An increased understanding of how developers' approach the development of software and what individual challenges they face, has a substantial potential to better support the process of programming. In this paper, we adapt Rabbit Eclipse, an existing Eclipse plugin, to generate event logs from IDE usage enabling process mining of developers' workflows. Moreover, we describe the results of an exploratory study in which the event logs of 6 developers using Eclipse together with Rabbit Eclipse were analyzed using process mining. Our results demonstrate the potential of process mining to better understand how developers' approach a given programming task.

Understanding how developers interact with different software artifacts when performing comprehension tasks has a potential to improve developers' productivity. In this paper, we propose a method to analyze eye-tracking data using process mining to find distinct reading patterns of how developers interacted with the different artifacts. To validate our approach, we conducted an exploratory study using eyetracking involving 11 participants. We applied our method to investigate how developers interact with different artifacts during domain and code understanding tasks. To contextualize the reading patterns and to better understand the perceived benefits and challenges participants associated with the different artifacts and their choice of reading patterns, we complemented the eye-tracking data with the data obtained from think aloud. The study used behavior driven development (BDD), a development practice that is increasingly used in Agile software development contexts, as a setting. The study shows that our method can be used to explore developers' behavior at an aggregated level and identify behavioral patterns at varying levels of granularity.

Global warming affects human beings and nature’s ecosystems. Apart from the observed, monitored and measured negative effects on human health and biodiversity, the application of the Laws of Thermodynamics proves that thermal engines can also be affected by having their thermal efficiency reduced due to the decreased value of ΔT (temperature difference between the two heat reservoirs). Considering that the global outcome is kept constant (same power demand and supply), a continuously decreased efficiency results in increased fuel consumption and thus higher CO2 emissions. Since CO2 as GHG favours global warming, a vicious circle is generated. Even though a slight decrease in thermal efficiency seems to be marginal and, thus, ignorable, the vast use of thermal engines in industrial power production and in transportation and the corresponding fossil fuels consumption results in a significant increase in CO2 emissions. The current study examines thermal engines (both for transportation and power generation on board the vessels) and estimates their GHG emissions. The present work, being part of an ongoing vast study on decarbonization, deals with the Carnot and Diesel thermal cycles. Examination of Otto, Dual Combustion, Joule/Brayton, and Rankine cycles will follow. The scenarios are examined to support decisions regarding actions that must be taken to start considering available complementary solutions which provide different levels of technological maturity, cost-effectiveness, and applicability.

Recent eye tracking research in the field of software engineering has proposed novel visualizations linking developer's gazes with the source code artifacts to better understand how developers comprehend source code artifacts potentially consisting of several different files. In addition, it is well established that cognitive processes can be monitored by recording the change in pupil dilation. Recent pupillometry studies in the software engineering field have shown that pupil dilation can be used either as an indicator of cognitive load or task difficulty. We envision to create a tool for visualizing pupil dilation linked to source code artifacts that can help to better understand the cognitive processes of a developer during code comprehension tasks in terms of cognitive load. In this paper, we describe a feasibility study we conducted to enable a more fine-grained analysis of pupil dilation and we demonstrate some preliminary results.

The alarming rate of climate change accentuates the need to reduce greenhouse gas (GHG) emissions produced from anthropogenic activities and consequently the consumption of fossil fuels. The transportation sector is one of the most energy-demanding activities, consisting around 27% of the global primary energy demand and one of the major contributors of GHG emissions to the atmosphere, while shipping transportation accounts for nearly 12% of its CO2 emissions. Decarbonization is vital for emission mitigation using innovative technologies, policies, and incentives at a local and international level. In this context, the presented Integrated Ship Energy Flowchart (ISEF), aims to create a digital twin of a ship and carry out deterministic calculations, such as engine power requirements and by extension fuel consumption and emissions, by modelling the various components of a ship’s energy flow. Most modeling approaches depend on tracking data from automatic identification systems (AIS) and commercial vessel databases, accompanied with prohibitive costs for many, as well as missing vessel characteristics. ISEF, on the other hand, aims to fill in the gap in case of missing or costly to obtain data while maintaining the flexibility to utilize field data if available. This is done by providing representative vessel characteristics, detailed engine modeling and simulating components such as environmental conditions (sea-state, wind). At the same time, ISEF develops a library of vessel data including ship particulars, engine and route information among others. Thus, it is also suitable for the validation of tracking information and machine learning or other deterministic algorithms. Additionally, this library will enable the development of a statistically representative ship describing the international fleet. This will therefore improve projection algorithms utilized in calculations and aid the evaluation of mitigation options regarding decarbonisation in terms of the overall fleet. Such a model also enables the investigation of alternative fuels and fuel mixtures, route optimization, and inclusion of cold ironing amongst others. The current objectives include the validation of the core modelling implementation via comparisons with available raw data to serve as a reference case and build the necessary libraries. Therefore, a case study of a specific ship utilizing real navigational data will be used to demonstrate the capabilities of the algorithm.