Rocks Coding, Not Development--A Human-Centric, Experimental Evaluation of LLM-Supported SE Tasks

Recently, large language models (LLM) based generative AI has been gaining momentum for their impressive high-quality performances in multiple domains, particularly after the release of the ChatGPT. Many believe that they have the potential to perform general-purpose problem-solving in software development and replace human software developers. Nevertheless, there are in a lack of serious investigation into the capability of these LLM techniques in fulfilling software development tasks. In a controlled 2 x 2 between-subject experiment with 109 participants, we examined whether and to what degree working with ChatGPT was helpful in the coding task and typical software development task and how people work with ChatGPT. We found that while ChatGPT performed well in solving simple coding problems, its performance in supporting typical software development tasks was not that good. We also observed the interactions between participants and ChatGPT and found the relations between the interactions and the outcomes. Our study thus provides first-hand insights into using ChatGPT to fulfill software engineering tasks with real-world developers and motivates the need for novel interaction mechanisms that help developers effectively work with large language models to achieve desired outcomes.Comment: The paper has been accepted by FS

From Monolithic to Microservice Architecture: The Case of Extensible and Domain-Specific IDEs

International audienceIntegrated Development Environments (IDEs) are evolving towards cloud-native applications with the aim to relocate the language services provided by an IDE on distant servers. Existing research works focus on the overall migration process to handle more efficiently their specific requirements. However, the microservicization of legacy monolithic applications is still highly dependent on the specific properties of the application of interest. In this paper, we report our experiment on the microservicization process of the Cloud-Based graphical modeling workbench Sirius Web. We aim to identify the technical challenges related to applications with similar properties, and provide insights for practitioners to migrate their similar applications towards microservices. We discuss the main lessons learned and identify the underlying challenges to be further addressed by the community

IDE baseado em Eclipse para CxProlog

O CxProlog é uma implementação da linguagem Prolog suportando várias extensões e desenvolvida no NOVA LINCS do Departamento de Informática, FCT, Universidade Nova de Lisboa sendo o seu criador o Professor A.Miguel Dias. O projeto desta dissertação consiste na conceção e implementação dum IDE baseado em Eclipse para o CxProlog. O IDE destina-se a suportar a escrita, teste e execução de programas CxProlog. Deverá disponibilizar as funcionalidades mais características dos IDEs atuais (realce de sintaxe, completação automática, etc.), assim como outras funcionalidades que sejam relevantes para um programador de CxProlog (ex: injeção de golos na consola). Uma das maiores ambições do projeto é que o IDE seja configurável e parcialmente definido utilizando a própria linguagem CxProlog. Tal ambição requer a utilização de mecanismos de interoperabilidade entre CxProlog e Java (a linguagem que implementa o Eclipse). Os maiores desafios do projeto são o domínio da plataforma Eclipse, principalmente os seus mecanismos para desenvolvimento de plugins, a interoperabilidade entre CxProlog e Java/Eclipse, e a implementação das funcionalidades mais sofisticadas. O documento apresentado engloba: planeamento, implementação e utilização prática do projeto. Para além disso o utilizador também terá acesso ao estudo realizado sobre o estado de arte dos IDEs e à avaliação do sistema