Sweden is seen as one of the most research-driven and educated countries in the world. Thus, Doctoral education is considered one of Sweden's most important parts of higher education. This position paper reflects upon the process and product of doctoral education in Computer Science and Software Engineering in Sweden. The paper provides an overview of doctoral education in Sweden, followed by a practical demonstration of how supervisors and doctoral students could use constructive alignment to achieve the learning outcomes of doctoral education using learning activities and assessment methods to evaluate the learning activities and, by extension, the learning outcomes.

Sverige ses som ett av de mest forskningsdrivna och utbildade länderna i världen. Forskarutbildningen anses därmed vara en av Sveriges viktigaste delar av den högre utbildningen. Detta ställningstagande reflekterar över forskarutbildningens process och produkt i Datavetenskap och programvarusystem i Sverige. Artikeln ger en översikt över forskarutbildningen i Sverige, följt av en praktisk demonstration av hur handledare och doktorander kan använda konstruktiv anpassning för att uppnå lärandemålen för forskarutbildningen med hjälp av inlärningsaktiviteter och bedömningsmetoder för att utvärdera lärandeaktiviteterna och i förlängningen lärandemålen. 

The development of autonomous vehicles has prompted an interest in exploring various techniques in navigation. One such technique is simultaneous localization and mapping (SLAM), which enables a vehicle to comprehend its surroundings, build a map of the environment in real time, and locate itself within that map. Although traditional techniques have been used to perform SLAM for a long time, recent advancements have seen the incorporation of neural network techniques into various stages of the SLAM pipeline. This review article provides a focused analysis of the recent developments in neural network techniques for SLAM-based localization of autonomous ground vehicles. In contrast to the previous review studies that covered general navigation and SLAM techniques, this paper specifically addresses the unique challenges and opportunities presented by the integration of neural networks in this context. Existing review studies have highlighted the limitations of conventional visual SLAM, and this article aims to explore the potential of deep learning methods. This article discusses the functions required for localization, and several neural network-based techniques proposed by researchers to carry out such functions. First, it presents a general background of the issue, the relevant review studies that have already been done, and the adopted methodology in this review. Then, it provides a thorough review of the findings regarding localization and odometry. Finally, it presents our analysis of the findings, open research questions in the field, and a conclusion. A semisystematic approach is used to carry out the review.

The use of artificial intelligence and machine learning techniques across all disciplines has exploded in the past few years, with the ever-growing size of data and the changing needs of higher education, such as digital education. Similarly, online educational information systems have a huge amount of data related to students in digital education. This educational data can be used with artificial intelligence and machine learning techniques to improve digital education. This study makes two main contributions. First, the study follows a repeatable and objective process of exploring the literature. Second, the study outlines and explains the literature's themes related to the use of AI-based algorithms in digital education. The study findings present six themes related to the use of machines in digital education. The synthesized evidence in this study suggests that machine learning and deep learning algorithms are used in several themes of digital learning. These themes include using intelligent tutors, dropout predictions, performance predictions, adaptive and predictive learning and learning styles, analytics and group-based learning, and automation. artificial neural network and support vector machine algorithms appear to be utilized among all the identified themes, followed by random forest, decision tree, naive Bayes, and logistic regression algorithms.

The purpose of this chapter is to identify and classify proposed business model innovation tools through a literature review of academic publications. We classified the tools into three categories: innovation process stage, strategic objective and size of firm. Our main findings are that the overall number of business model innovation (BMI) tools described in the research literature is limited mostly to facilitate design processes rather than for test or implementation purposes. Moreover, the identified tools are based on conceptual reasoning and not on empirical studies of tools used by managers. Implications for managers are that most BMI tools are intended for, and have their strength in, experimenting with the design or redesign of a business model, placing it in a value chain and value network ecosystem. As most of these BMI tools have a visual representation, such as the business model canvas, they facilitate creativity and analysis work in management groups with different functions, e.g., in workshops with visual boards. Moreover, while most BMI tools assume the profit objective it is important for managers to make the objective of the BMI process explicit as many of the tools may be used also for growth or creating new businesses. Making the objective explicit might be especially important for managers in government or non-profit organizations as these organizations often have other objectives than profit and growth. A final implication for managers is that BMI tools are mainly developed to support managers when established companies need to change their business model in three types of situations; changes due to digitalization, to develop and sharpen the company’s competitive advantages and when developing new businesses, i.e., corporate venturing.

The outbreak of COVID-19 has affected people all around the world. Governments had no choice but to put people in self-isolation to stop the spread of the virus. As a result, all companies and educational institutions switched to working or studying from home. The purpose of the study is to investigate the impact of COVID-19 on student teaching and learning in the context of Malmo university. Furthermore, the study proposes recommendations for sustainable post-pandemic education at Malmo University. The study includes ten semi-structured interviews with students followed by a workshop with ten senior lecturers teaching bachelor's and master's courses. The study uses snowball sampling to select students for the interviews and senior lecturers for the workshop. A qualitative data analysis technique, thematic analysis, is used for data analysis on the data collected from interviews with students and the workshop with senior lecturers. The results from the study suggested that online education leads to several benefits for students, such as better time management, higher lecture attendance, flexibility, and discipline in their studies. However, the shift to online education has caused a communication deterioration between students and teachers. Less social interaction with other students leads to depression, anxiety, and stress. The recommendations for post-pandemic education include the unified selection of digital learning tools across courses, a designated budget for digital learning tools, training support, and hybrid learning methods. In conclusion, the study proposes blended and hybrid learning to improve higher education at the university, requiring digital tools to minimize students' communication barriers.

The introduction of cloud technology has reduced the feedback time in software development for many companies. However, companies require significant resources to run applications in an Infrastructure as a Service. The study aims at developing an innovation platform which enables faster deployment of web-based applications. The innovation platform is an add-on for a cloud service, its purpose is to allow developers to set up and use multiple cameras in a cloud environment. Furthermore, the study investigates the drivers and value created by the platform for Axis. We developed a proof of concept built on the innovation platform, using the design science methodology and evaluated it in a focus group. The prototype was a mock version of a grocery store’s internal website, used to show the potential of the innovation platform. Moreover, we conducted semi-structured interviews to investigate the drivers for implementing the platform and the value it created. Results showed that the implementation of the prototype may make the deployment of web-based applications easier. A majority of the interviewees and the focus group participants agreed that the development of the innovation platform should continue and be tested to adopt the platform as a complement to AWS. However, the degree to which the platform should be open source needs a more clear management strategy. The prototype is seen as an innovation platform which may be used to quickly experiment with new ideas. The key drivers for implementing a prototype entails reduced cost, faster time to market and reduced complexity of web-based deployments.

The use of open-source software in business development has grown in the past five years. The rise of open source software has grabbed the attention of every industry such as e-commerce, fintech, cybersecurity, telecom, automotive, aviation, etc. This study aims to investigate how companies set up an open source program office (OSPO) to unlock the potential of OSS and to show the roadmap to set up an OSPO. We conducted two semi-structured interviews in two companies to identify the key components of open source operations. We found out that company A is more mature in open source operations compared to company B.

Moving toward the open innovation (OI) model requires multifaceted transformations within companies. It often involves giving away the tools for product development or sharing future product directions with open tools ecosystems. Moving from the traditional closed innovation model toward an OI model for software development tools shows the potential to increase software development competence and efficiency of organizations. We report a case study in software-intensive company developing embedded devices (e.g., smartphones) followed by a survey in OSS communities such as Gerrit, Git, and Jenkins. The studied branch focuses on developing Android phones. This paper presents contribution strategies and triggers for openness. These strategies include avoid forking OSS tools, empower developers to participate in the ecosystem, steer ecosystems through contributions, create business through differentiation, and create new ecosystems. The triggers of openness are from 30 different companies with examples. Finally, openness requires a cultural change aligned with strategies and business models.

Context: Open tools (e.g., Jenkins, Gerrit and Git) offer a lucrative alternative to commercial tools. Many companies and developers from OSS communities make a collaborative effort to improve the tools. Prior to this study, we developed an empirically based theory for companies' strategic choices on the development of these tools, based on empirical observations in the telecom domain. Aim: The aim of this study is to validate the theory of openness for tools in software engineering, in another domain, automotive. Specifically, we validated the theory propositions and mapped the case companies onto the model of openness. Method: We run focus groups in two automotive companies, collecting data in a survey and follow-up discussions. We used the repertory grid technique to analyze the survey responses, in combination with qualitative data from the focus group, to validate the propositions. Results: Openness of tools has the potential to reduce development costs and time, and may lead to process and product innovation. This study confirms three out of five theory propositions, on cost and time reduction, and the complementary role of open tools. One propositions was not possible to validate due to lack of investment in OSS tools communities by both companies. However, our findings extend the fifth proposition to require management being involved for both the proactive and reactive strategy. Further, we observe that the move towards open tools happen with a paradigm shift towards openness in the automotive domain, and lead to standardization of tools. Both companies confirm that they need legal procedures for the contribution, as well as an internal champion, driving the open tools strategy. Conclusion: We validated the theory, originating from the telecom domain, partially using two automotive companies. Both case companies are classified as laggards (reactive, cost saving) in the model of openness presented in the theory. Furthermore, we would like to have more validations studies to validate the remaining quadrants (e.g., leverage, lucrativeness and leaders).  

Context

The increased use of Open Source Software (OSS) affects how software-intensive product development organizations (SIPDO) innovate and compete, moving them towards Open Innovation (OI). Specifically, software engineering tools have the potential for OI, but require better understanding regarding what to develop internally and what to acquire from outside the organization, and how to cooperate with potential competitors.

Aim

This paper aims at synthesizing a theory of openness for software engineering tools in SIPDOs, that can be utilized by managers in defining more efficient strategies towards OSS communities.

Method

We synthesize empirical evidence from a systematic mapping study, a case study, and a survey, using a narrative method. The synthesis method entails four steps: (1) Developing a preliminary synthesis, (2) Exploring the relationship between studies, (3) Assessing the validity of the synthesis, and (4) Theory formation.

Result

We present a theory of openness for OSS tools in software engineering in relation to four constructs: (1) Strategy, (2) Triggers, (3) Outcomes, and (4) Level of openness.

Conclusion

The theory reasons that openness provides opportunities to reduce the development cost and development time. Furthermore, OI positively impacts on the process and product innovation, but it requires investment by organizations in OSS communities. By betting on openness, organizations may be able to significantly increase their competitiveness.