkan beberapa kasus yang terjadi masih banyak pengguna website mengalami kebingungan ketika memilih kategori pertanyaan yang diajukan. Akib

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Singh, Prabhnoor, Rajkanwar Chopra, Ojasvi Sharma, and Rekha Singla. "Stackoverflow tag prediction using tag associations and code analysis." Journal of Discrete Mathematical Sciences and Cryptography 23, no. 1 (2020): 35–43. http://dx.doi.org/10.1080/09720529.2020.1721857.

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Pagano, Dennis, and Walid Maalej. "How Do Developers Blog?" ACM SIGSOFT Software Engineering Notes 46, no. 3 (2021): 26–29. http://dx.doi.org/10.1145/3468744.3468753.

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A decade ago, the rise of GitHub and StackOverflow as social version control and knowledge sharing environments was about to start. Social media like Twitter were mocked by some software engineering researchers and practitioners as "tools for kids not professionals". At that time, we published one of the first papers [12] on social media in software engineering at MSR 2011, the Mining Software Repositories Conference.

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Sankha Subhra Paul, R. R., and Ashish Tripathi. "Social Influence and learning pattern analysis: Case studies in Stackoverflow." International Journal of IT-based Social Welfare Promotion and Management 2, no. 1 (2015): 1–10. http://dx.doi.org/10.21742/ijswpm.2015.2.1.01.

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Dargahi Nobari, Arash, Mahmood Neshati, and Sajad Sotudeh Gharebagh. "Quality-aware skill translation models for expert finding on StackOverflow." Information Systems 87 (January 2020): 101413. http://dx.doi.org/10.1016/j.is.2019.07.003.

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Huang, Weizhi, Wenkai Mo, Beijun Shen, Yu Yang, and Ning Li. "Automatically Modeling Developer Programming Ability and Interest Across Software Communities." International Journal of Software Engineering and Knowledge Engineering 26, no. 09n10 (2016): 1493–510. http://dx.doi.org/10.1142/s0218194016400143.

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Developer profile plays an important role in software project planning, developer recommendation, personnel training, and other tasks. Modeling the ability and interest of developers is its key issue. However, most existing approaches require manual assessment, like 360[Formula: see text] performance evaluation. With the emergence of social networking sites such as StackOverflow and Github, a vast amount of developer information is created on a daily basis. Such personal and social context data has huge potential to support automatic and effective developer ability evaluation and interest mini

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Abdalkareem, Rabe, Emad Shihab, and Juergen Rilling. "On code reuse from StackOverflow: An exploratory study on Android apps." Information and Software Technology 88 (August 2017): 148–58. http://dx.doi.org/10.1016/j.infsof.2017.04.005.

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Shejwalkar, Virat, Arun Ganesh, Rajiv Mathews, et al. "Recycling Scraps: Improving Private Learning by Leveraging Checkpoints]{Recycling Scraps: Improving Private Learning by Leveraging Checkpoints." Proceedings on Privacy Enhancing Technologies 2025, no. 2 (2025): 607–28. https://doi.org/10.56553/popets-2025-0079.

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DP training pipelines for modern neural networks are iterative and generate multiple checkpoints. However, all except the final checkpoint are discarded after training. In this work, we propose novel methods to utilize intermediate checkpoints to improve prediction accuracy and estimate uncertainty in DP predictions. First, we design a general framework that uses aggregates of intermediate checkpoints during training to increase the accuracy of DP ML techniques. Specifically, we demonstrate that training over aggregates can provide significant gains in prediction accuracy over the existing sta

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Halachev, Petar, Aleksandra Todeva, Gergana Georgieva, and Marina Jekova. "CONTEMPORARY ASPECTS IN THE SELECTION OF TOOLS AND TECHNOLOGIES FOR DEVELOPING WEB SITES." International Conference on Technics, Technologies and Education, no. 1 (2018): 125–31. http://dx.doi.org/10.15547/ictte.2018.04.002.

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he report explores and analyzes the application of the most popular programming languages from different organizations: GitHub; Stackoverflow; the TIOBE's Community index. The main client technologies: HTML; CSS; JavaScript; Typescript are presented and analysed. Features are characterized and the advantages and the disadvantages of the server technologies are described: Java; PHP; Python; Ruby. The application areas for web site development technologies have been defined. The creation of a quality web site is a complex and complicated process, but by observing some guidelines and recommendati

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Greenberg, Jane, Angela Murillo, and John A. Kunze. "Ontological Empowerment: Sustainability via Ownership." Advances in Classification Research Online 23, no. 1 (2013): 47. http://dx.doi.org/10.7152/acro.v23i1.14258.

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<p>Positive impacts associated with urban housing/home ownership programs motivate us to study this topic in relation to ontologies. This paper reviews ontological dependence and presents early work underway in the DataONE Preservation and Metadata Working Group (PAMWG) to collectively leverage existing metadata schemes and ontologies. The paper introduces a high-level set of functional requirements and the stackoverflow model that may be used detect highly rated metadata or ontological properties to from a loose cannon for describing scientific data. The long term goal is to establish c

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Anwar, Zeeshan, Hammad Afzal, Seifedine Kadry, and Xiaochun Cheng. "Semantic Web Approaches in Stack Overflow." International Journal on Semantic Web and Information Systems 20, no. 1 (2024): 1–61. http://dx.doi.org/10.4018/ijswis.358617.

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StackOverflow (SO), a prominent question-answering site for programming, has amassed a vast repository of user-generated content since its inception in 2008. This paper conducts a thorough analysis of research trends on SO, examining 170 publications from 2008 to 2019. Utilizing qualitative and quantitative methods, the study categorizes papers using literature review and Latent Dirichlet Allocation (LDA), identifying 62 topics grouped into 8 main categories. Additionally, it highlights tools developed by researchers using SO data sets, showcasing their practical applications. The analysis als

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Li, Peng, Yeye He, Cong Yan, Yue Wang, and Surajit Chaudhuri. "Auto-Tables: Relationalize Tables without Using Examples." ACM SIGMOD Record 53, no. 1 (2024): 76–85. http://dx.doi.org/10.1145/3665252.3665269.

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Relational tables, where each row corresponds to an entity and each column corresponds to an attribute, have been the standard for tables in relational databases. However, such a standard cannot be taken for granted when dealing with tables "in the wild". Our survey of real spreadsheettables and web-tables shows that over 30% of such tables do not conform to the relational standard, for which complex table-restructuring transformations are needed before these tables can be queried easily using SQL-based tools. Unfortunately, the required transformations are non-trivial to program, which has be

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Diyanati, Ahmad, Behrooz Shahi Sheykhahmadloo, Seyed Mostafa Fakhrahmad, Mohammad Hadi Sadredini, and Mohammad Hassan Diyanati. "A proposed approach to determining expertise level of StackOverflow programmers based on mining of user comments." Journal of Computer Languages 61 (December 2020): 101000. http://dx.doi.org/10.1016/j.cola.2020.101000.

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Joorabchi, Arash, Michael English, and Abdulhussain E. Mahdi. "Automatic mapping of user tags to Wikipedia concepts: The case of a Q&A website – StackOverflow." Journal of Information Science 41, no. 5 (2015): 570–83. http://dx.doi.org/10.1177/0165551515586669.

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Osadcha, Kateryna P., and Viacheslav V. Osadchyi. "The use of cloud computing technology in professional training of future programmers." CTE Workshop Proceedings 8 (March 19, 2021): 155–64. http://dx.doi.org/10.55056/cte.229.

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The article provides a brief analysis of the current state of the study of cloud technologies by future software engineers at foreign and Ukrainian universities. The author experience in the application of cloud technologies in the training of future software engineers in Ukraine is presented. The application of cloud business automation systems, online services to monitor the implementation of the software projects, Google services for collaboration, planning and productivity while studying professional disciplines and carrying out diploma projects is described. Based on the survey conducted

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Anneser, Christoph, Nesime Tatbul, David Cohen, et al. "AutoSteer: Learned Query Optimization for Any SQL Database." Proceedings of the VLDB Endowment 16, no. 12 (2023): 3515–27. http://dx.doi.org/10.14778/3611540.3611544.

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This paper presents AutoSteer, a learning-based solution that automatically drives query optimization in any SQL database that exposes tunable optimizer knobs. AutoSteer builds on the Bandit optimizer (Bao) and extends it with new capabilities (e.g., automated hint-set discovery) to minimize integration effort and facilitate usability in both monolithic and disaggregated SQL systems. We successfully applied AutoSteer on PostgreSQL, PrestoDB, Spark-SQL, MySQL, and DuckDB - five popular open-source database engines with diverse query optimizers. We then conducted a detailed experimental evaluati

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Dong, Yichen, Zhen Wang, and Tianjun Wu. "An open intent detection model optimized for datasets based on the Bert large model." Applied and Computational Engineering 47, no. 1 (2024): 225–31. http://dx.doi.org/10.54254/2755-2721/47/20241381.

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Within current task-oriented dialogue systems, the focus of intent detection predominantly centers on closed domains. Nevertheless, in real-world usage scenarios, a substantial proportion of interactions fall into the open-domain category. User intentions frequently transcend predefined boundaries, giving rise to a multitude of out-of-domain intents, which pose a formidable challenge to existing models, ultimately leading to diminished recognition rates and accuracy. The demand for open intent detection models is increasing in today's society to address this issue effectively. This paper propo

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Bozic, Bojan, Andre Rios, and Sarah Jane Delany. "Comparing tagging suggestion models on discrete corpora." International Journal of Web Information Systems 16, no. 2 (2020): 201–21. http://dx.doi.org/10.1108/ijwis-08-2019-0035.

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Purpose This paper aims to investigate the methods for the prediction of tags on a textual corpus that describes diverse data sets based on short messages; as an example, the authors demonstrate the usage of methods based on hotel staff inputs in a ticketing system as well as the publicly available StackOverflow corpus. The aim is to improve the tagging process and find the most suitable method for suggesting tags for a new text entry. Design/methodology/approach The paper consists of two parts: exploration of existing sample data, which includes statistical analysis and visualisation of the d

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Ilhami, Mirza. "Tren dan Peluang Cross-Platform Mobile App untuk Developer Pemula." KONSTELASI: Konvergensi Teknologi dan Sistem Informasi 1, no. 2 (2021): 402–11. http://dx.doi.org/10.24002/konstelasi.v1i2.4320.

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The development of cross-platform based mobile applications has grown rapidly in the last five years. From a developer's point of view, the many technologies that must be studied make them confused about which programming language to master because it will correlate with the time required and technology adoption by the industrial world. From an industry point of view, the challenge faced is determining the right framework or programming language and tools for their application. It also correlates with development time and costs, as well as finding the best talent with the technology. The purpo

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Mustafa, Sohaib, Wen Zhang, Muhammad Mateen Naveed, and Dur e. Adan. "Using social Cognitive theory to reengage dormant users in question and answer Communities: A case study of active StackOverflow participants." Electronic Commerce Research and Applications 68 (November 2024): 101450. http://dx.doi.org/10.1016/j.elerap.2024.101450.

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Ceh, Simon M., and Mathias Benedek. "Where to Share? A Systematic Investigation of Creative Behavior on Online Platforms." Creativity. Theories – Research - Applications 8, no. 1 (2021): 108–23. http://dx.doi.org/10.2478/ctra-2021-0008.

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Abstract Digitalization, underpinned by the ongoing pandemic, has transferred many of our everyday activities to online places. In this study, we wanted to find out what online outlets people use to share their creative work and why they do it. We found that most people posted creative work online at least a few times per year. They especially shared creative content related to creative cooking, visual art, and literature but hardly related to performing art. YouTube, Facebook, and Instagram were the three platforms with the highest familiarity and usage rates; among these, YouTube was most st

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Tang, Mingjing, Tong Li, Wei Wang, Rui Zhu, Zifei Ma, and Yahui Tang. "Software Knowledge Entity Relation Extraction with Entity-Aware and Syntactic Dependency Structure Information." Scientific Programming 2021 (December 22, 2021): 1–13. http://dx.doi.org/10.1155/2021/7466114.

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Software knowledge community contains a large scale of software knowledge entities with complex structure and rich semantic relations. Semantic relation extraction of software knowledge entities is a critical task for software knowledge graph construction, which has an important impact on knowledge graph based tasks such as software document generation and software expert recommendation. Due to the problems of entity sparsity, relation ambiguity, and the lack of annotated dataset in user-generated content of software knowledge community, it is difficult to apply existing methods of relation ex

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Li, Peng, Yeye He, Cong Yan, Yue Wang, and Surajit Chaudhuri. "Auto-Tables: Synthesizing Multi-Step Transformations to Relationalize Tables without Using Examples." Proceedings of the VLDB Endowment 16, no. 11 (2023): 3391–403. http://dx.doi.org/10.14778/3611479.3611534.

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Relational tables, where each row corresponds to an entity and each column corresponds to an attribute, have been the standard for tables in relational databases. However, such a standard cannot be taken for granted when dealing with tables "in the wild". Our survey of real spreadsheet-tables and web-tables shows that over 30% of such tables do not conform to the relational standard, for which complex table-restructuring transformations are needed before these tables can be queried easily using SQL-based tools. Unfortunately, the required transformations are non-trivial to program, which has b

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Ahmed, Majid Hameed, Sabrina Tiun, Nazlia Omar, and Nor Samsiah Sani. "A multi-view representation technique based on principal component analysis for enhanced short text clustering." PLOS ONE 19, no. 8 (2024): e0309206. http://dx.doi.org/10.1371/journal.pone.0309206.

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Clustering texts together is an essential task in data mining and information retrieval, whose aim is to group unlabeled texts into meaningful clusters that facilitate extracting and understanding useful information from large volumes of textual data. However, clustering short texts (STC) is complex because they typically contain sparse, ambiguous, noisy, and lacking information. One of the challenges for STC is finding a proper representation for short text documents to generate cohesive clusters. However, typically, STC considers only a single-view representation to do clustering. The single

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Liao, Zhifang, Ningwei Wang, Shengzong Liu, Yan Zhang, Hui Liu, and Qi Zhang. "Identification-Method Research for Open-Source Software Ecosystems." Symmetry 11, no. 2 (2019): 182. http://dx.doi.org/10.3390/sym11020182.

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In recent years, open-source software (OSS) development has grown, with many developers around the world working on different OSS projects. A variety of open-source software ecosystems have emerged, for instance, GitHub, StackOverflow, and SourceForge. One of the most typical social-programming and code-hosting sites, GitHub, has amassed numerous open-source-software projects and developers in the same virtual collaboration platform. Since GitHub itself is a large open-source community, it hosts a collection of software projects that are developed together and coevolve. The great challenge her

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Mohamad Johari, Mohd Ainal Farhan, and Adila Firdaus Arbain. "Transforming Workplace Efficiency: Using Agile Development Methodologies for Developing Meeting Management System." International Journal of Innovative Computing 14, no. 2 (2024): 117–27. http://dx.doi.org/10.11113/ijic.v14n2.505.

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This In today's digital era, individuals are seamlessly connected across various digital platforms, from social media giants like Facebook, Twitter, and Instagram to knowledge-sharing hubs like StackOverflow and Quora. The relentless advancement of digital technologies has ushered in a wave of unprecedented accessibility and connectivity. While this transformation has brought tremendous benefits to society, organizations face new and intricate challenges in adapting to evolving task preferences, performance expectations, and operational requirements. In response to this dynamic landscape, this

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Kumar, Akshi, and Saurabh Raj Sangwan. "Expert Finding in Community Question-Answering for Post Recommendation." International Journal of Engineering & Technology 7, no. 3.4 (2018): 151. http://dx.doi.org/10.14419/ijet.v7i3.4.16764.

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Community question answering system is a perfect example of platform where people participate to seek expertise on their topic of interest. But information overload, finding the expertise level of users and trustworthy answers remain key challenges within these communities. Moreover, people do not look for personal advices but expert views on such platforms therefore; expert finding is an integral part of these communities. In order to trust someone's opinion who is not known in person by the users of the community, it is necessary to find the credibility of such person. By determining experti

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R., Jayashree, and Christy A. "Enhanced User-driven Ranking System with Splay Tree." TELKOMNIKA Telecommunication, Computing, Electronics and Control 16, no. 1 (2018): 432–44. https://doi.org/10.12928/TELKOMNIKA.v16i1.5875.

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E-learning is one of the information and communication technology products used for teaching and learning process [35]. An efficient and effective way to construct trust relationship among peer users in e-learning environment is ranking. User-driven ranking systems are based only on the feedback or rating provided by the users. In [46-48] the authors provide a variety of trust and reputation methods. Certified Belief in Strength (CBS) [45] is a novel trust measurement method based on reputation and strength . In [38] author presents a recommendation system based on the relevant feedback review

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Christoforaki, Maria, and Panagiotis Ipeirotis. "STEP: A Scalable Testing and Evaluation Platform." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 2 (September 5, 2014): 41–49. http://dx.doi.org/10.1609/hcomp.v2i1.13159.

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The emergence of online crowdsourcing sites, online work platforms, and evenMassive Open Online Courses (MOOCs), has created an increasing need for reliably evaluating the skills of the participating users in a scalable way.Many platforms already allow users to take online tests and verify their skills, but the existing approaches face many problems. First of all, cheating is very common in online testing without supervision, as the test questions often "leak" and become easily available online together with the answers.Second, technical skills, such as programming, require the tests to be fre

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Hu, Jiawei, and Bo Yang. "Posts Quality Prediction for StackOverflow Website." IEEE Access, 2024, 1. http://dx.doi.org/10.1109/access.2024.3440879.

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Saraj, Singh Manes, and Baysal Olga. "How Often and What StackOverflow Posts Do Developers Reference in Their GitHub Projects?" MSR 2019, March 22, 2019. https://doi.org/10.5281/zenodo.2604130.

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Yang, Yi, Ying Li, Kai Chen, and Jinghua Liu. "Jeu de mots paronomasia: a StackOverflow-driven bug discovery approach." Cybersecurity 6, no. 1 (2023). http://dx.doi.org/10.1186/s42400-023-00153-0.

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AbstractLocating bug code snippets (short for BugCode) has been a complex problem throughout the history of software security, mainly because the constraints that define BugCode are obscure and hard to summarize. Previously, security analysts attempted to define such constraints manually (e.g., limiting buffer size to detect overflow), but were limited to the types of BugCode. Recent researchers address this problem by extracting constraints from program documentation, which shows the potential for API misuse. But for bugs beyond the scope of API misuse, such an approach becomes less effective

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GENÇ, Adile, Ayça YURTSEVEN, Hacer ÖZYURT, and Özcan ÖZYURT. "STACKOVERFLOW'DA "BIG DATA" İLE İLGİLİ GÖNDERİLERİN KONU MODELLEME VE BİRLİKTELİK ANALİZİ İLE ÖZELLİKLERİNİN ÇIKARILMASI." Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi, December 19, 2023. http://dx.doi.org/10.31796/ogummf.1375611.

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Günümüz teknolojisinde internet kullanımının artması ile birlikte "Büyük Veri" kavramının ortaya çıkması kaçınılmaz olmuştur. 23 milyondan fazla soru ve 35 milyona yakın cevap barındırarak büyük veriye katkı sağlayan StackOverflow'da paylaşılan bilgilerin analizi güncel konu ve eğilimlerin belirlenmesi konusunda önemli çıkarımlar sunabilmektedir. StackOverflow'daki bu büyük ve dağınık veri kümesi üzerinde tartışmaların elle analiz edilmesi mümkün olmadığı için otomatik analiz yapabilecek yöntemlere ihtiyaç duyulmaktadır. Bu ihtiyacı gidermek için konu modelleme yaklaşımlarına başvurulmuştur. K

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Bodke, Sneha, Ashwini Meher, and Kavita Shirsat. "Evaluating Answer Qualities on Q&A Community Sites (StackOverFlow)." SSRN Electronic Journal, 2019. http://dx.doi.org/10.2139/ssrn.3367706.

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GÜRCAN, Fatih, and Özcan ÖZYURT. "Stackoverflow gönderilerinde tartışılan trend konuların kelime frekans analizi ile belirlenmesi." Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi, February 9, 2021. http://dx.doi.org/10.17714/gumusfenbil.811123.

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Amin, Ghadesi, Li Heng, and Lamothe Maxime. "What Causes Exceptions in Machine Learning Applications? Mining Machine Learning-Related Stack Traces on Stack Overflow." April 17, 2023. https://doi.org/10.5281/zenodo.7839032.

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Tseng, Chun-Hsiung, and Jia-Rou Lin. "A semi-hierarchical clustering method for constructing knowledge trees from stackoverflow." Journal of Information Science, September 21, 2020, 016555152096103. http://dx.doi.org/10.1177/0165551520961035.

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To help students learn how to programme, we have to give them a clear knowledge map and sufficient materials. Question-based websites, such as stackoverflow, are excellent information sources for this goal. However, for beginners, the process can be a little tricky since they may not know how to ask correct questions if they do not have sufficient background knowledge, and a knowledge tree is usually considered more helpful in such a scenario. In this research, a method to infer a knowledge tree automatically from the type of websites and to group documents based on the resulting knowledge tre

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Anwar, Zeeshan, Hammad Afzal, Ali Ahsan, Naima Iltaf, and Ayesha Maqbool. "A novel hybrid CNN-LSTM approach for assessing StackOverflow post quality." Journal of Intelligent Systems 32, no. 1 (2023). http://dx.doi.org/10.1515/jisys-2023-0057.

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Abstract Maintaining the content quality on social media Q&A platforms is pivotal for user attraction and retention. Automating post quality assessment offers benefits such as reduced moderator workload, amplified community impact, enhanced expert user recognition, and importance to expert feedback. While existing approaches for post quality mainly employ binary classification, they often lack optimal feature selection. Our research introduces an automated system that categorizes features into textual, readability, format, and community dimensions. This system integrates 20 features belong

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Firouzi, Ehsan, and Mohammad Ghafari. "Time to separate from StackOverflow and match with ChatGPT for encryption." Journal of Systems and Software, June 2024, 112135. http://dx.doi.org/10.1016/j.jss.2024.112135.

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Michael Ayas, Hamdy, Philipp Leitner, and Regina Hebig. "An empirical study of the systemic and technical migration towards microservices." Empirical Software Engineering 28, no. 4 (2023). http://dx.doi.org/10.1007/s10664-023-10308-9.

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Abstract Context As many organizations modernize their software architecture and transition to the cloud, migrations towards microservices become more popular. Even though such migrations help to achieve organizational agility and effectiveness in software development, they are also highly complex, long-running, and multi-faceted. Objective In this study we aim to comprehensively map the journey towards microservices and describe in detail what such a migration entails. In particular, we aim to discuss not only the technical migration, but also the long-term journey of change, on a systemic le

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"IMPACT OF USERS' MOTIVATION ON GAMIFIED CROWDSOURCING SYSTEMS: A CASE OF STACKOVERFLOW." Issues In Information Systems, 2018. http://dx.doi.org/10.48009/2_iis_2018_33-40.

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Mustafa, Sohaib, Wen Zhang, and Muhammad Mateen Naveed. "What motivates online community contributors to contribute consistently? A case study on Stackoverflow netizens." Current Psychology, June 25, 2022. http://dx.doi.org/10.1007/s12144-022-03307-4.

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van der Linden, Dirk, Emma Williams, Joseph Hallett, and Awais Rashid. "The impact of surface features on choice of (in)secure answers by Stackoverflow readers." IEEE Transactions on Software Engineering, 2020, 1. http://dx.doi.org/10.1109/tse.2020.2981317.

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Ahmed, Tanveer, and Abhishek Srivastava. "Understanding and evaluating the behavior of technical users. A study of developer interaction at StackOverflow." Human-centric Computing and Information Sciences 7, no. 1 (2017). http://dx.doi.org/10.1186/s13673-017-0091-8.

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Soto de la Cruz, Ramon, Felix Agustín Castro-Espinoza, and Liz Soto. "Isodata-Based Method for Clustering Surveys Responses with Mixed Data: The 2021 StackOverflow Developer Survey." Computación y Sistemas 27, no. 1 (2023). http://dx.doi.org/10.13053/cys-27-1-4539.

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Falci, Samuel Henrique, Fabiano Azevedo Dorça, Alessandro Vivas Andrade, and Daniel Henrique Mourão Falci. "A low complexity heuristic to solve a learning objects recommendation problem." Smart Learning Environments 7, no. 1 (2020). http://dx.doi.org/10.1186/s40561-020-00133-8.

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Abstract The recommendation of learning objects in virtual learning environments has become the focus of research to improve online learning experience. Several approaches have been presented in an attempt to model the individual characteristics of the students and offer learning objects that best suit their particularities. Most of them, though, are impractical in real-world scenarios due to the high computational cost as a huge number of repositories offering learning objects such as Youtube, Wikipedia, Stackoverflow, Github, discussion forums, social networks and many others are available a

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Mustafa, Sohaib, Wen Zhang, and Muhammad Mateen Naveed. "How to mend the dormant user in Q&A communities? A social cognitive theory-based study of consistent geeks of StackOverflow." Behaviour & Information Technology, July 31, 2023, 1–20. http://dx.doi.org/10.1080/0144929x.2023.2237604.

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Mak, Yen-Wei, Hui-Ngo Goh, and Amy Hui-Lan Lim. "Forum Text Processing and Summarization." JOIV : International Journal on Informatics Visualization 8, no. 1 (2024). http://dx.doi.org/10.62527/joiv.8.1.2279.

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Frequently Asked Questions (FAQs) are extensively studied in general domains like the medical field, but such frameworks are lacking in domains such as software engineering and open-source communities. This research aims to bridge this gap by establishing the foundations of an automated FAQ Generation and Retrieval framework specifically tailored to the software engineering domain. The framework involves analyzing, ranking, performing sentiment analysis, and summarization techniques on open forums like StackOverflow and GitHub issues. A corpus of Stack Overflow post data is collected to evalua

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