The purpose of requirements engineering (RE) is to make sure that the expectations and needs of the stakeholders of a software system are met. Emotional needs can be captured as emotional requirements that represent how the end user should feel when using the system. Differently from functional and quality (non-functional) requirements, emotional requirements have received relatively less attention from the RE community. This study is motivated by the need to explore and map the literature on emotional requirements. The study applies the systematic mapping study technique for surveying and analyzing the available literature to identify the most relevant publications on emotional requirements. We identified 34 publications that address a wide spectrum of practices concerned with engineering emotional requirements. The identified publications were analyzed with respect to the application domains, instruments used for eliciting and artefacts used for representing emotional requirements, and the state of the practice in emotion-related requirements engineering. This analysis serves to identify research gaps and research directions in engineering emotional requirements. To the best of the knowledge by the authors, no other similar study has been conducted on emotional requirements.

Due to high demand, many cloud data centers have been developed across the world, consuming a large amount of energy. Making cloud datacenters energy efficient has become essential. Energy consumption of data centers can be minimized by designing energy-efficient hardware, software, and infrastructure. In this paper, we aim at giving an overview of software techniques, affected stakeholders, performance features, datasets, and tools used to make cloud data centers energy-efficient. To achieve this goal, we conducted a systematic mapping study using five online databases. After applying inclusion/exclusion and quality criteria, we selected 58 publications for further analysis. Our results indicate that all publications are solution and validation type of publications. We did not find publications containing evaluations in industry. We found that workload scheduling is the most frequently proposed technique used to improve cloud datacenters' energy efficiency. We found that not considering violations of service level agreements mostly affects end-users of cloud data centers. When analyzing how suggested solutions are validated, we identified the need to develop a standardized set of performance measures to benchmark software techniques proposed to make cloud data centers greener.

Energy consumption of mobile apps is receiving a lot of attention from researchers. Recent studies indicate that energy consumption of mobile devices could be lowered by improving the quality of mobile apps. Frequent refactoring is one way of achieving this goal. We explore the performance and energy impact of several common code refactorings in Android apps. Experimental results indicate that some code smell refactorings positively impact the energy consumption of Android apps. Refactoring of the code smells 'Duplicated code' and 'Type checking' reduce energy consumption by up to 10.8%. Significant reduction in energy consumption, however, does not seem to be directly related to the increase or decrease of execution time. In addition, the energy impact over permutations of code smell refactorings in the selected Android apps was small. When analyzing the order in which refactorings were made across code smell types, it turned out that some permutations resulted in a reduction and some in an increase of energy consumption for the analyzed apps.

Sustainability in software engineering is a relatively new and fast growing field of research. Green software engineering aims to produce sustainable software products with minimum negative impact on the environment. In order to make greener software products, software practitioners need actionable timely information, to make useful trade-offs between energy efficiency and other quality attributes, like performance, during development. Software analytics could be used to provide this support, as it combines information from different software artifacts and converts it into useful information. The objective of this paper is to provide an overview of the sub-domains, contribution types, research types, research methods, future research potentials and the role of software analytics in the field of green software engineering in 2015-16. We applied the systematic mapping method and conducted a search for studies in six online databases. Screening of papers was done according to inclusion/exclusion criteria and 50 selected studies were classified after analysis and data extraction. We found that there are many validation studies but hardly any evaluation and experience papers in the domain of green software engineering. Only 11 out of 50 papers in the green software engineering domain used software analytics techniques to foster green software engineering. Our results indicate the need to develop new/improved automated software analytics tools for software practitioners along with metrics explaining the correlation between energy usage and other quality attributes.