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Software development is a cognitively intensive process requiring multitasking, adherence to evolving workflows, and continuous learning. With the rise of large language model (LLM)-based tools, such as conversational agents (CAs), there is…
Due to the substantial number of enrollments in programming courses, a key challenge is delivering personalized feedback to students. The nature of this feedback varies significantly, contingent on the subject and the chosen evaluation…
Developing IoT, Data Computing and Cloud Computing software requires different programming skills and different programming languages. This cause a problem for many companies and researchers that need to hires many programmers to develop a…
The ever-increasing complexity of modern software engineering projects makes the usage of automated assistants imperative. Bots can be used to complete repetitive tasks during development and testing, as well as promoting communication…
The linked open data (LOD) paradigm has emerged as a promising approach to structuring and sharing geospatial information. One of the major obstacles to this vision lies in the difficulties found in the automatic integration between…
Design of dialogue systems has witnessed many advances lately, yet acquiring huge set of data remains an hindrance to their fast development for a new task or language. Besides, training interactive systems with batch data is not…
Popular and large contemporary open-source projects now embrace a diverse set of documentation for communication channels. Examples include contribution guidelines (i.e., commit message guidelines, coding rules, submission guidelines), code…
The choice of programming language is a very important decision as it not only affects the performance and maintainability of the software but also dictates the talent pool and community support available. To better understand the…
NLP models today strive for supporting multiple languages and modalities, improving accessibility for diverse users. In this paper, we evaluate their multilingual, multimodal capabilities by testing on a visual reasoning task. We observe…
Conversational large-language models are extensively used for issue resolution tasks. However, not all developer-LLM conversations are useful for effective issue resolution. In this paper, we analyze 686 developer-ChatGPT conversations…
Sentiments of words differ from one corpus to another. Inducing general sentiment lexicons for languages and using them cannot, in general, produce meaningful results for different domains. In this paper, we combine contextual and…
Detecting the presence of bots in distributed software development activity is very important in order to prevent bias in large-scale socio-technical empirical analyses. In previous work, we proposed a classification model to detect bots in…
Web applications development involves managing a high diversity of files and resources like code, pages or style sheets, implemented in different languages. To deal with the automatic generation of custom-made configurations of web…
Management of security policies has become increasingly difficult given the number of domains to manage, taken into consideration their extent and their complexity. Security experts has to deal with a variety of frameworks and specification…
With over 28 million developers, success of the GitHub collaborative platform is highlighted through an abundance of communication channels among contemporary software projects. Knowledge is broken into two forms and its sharing (through…
With the advances in machine learning, there is a growing interest in AI-enabled tools for autocompleting source code. GitHub Copilot has been trained on billions of lines of open source GitHub code, and is one of such tools that has been…
Emotions play a significant role in teamwork and collaborative activities like software development. While researchers have analyzed developer emotions in various software artifacts (e.g., issues, pull requests), few studies have focused on…
The process of engineering and deploying applications in the edge/embedded space is massively complicated by the non-homogeneous nature of the software stack and the complexity of diagnostics & debugging. Often different languages and…
This paper illustrates an empirical study of the working efficiency of machine learning techniques in classifying code review text by semantic meaning. The code review comments from the source control repository in GitHub were extracted for…
Software is foundationally important to scientific and social progress, however, traditional acknowledgment of the use of others' work has not adapted in step with the rapid development and use of software in research. This report outlines…