This paper presents the results of a survey on the experience of emotions in the work of software developers. Quantitative analysis revealed information about emotions affecting programmers, their frequency and impact on their performance. The concept of emotional risk to productivity was also presented. It allows to choose the emotional states, which should be avoided. Furthermore, all collected data were analyzed with information about the experience of developers. In addition to most hazardous emotions, those with the most positive impact on productivity were selected.

In this paper a novel application of multimodal emotion recognition algorithms in software engineering is described. Several application scenarios are proposed concerning program usability testing and software process improvement. Also a set of emotional states relevant in that application area is identified. The multimodal emotion recognition method that integrates video and depth channels, physiological signals and input devices usage patterns is proposed and some preliminary results on learning set creation are described.

Research conducted in recent years has shown that emotions and moods can have a serious impact on the work of software development teams [1]. To shed new light on the issues affecting the working atmosphere, we conducted a study to examine perceptions whether and how gender diversity impacts on the mood and atmosphere, and thus on the comfort of IT teams.

Software product management, which involves multiple processes and responsibilities and links to many activities within the organisation, increases the success rate of IT projects. However, the adoption of product management activities and the implementation of the software product manager role itself varies between companies. This research explores the topic of software product managers’ strategies for dealing with challenges in their work. The aim of the study is to identify and evaluate solutions to the main problems that affect the software product management process and to provide guidelines for dealing with them. For this purpose, a focus group method was adopted and 47 software product managers participated in 15 focus groups. This was followed by a survey to assess the comprehensibility and effectiveness of the solutions identified. The paper proposes a list of 39 solutions to the 5 most common problems in the work of product managers. Furthermore, based on the identified solutions and the results of discussions with experienced professionals during the focus groups, guidelines for these problems were also developed. These guidelines can be used by product managers as well as other roles working in the product development team to create their own strategies for overcoming software product management challenges and improving software engineering practices. Finally, the solutions and guidelines presented, when combined with a list of problems identified in previous research, will form a Software Product Management Guide – a framework currently under construction, as part of wider research, for product development teams to improve software engineering practices.

The paper concerns accuracy of emotion recognition from facial expressions. As there are a couple of ready off-the-shelf solutions available in the market today, this study aims at practical evaluation of selected solutions in order to provide some insight into what potential buyers might expect. Two solutions were compared: FaceReader by Noldus and Xpress Engine by QuantumLab. The performed evaluation revealed that the recognition accuracies differ for photo and video input data and therefore solutions should be matched to the specificity of the application domain.