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Software startups continue to be important drivers of economy globally. As the initial investment required to found a new software company becomes smaller and smaller resulting from technological advances such as cloud technology, increasing numbers of new software startups are born. Typically, the main argument for studying software startups is that they differ from mature software organizations in various ways, thus making the findings of many existing studies not directly applicable to them. How, exactly, software startups really differ from other types of software organizations as an on-going debate. In this paper, we seek to better understand how software startups differ from mature software organizations in terms of development practices. Past studies have primarily studied method use, and in comparison, we take on a more atomic approach by focusing on practices. Utilizing the Essence Theory of Software Engineering as a framework, we split these practices into categories for analysis while simultaneously evaluating the suitability of the theory for the context of software startups. Based on the results, we propose changes to the Essence Theory of Software Engineering for it to better fit the startup context.

Software engineering courses include practical and theoretical elements that give many options for pedagogical combinations among them. In this paper, we report on two different pedagogical approaches for an undergraduate, introductory project-based software engineering course with more than 500 students working in collaborative scrum teams. We call one approach ‘Every Student is an Innovator’, and the other ‘No Student Left Behind’. This SE course has been long-running, with stable learning objectives and content. However, from one year to another, we radically changed the pedagogical approach of the course along several dimensions, among them the technical framework, software tools, project topic, mentor roles, assessment form and frequency, feedback and degree of student innovativeness. We report on the perceived challenges, detailed changes, the anticipated effects on the course learning outcomes. The results showed that innovativeness and fun need freedom and flexibility with processes and technology. However, strict design requirements and systematic guidance ensure fulfillment of learning objectives. Analyzing student and staff feedback, we find that both approaches lead to students using more time than intended and worrying about unknown assessment criteria. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

The workshop connects to the central theme “Educating for the Future” of CSEE&T 2020 and thus explores opportunities to improve Software Engineering education and training by using Essence. Essence, an OMG Standard, delivers essential, universal elements found in all Software Engineering (SE) endeavours and a language to describe and extend these elements and their use in concrete practices to tailor SE methods to teams' needs. Its Kernel separates the stable What and Why from the more adaptable How. That way, it provides an essential thinking framework facilitating the adoption and customization of practices and methods. As such, it supports multiple ways of educating SE students as well as training practitioners for the future. The first deployments of Essence in industry and academic courses around the globe show promising results. But since it is an entirely new way to think about SE practices, methods, and their building blocks—it requires some effort and thought to dive into the standard. This workshop facilitates the adoption by sharing experiences, best practices, and lessons learned.

There is a rapidly increasing amount of Artificial Intelligence (AI) systems developed in recent years, with much expectation on its capacity of innovation and business value generation. However, the promised value of AI systems in specific business contexts might not be understood, and further integrated into the development processes. We wanted to understand how software engineering processes and practices can be applied to develop AI systems in a fast-faced, business-driven manner. As the first step, we explored contextual factors of AI development and the connections between AI developments to business opportunities. We conducted 12 semi-structured interviews in seven companies in Brazil, Norway and Southeast Asia. Our investigation revealed different types of AI systems and different AI development approaches. However, it is common that business opportunities involving with AI systems are not validated and there is lack of business-driven metrics that guide the development of AI systems. The findings have implications for future research on business-driven AI development and supporting tools and practices. peerReviewed

Software startups need to work in a systematic fashion just like mature organizations. However, existing software engineering methods and practices are not aimed at software startups. They do not account for the business aspect of startups and may not be well suited for software startups in general. The Lean Startup Methodology on the other hand contains some useful practices for software startups but is nonetheless impractical, offering little in the way of telling you what to do. Software startups are thus required to tailor their own method. Currently, many software startups simply work ad hoc or use various Agile methods and practices. In terms of Agile methods and practices, little consensus exists between startups. In this chapter, we discuss methods and method tailoring. We give guidelines on how to create your own way of working and recommend a tangible tool for doing so: the Essence Theory of Software Engineering. peerReviewed

Early prediction of software quality is important for better software planning and controlling. In early development phases, design complexity metrics are considered as useful indicators of software testing effort and some quality attributes. Although many studies investigate the relationship between design complexity and cost and quality, it is unclear what we have learned beyond the scope of individual studies. This paper presented a systematic review on the influence of software complexity metrics on quality attributes. We aggregated Spearman correlation coefficients from 59 different data sets from 57 primary studies by a tailored meta-analysis approach. We found that fault proneness and maintainability are most frequently investigated attributes. Chidamber and Kemerer metric suite is most frequently used but not all of them are good quality attribute indicators. Moreover, the impact of these metrics is not different in proprietary and open source projects. The result provides some implications for building quality model across project type, Comment: This is the author's version of the work

Software cost estimation is the process of forecasting the effort needed to develop the software system. Global software engineering (GSE) highlights that software development knows no boundaries and majority of the software products and services are developed today by globally-distributed teams, projects, and companies. The problem of cost estimation gets more complex if the discussion is carried out in the context of GSE, which has its own issues. Temporal, cultural, and geographical distance creates communication and software process implementation issues. Traditional software process models such as capability maturity model (CMM) lacks the dynamism to accommodate the recent trends in GSE. The chapter introduces GSE and discusses various cost estimation techniques and different levels of CMM. A couple of GSE-based case studies having CMM-level projects from multiple organizations are studied to analyze the impacts of highly mature processes on effort, quality, and cycle time.

Context: Software has become ubiquitous in every corner of modern societies. During the last five decades, software engineering has also changed significantly to advance the development of various types and scales of software products. In this context, Software Engineering Education plays an important role in keeping students updated with software technologies, processes, and practices that are popular in industries. Objective: We investigate from literature the extent Software Engineering Education addresses major Software Engineering Trends in the academic setting. Method: We conducted a systematic mapping study about teaching major Software Engineering Trends in project courses. We classified 126 papers based on their investigated Software Engineering Trends, specifically Software Engineering processes and practices, teaching approaches, and the evolution of Software Engineering Trends over time. Results: We reveal that Agile Software Development is the major trend. The other Trends, i.e., Software Implementation, Usability and Value, Global Software Engineering, and Lean Software Startup, are relatively small in the academic setting, but continuously growing in the last five years. System of Systems is the least investigated among all Trends. Conclusions: The study points out the possible gaps between Software Industry and Education, which implies actionable insights for researchers, educators, and practitioners.

Software Engineering as an industry is highly diverse in terms of development methods and practices. Practitioners employ a myriad of methods and tend to further tailor them by e.g. omitting some practices or rules. This diversity in development methods poses a challenge for software engineering education, creating a gap between education and industry. General theories such as the Essence Theory of Software Engineering can help bridge this gap by presenting software engineering students with higher-level frameworks upon which to build an understanding of software engineering methods and practical project work. In this paper, we study Essence in an educational setting to evaluate its usefulness for software engineering students while also investigating barriers to its adoption in this context. To this end, we observe 102 student teams utilize Essence in practical software engineering projects during a semester long, project-based course., Preprint submitted and accepted to the 2018 International Conference on Product-Focused Software Process Improvement (PROFES2018)

Software ecosystems (SECOs) and open innovation processes have been claimed as a way forward for the software industry. A proper understanding of requirements is as important for these IT-systems as for more traditional ones. This paper presents a mapping study on the issues of requirements engineering and quality aspects in SECOs and analyzes emerging ideas. Our findings indicate that among the various phases or subtasks of requirements engineering, most of the SECO specific research has been accomplished on elicitation, analysis, and modeling. On the other hand, requirements selection, prioritization, verification, and traceability has attracted few published studies. Among the various quality attributes, most of the SECOs research has been performed on security, performance and testability. On the other hand, reliability, safety, maintainability, transparency, usability attracted few published studies. The paper provides a review of the academic literature about SECO-related requirements engineering activities, modeling approaches, and quality attributes, positions the source publications in a taxonomy of issues and identifies gaps where there has been little research., Comment: Journal of Information Technology Research (JITR) 11(1)

The rapid growth of Internet-of-things (IoT) software applications has driven both practitioners and researchers' attention to methodological approaches for secure IoT development. Security issues for IoT is special in the way that they include not only software, but also hardware and network concerns. With the aim at proposing a methodological approach for secure IoT application development, we investigated what are security challenges in the context of IoT development. We reviewed literature and investigated two industry cases. The preliminary finding results in a list of 17 security challenges with regards to technical, organizational and methodological perspectives. Cross-case comparison provides initial explanation about the less emphasis on methodological and organizational security concerns in our cases.

[Context] With the proliferation of desktop and mobile platforms the development and maintenance of identical or similar applications on multiple platforms is urgently needed. [Goal] We study a software product deployed to more than 25 software/hardware combinations over 10 years to understand multi-platform development practices. [Method] We use semi structured interviews, project wikis, VCSs and issue tracking systems to understand and quantify these practices. [Results] We find the projects using MR cloning, MR review meeting, cross platform coordinator's role as three primary means of coordination. We find that forking code temporarily relieves the coordination needs and is driven by divergent schedule, market needs, and organizational policy. Based on our qualitative findings we propose quantitative measures of coordination, redundant work, and parallel development. [Conclusions] A model of coordination intensity suggests that it is related to the amount of paralel and redundant work. We hope that this work will provide a basis for quantitative understanding of issues faced in multi-platform software development.