Background: Systematic literature reviews (SLRs) have become prevalent in software engineering research. Several researchers may conduct SLRs on similar topics without a prospective register for SLR protocols. However, even ignoring these unavoidable duplications of effort in the simultaneous conduct of SLRs, the proliferation of overlapping and often repetitive SLRs indicates that researchers are not extensively checking for existing SLRs on a topic. Given how effort-intensive it is to design, conduct, and report an SLR, the situation is less than ideal for software engineering research. Aim: To understand how authors justify additional SLRs on a topic. Method: To illustrate the issue and develop suggestions for improvement to address this issue, we have intentionally picked a sufficiently narrow but well-researched topic, i.e., effort estimation in Agile software development. We identify common justification patterns through a qualitative content analysis of$\mathbf{1 8}$published SLRs. We further consider the citation data, publication years, publication venues, and the quality of the SLRs when interpreting the results. Results: The common justification patterns include authors claiming gaps in coverage, methodological limitations in prior studies, temporal obsolescence of previous SLRs, or rapid technological and methodological advancements necessitating updated syntheses. Conclusion: Our in-depth analysis of SLRs on a fairly narrow topic provides insights into SLRs in software engineering in general. By emphasizing the need for identifying existing SLRs and for justifying the undertaking of further SLRs, both in design and review guidelines and as a policy of conferences and journals, we can reduce the likelihood of duplication of effort and increase the rate of progress in the field.

[Context]: The COVID-19 pandemic has disrupted the global market and workplace landscape. As a response, hybrid work situations have become popular in the software business sector. This way of working has an impact on software companies. [Objective]: This study investigates software companies' responses to hybrid working. [Method]: We conducted a large-scale survey to achieve our objective. Our results are based on a qualitative analysis of 124 valid responses. [Results]: The main result of our study is a taxonomy of software companies' impacts on hybrid working at individual, team and organisation levels. We found higher positive responses at individual and organisational levels than negative responses. At the team level, both positive and negative impacts obtained a uniform number of responses. [Conclusion]: The results indicate that hybrid working became credible with the wave of COVID-19, with 83 positive responses outweighing the 41 negative responses. Software company respondents witnessed better work-life balance, productivity, and efficiency in hybrid working.

Context: Generative AI (GenAI) brings new op-portunities to the software industry and the digital economy in a broader context. Objective: This study aimed to explore and capture the practitioners' perception of GenAI adoption in the fast-paced software industry in the context of developing countries. Method: We conducted online focus group discussions with 18 practitioners from various roles to collect qualitative data. The practitioners have an average of 7.8 years of working experience and have used GenAI for over a year. We employed thematic analysis and the Human-AI Collaboration and Adaptation Framework (HACAF) to identify the influencing factors of GenAI adoption, such as awareness, use cases, and challenges. Results: The adoption of GenAI technology is evident from practitioners. We identified 22 practical use cases, three of which were novel, i.e., contextualizing solutions, assisting the internal audit process, and benchmarking the internal software development process. We also discovered seven key challenges associated with the GenAI adoption, two of which were novel, namely, no matching use cases and unforeseen benefits. These challenges slow GenAI adoption and potentially hinder developing countries from entering a high-skill industry. Conclusion: While the adoption of GenAI technology is promising, industry-academia collaboration is needed to find solutions and strategies to address the challenges and maximize its potential benefits.

Context The COVID‐19 pandemic has had a disruptive impact on how people work and collaborate across all global economic sectors, including software business. While remote working is not new for software engineers, forced WFH situations come with both limitations and opportunities. As the ‘new normal’ for working might be based on the current state of Work‐from‐home (WFH), it is useful to understand what has happened and learn from that. Objective This study aims to gain insights into how their WFH arrangement impacts project management and software engineering. We are also interested in exploring these impacts in different contexts, such as startups and established companies. Method We conducted a global‐scale, cross‐sectional survey during the spring and summer 2021. Our results are based on quantitative and qualitative analysis of 297 valid responses. Results We characterize the profile of WFH in both spatial and temporal aspects, together with a set of common collaborative tools and coordination and control mechanisms. We revealed some areas of project management that are relatively more challenging during WFH situations, such as coordination, communication and project planning. We also revealed a mixed picture of the perceived impact of WFH on different software engineering activities. Conclusion WFH is a situational phenomenon which can have both negative and positive impact on software teams. For practitioners, we suggest a unified approach to consider the context of WFH, collaborative tools, associated coordination and control approaches and a process that resolve those aspects that are sensitive to physical interaction.

[Context] Systematic Literature Review (SLR) has been a major type of study published in Software Engineering (SE) venues for about two decades. However, there is a lack of understanding of whether an SLR is really needed in comparison to a more conventional literature review. Very often, SE researchers embark on an SLR with such doubts. We aspire to provide more understanding of when an SLR in SE should be conducted. [Objective] The first step of our investigation was focused on the dataset, i.e., the reviewed papers, in an SLR, which indicates the development of a research topic or area. The objective of this step is to provide a better understanding of the characteristics of the datasets of SLRs in SE. [Method] A research synthesis was conducted on a sample of 170 SLRs published in top-tier SE journals. We extracted and analysed the quantitative attributes of the datasets of these SLRs. [Results] The findings show that the median size of the datasets in our sample is 57 reviewed papers, and the median review period covered is 14 years. The number of reviewed papers and review period have a very weak and non-significant positive correlation. [Conclusions] The results of our study can be used by SE researchers as an indicator or benchmark to understand whether an SLR is conducted at a good time.

Following the highly pervasive and effective use of agile methods at the team level, many software organisations now wish to replicate this success at the organisational level, adopting large-scale agile methods such as SAFe, Scrum-at-Scale, and others. However, this has proven significantly challenging. An analysis of the extant literature reveals a disparate set of studies across each individual method, with no cross-method comparison based on empirical evidence. This systematic literature review compares the main large-scale agile methods, namely SAFe, LeSS, Scrum-at-Scale, DAD, and the Spotify model. It is the first study to analyse and compare each of the method’s principles, practices, tools, and metrics in a standardised manner. For each method, it presents not just the original method specifications but also all extensions and modifications to each method proposed by subsequent empirical research. It includes in this comparison not just commercial large-scale methods but also those that have been custom-built in organisations such as Nokia, Ericsson, and others. Based on the findings reported in this study, practitioners can make a more informed decision as to which commercial method or method component or, indeed, custom-built method is better suited to their needs. Our study reveals a number of theoretical and practical issues in the current literature, such as an emphasis on the practices of commercial frameworks at the expense of their underlying principles, or indeed any of the custom method. A set of challenges and success factors associated with the use of large-scale agile methods are identified. The study also identifies a number of research gaps to be addressed across methods.

Software startups develop innovative, software-intensive products or services. Such innovativeness translates into uncertainty regarding a matching need for a product from potential customers, representing a possible determinant reason for startup failure. Research has shown that experimentation, an approach based on the use of experiments to guide several aspects of software development, could improve these companies’ success rate by fostering the evaluation of assumptions about customers’ needs before developing a full-fledged product. Nevertheless, software startups are not using experimentation as expected. In this study, we investigated the reasons behind such a mismatch between theory and practice. To achieve it, we performed a qualitative survey study of 106 failed software startups. We built the eXperimentation Progression model (XPro), demonstrating that the effective adoption and implementation of experimentation is a staged process: first, teams should be aware of experimentation, then they need to develop an intention to experiment, perform the experiments, analyze the results, and finally act based on the obtained learning. Based on the XPro model, we further identified 25 inhibitors that prevent a team from progressing along the stages properly. Our findings inform researchers of how to develop practices and techniques to improve experimentation adoption in software startups. Practitioners could learn various factors that could lead to their startup failure so they could take action to avoid them.

Background: Measuring an organization's capability to innovate and assessing its innovation output and performance is a challenging task. Previously, a comprehensive model and a suite of measurements to support this task were proposed. Aims: In the current paper, seven years since the publication of the paper titled Towards innovation measurement in the software industry, we have reflected on the impact of the work. Method: We have mainly relied on quantitative and qualitative analysis of the citations of the paper using an established classification schema. Results: We found that the article has had a significant scientific impact (indicated by the number of citations), i.e., (1) cited in literature from both software engineering and other fields, (2) cited in grey literature and peer-reviewed literature, and (3) substantial citations in literature not published in the English language. However, we consider a majority of the citations in the peer-reviewed literature (75 out of 116) as neutral, i.e., they have not used the innovation measurement paper in any substantial way. All in all, 38 out of 116 have used, modified or based their work on the definitions, measurements or the model proposed in the article. This analysis revealed a significant weakness of the citing work, i.e., among the citing papers, we found only two explicit comparisons to the innovation measurement proposal, and we found no papers that identify weaknesses of said proposal. Conclusions: This work highlights the need for being cautious of relying solely on the number of citations for understanding impact, and the need for further improving and supporting the peer-review process to identify unwarranted citations in papers.

Business Model Canvas (BMC) is a tool widely used to describe startup business models. Despite the various business aspects described, BMC pays a little emphasis on team- related factors. The importance of team-related factors in software development has been acknowledged widely in literature. While not as extensively studied, the importance of teams in software startups is also known in both literature and among practitioners. In this paper, we propose potential changes to BMC to have the tool better reflect the importance of the team, especially in a software startup environment. Based on a literature review, we identify various components related to the team, which we then further support with empirical data. We do so by means of a qualitative case study of five startups.

Context Inner source software development (ISSD) has been viewed as an alternative approach in which organisations adopt open source software development (OSSD) practices and exploit its benefits internally. Objective In this paper, we aim to provide an extensive review of current research on ISSD and to establish a research agenda on this domain. Method The review is primarily performed using a systematic literature review protocol. Results We identified, critically evaluated and integrated the findings of 37 primary studies, describing 25 empirical research papers, 10 frameworks/methods, models and tools to support the implementation of inner source, as well as a set of benefits and challenges associated with ISSD. Conclusion This study presents four main contributions. First, the study provides an in-depth review of ISSD to date, i.e. the evolution of research across inner source, contributions of existing research developments, and theories, models and frameworks used to study inner source. Second, our review applies the OSSD approach framework as the lens to analyse ISSD. Third, the review updates the key challenges associated with ISSD from a management perspective. The final contribution is the establishment of a research agenda to advance knowledge on ISSD.

This extended abstract summarises an article, which has been published in the Information and Software Technology (IST) Journal and was selected for the Journal-First presentations at the International Conference on Software and System Process (ICSSP 2018). Full Article Reference. Henry Edison, Xiaofeng Wang, Ronald Jabangwe, and Pekka Abrahamsson. 2018. Innovation Initiatives in Large Software Companies: A Systematic Mapping Study. Information and Software Technology, 95:1--14, (March 2018) DOI:10.1016/j.infsof.2017.12.007.

Given the value and effectiveness of open source software development to date, practitioners are keen to replicate these practices inside their respective corporations. This application of open source practices inside the confines of a corporate entity has been coined inner source software development. However, while organisations have found ways to directly benefit from revenue streams as a result of leveraging open source practices internally, the current research on inner source is scattered among different areas. Thus gaining clarity on the state-of-the-art in inner source research is challenging. In particular, there is no systematic literature review of known research to date on inner source. We address this challenge by presenting a systematic literature review that identifies, critically evaluates and integrates the findings of 29 primary studies on inner source. Case study approach is the common research approach undertaken in the area. We also identified 8 frameworks/methods, models and tools proposed in the literature to support inner source, as well as a set of benefits and challenges associated with inner source. We envision future work to perform deeper analysis and synthesis on the empirical research on inner source software development.

To keep the competitive advantage and adapt to changes in the market and technology, companies need to innovate in an organised, purposeful and systematic manner. However, due to their size and complexity, large companies tend to focus on maintaining their business, which can potentially lower their agility to innovate. This study aims to provide an overview of the current research on innovation initiatives and to identify the challenges of implementing the initiatives in the context of large software companies. The investigation was performed using a systematic mapping approach of published literature on corporate innovation and entrepreneurship. Then it was complemented with interviews with four experts with rich industry experience. Our study results suggest that, there is a lack of high quality empirical studies on innovation initiative in the context of large software companies. A total of 7 studies are conducted in such context, which reported 5 types of initiatives: intrapreneurship, bootlegging, internal venture, spin-off and crowdsourcing. Our study offers three contributions. First, this paper represents the map of existing literature on innovation initiatives inside large companies. The second contribution is to provide an innovation initiative tree. The third contribution is to identify key challenges faced by each initiative in large software companies. At the strategic and tactical levels, there is no difference between large software companies and other companies. At the operational level, large software companies are highly influenced by the advancement of Internet technology. Large software companies use open innovation paradigm as part of their innovation initiatives. We envision a future work is to further empirically evaluate the innovation initiative tree in large software companies, which involves more practitioners from different companies.

Product innovation is a risky activity, but when successful, it enables large software companies accrue high profits and leapfrog the competition. Internal startups have been promoted as one way to foster product innovation in large companies, which allows them to innovate as startups do. However, internal startups in large companies are challenging endeavours despite of the promised benefits. How large software companies can leverage internal startups in software product innovation is not fully understood due to the scarcity of the relevant studies. Based on a conceptual framework that combines the elements from the Lean startup approach and an internal corporate venturing model, we conducted a case study of a large software company to examine how a new product was developed through the internal startup effort and struggled to achieve the desired outcomes set by the management. As a result, the conceptual framework was further developed into a Lean startup-enabled new product development model for large software companies.

Software startups are challenging endeavours, with various road blocks on their path to success. The current understanding of the challenges that software startups may encounter is very limited. In this paper, we use the research framework of learning and product development stages to analyse the key challenges that software startups have to deal with at different life cycle stages, from problem definition to solution validation and from concept to mature product. Based on an analysis of the empirical data collected by a large survey of 4100 startups, we find out that what perceived as biggest challenges by software startups do vary across different life cycle stages. Building product is the biggest obstacle for software startups, even though its significance decreases when the learning focuses of the startups move from problem to solution and their products mature. Business related challenges such as customer acquisition and scaling are more noticeable at the later stages. Our study raises the awareness of these challenges and suggests to tackle right challenges at the right time.