Analysis of Development Tool Usage in Software Engineering Classes

In this paper, the survey, dedicated to the usage of software systems in a software development process, is analysed. The survey was conducted among the students of Innopolis University. Based on the result of the survey, the following conclusions were made: (1) Windows, macOS and Linux-based operating systems have almost equal share of usage among future software developers (2) the most popular IDE is IntelliJ IDEA, however, to the end of the studying process students the diversity of IDEs usage increases (3) the mostly used code management system by far is Github, with almost 100% share (4) Trello and Jira are the most popular project management software for lightweight and complex industrial projects respectively. The obtained results will be used for the prioritization of the development of integration agents for InnoMetrics project, as well as for the adaptation of a studying process in academic institutions to make it more relevant to the given trends and for the market analysis of software engineering environment

Measurements for Energy Efficient, Adaptable, Mobile Systems - A Research Agenda

Software systems are the enabling technology for the devel- opment of sustainable systems. However, such devices consume power both from the client side and from the server side. This scenario poses to software engineering a new challenge that concerns the development of software for sustainable systems i.e. systems that explicitly charac- terize the resources under control, that dynamically evolve to maintain an acceptable consumption of resources making the best possible trade- off with user needs and that are opportunistic and proactive in taking actions that can optimize future resource consumption based on context and past experiences. This paper outlines a research agenda in this area

AIDOaRt: AI-augmented Automation for DevOps, a model-based framework for continuous development in Cyber-Physical Systems

The advent of complex Cyber-Physical Systems (CPSs) creates the need for more efficient engineering processes. Recently, DevOps promoted the idea of considering a closer continuous integration between system development (including its design) and operational deployment. Despite their use being still currently limited, Artificial Intelligence (AI) techniques are suitable candidates for improving such system engineering activities (cf. AIOps). In this context, AIDOaRT is a large European collaborative project that aims at providing AI-augmented automation capabilities to better support the modeling, coding, testing, monitoring, and continuous development of CPSs. The project proposes to combine Model Driven Engineering principles and techniques with AI-enhanced methods and tools for engineering more trustable CPSs. The resulting framework will (1) enable the dynamic observation and analysis of system data collected at both runtime and design time and (2) provide dedicated AI-augmented solutions that will then be validated in concrete industrial cases. This paper describes the main research objectives and underlying paradigms of the AIDOaRt project. It also introduces the conceptual architecture and proposed approach of the AIDOaRt overall solution. Finally, it reports on the actual project practices and discusses the current results and future plans

The Development of Data Collectors in Open-Source System for Energy Efficiency Assessment

The paper is devoted to the development of the data col- lectors for Windows OS and MacOS. The purpose of these plugins is to collect the process metrics from the user’s device and send it to the back- end for further processing. The overall open source framework is aimed at energy efficiency analysis of the developing software products. The development presented here as a sequence of the life cycle stages, includ- ing requirements analysis, design, implementation and testing. Specifics of the implementation for each targeted operating system are give