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Context. Software Performance Antipatterns (SPAs) research has focused on algorithms for the characterization, detection, and solution of antipatterns. However, existing algorithms are based on the analysis of runtime behavior to detect trends on several monitored variables (e.g., response time, CPU utilization, and number of threads) using pre-defined thresholds. Objective. In this paper, we introduce a new approach for SPA characterization and detection designed to support continuous integration/delivery/deployment (CI/CDD) pipelines, with the goal of addressing the lack of computationally efficient algorithms. Method. Our approach includes SPA statistical characterization using a multivariate analysis approach of load testing experimental results to identify the services that have the largest impact on system scalability. More specifically, we introduce a layered decomposition approach that implements statistical analysis based on response time to characterize load testing experimental results. A distance function is used to match experimental results to SPAs. Results. We have instantiated the introduced methodology by applying it to a large complex telecom system. We were able to automatically identify the top five services that are scalability choke points. In addition, we were able to automatically identify one SPA. We have validated the engineering aspects of our methodology and the expected benefits by means of a domain experts' survey. Conclusion. We contribute to the state-of-The-Art by introducing a novel approach to support computationally efficient SPA characterization and detection in large complex systems using performance testing results. We have compared the computational efficiency of the proposed approach with state-of-The-Art heuristics. We have found that the approach introduced in this paper grows linearly, which is a significant improvement over existing techniques. © 2021 ACM. open access

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 thework. 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 peerreviewed 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. © 2020 IEEE Computer Society. All rights reserved. open acess

Regulatory compliance is a well-studied area, including research on how to model, check, analyse, enact, and verify compliance of software. However, while the theoretical body of knowledge is vast, empirical evidence on challenges with regulatory compliance, as faced by industrial practitioners particularly in the Software Engineering domain, is still lacking. In this paper, we report on an industrial case study which aims at providing insights into common practices and challenges with checking and analysing regulatory compliance, and we discuss our insights in direct relation to the state of reported evidence. Our study is performed at Ericsson AB, a large telecommunications company, which must comply to both locally and internationally governing regulatory entities and standards such as GDPR. The main contributions of this work are empirical evidence on challenges experienced by Ericsson that complement the existing body of knowledge on regulatory compliance., Comment: Full research paper accepted at International Conference on Product-Focused Software Process Improvement 2020

[Context and motivation] To validate developers’ ideas of what users might want and to understand user needs, it has been proposed to collect and combine system monitoring with user feedback. [Question/problem] So far, the monitoring data and feedback have been collected passively, hoping for the users to get active when problems emerge. This approach leaves unexplored opportunities for system improvement when users are also passive or do not know that they are invited to offer feedback. [Principal ideas/results] In this paper, we show how we have used goal monitors to identify interesting situations of system use and let a system autonomously elicit user feedback in these situations. We have used a monitor to detect interesting situations in the use of a system and issued automated requests for user feedback to interpret the monitoring observations from the users’ perspectives. [Contribution] The paper describes the implementation of our approach in a Smart City system and reports our results and experiences. It shows that combining system monitoring with proactive, autonomous feedback collection was useful and surfaced knowledge of system use that was relevant for system maintenance and evolution. The results were helpful for the city to adapt and improve the Smart City application and to maintain their internet-of-things deployment of sensors.

Context Embedded systems have overwhelming penetration around the world. Innovations are increasingly triggered by software embedded in automotive, transportation, medical-equipment, communication, energy, and many other types of systems. To test embedded software in an effective and efficient manner, a large number of test techniques, approaches, tools and frameworks have been proposed by both practitioners and researchers in the last several decades. Objective However, reviewing and getting an overview of the entire state-of-the-art and the –practice in this area is challenging for a practitioner or a (new) researcher. Also unfortunately, as a result, we often see that many companies reinvent the wheel (by designing a test approach new to them, but existing in the domain) due to not having an adequate overview of what already exists in this area. Method To address the above need, we conducted and report in this paper a systematic literature review (SLR) in the form of a systematic literature mapping (SLM) in this area. After compiling an initial pool of 588 papers, a systematic voting about inclusion/exclusion of the papers was conducted among the authors, and our final pool included 312 technical papers. Results Among the various aspects that we aim at covering, our review covers the types of testing topics studied, types of testing activity, types of test artifacts generated (e.g., test inputs or test code), and the types of industries in which studies have focused on, e.g., automotive and home appliances. Furthermore, we assess the benefits of this review by asking several active test engineers in the Turkish embedded software industry to review its findings and provide feedbacks as to how this review has benefitted them. Conclusion The results of this review paper have already benefitted several of our industry partners in choosing the right test techniques / approaches for their embedded software testing challenges. We believe that it will also be useful for the large world-wide community of software engineers and testers in the embedded software industry, by serving as an “index” to the vast body of knowledge in this important area. Our results will also benefit researchers in observing the latest trends in this area and for identifying the topics which need further investigations.

Background: Achieving and maintaining a strategic competitive advantage through business and technology innovation via continually improving effectiveness and efficiency of the operations are the critical survival factors for software-intensive product development companies. These companies invest in business modeling and tool support for integrating business models into their product development, but remain uncertain, if such investments generate desired results. Aim: This study explores the effects of business modeling on effectiveness and efficiency for companies developing software-intensive products. Method: We conducted a systematic literature review using the snowballing methodology, followed by thematic and narrative analysis. 57 papers were selected for analysis and synthesis, after screening 16 320 papers from multiple research fields. Results: We analyzed the literature based on purpose, benefit, challenge, effectiveness, and efficiency with software and software-intensive products as the unit of analysis. The alignment between strategy and execution is the primary challenge, and we found no evidence that business modeling increases effectiveness and efficiency for a company. Any outcome variations may simply be a result of fluctuating contextual or environmental factors rather than the application of a specific business modeling method. Therefore, we argue that governance is the fundamental challenge needed for business modeling, as it must efficiently support simultaneous experimentation with products and business models while turning experiences into knowledge. Conclusion: We propose a conceptual governance model for exploring the effectiveness and efficiency of business modeling to occupy the missing link between business strategy, processes and software tools. We also recommend managers to introduce a systematic approach for experimentation and organizational learning, collaboration, and value co-creation. open access

This papers surveys current stakeholder identification methods and techniques from the Requirements Engineering (RE) discipline. Upon critical analysis of available models and techniques, we identify the techniques that should be prioritized when identifying stakeholders that should be involved in the decision making processes about software components or assets. Next, we analyzed industrial decision scenarios and match the most prominent issues with stakeholder identification against the perceived benefits that the identified techniques offer. We conclude this paper with a research agenda in stakeholder identification for decision making about software components. © 2017 IEEE.

Smart contracts are seen as the major building blocks for future autonomous blockchain- and Distributed Ledger Technology (DLT)-based applications. Engineering such contracts for trustless, append-only, and decentralized digital ledgers allows mutually distrustful parties to transform legal requirements into immutable and formalized rules. Previous experience shows this to be a challenging task due to demanding socio-technical ecosystems and the specificities of decentralized ledger technology. In this paper, we therefore develop an integrated process model for engineering DLT-based smart contracts that accounts for the specificities of DLT. This model was iteratively refined with the support of industry experts. The model explicitly accounts for the immutability of the trustless, append-only, and decentralized DLT ecosystem, and thereby overcomes certain limitations of traditional software engineering process models. More specifically, it consists of five successive and closely intertwined phases: conceptualization, implementation, approval, execution, and finalization. For each phase, the respective activities, roles, and artifacts are identified and discussed in detail. Applying such a model when engineering smart contracts will help software engineers and developers to better understand and streamline the engineering process of DLTs in general and blockchain in particular. Furthermore, this model serves as a generic framework which will support application development in all fields in which DLT can be applied.

High-quality work is said to depend on team abilities. However, teams working in large-scale projects often do not have all expertise to complete their tasks, which are also highly interdependent. Therefore, teams need to rely on coordination with other teams, experts, and supporting roles. In this paper, we explore teams' coordination needs and evaluate the impact of the satisfaction of these needs on team performance. We conducted an embedded multicase study with nine teams in two projects in two companies. We collected qualitative data through nine focus groups and 19 interviews and quantitative data using a questionnaire with 49 members from the studied teams. Our results suggest that project-, team-, and task-related characteristics impact teams' coordination needs. Even in the same project, teams may have different expertise and work coordination needs. We found that the satisfaction of these needs seems to influence teams' performance, although our results are inconclusive and yield a closer look in future research. On the basis of our findings, we recommend the companies to cultivate a networking culture and support teams external coordination with other teams and experts, paying attention to their needs, for example, driven by a lack of experience or increased work complexity. © 2020 The Authors. Journal of Software: Evolution and Process published by John Wiley & Sons Ltd Open access

The successful launch of an innovation project de-pends on an attractive vision and how well the vision is supported by the complementary capabilities of the consortium partners that want to cooperate to realize the vision. Alas, for an innovator the search for the right partners and visions can be lengthy and diffi-cult. Even though the analysis of context and problem, the identi-fication of stakeholders, the analysis of stakeholder goals and tech-nological capabilities, and the definition of requirements belong to the cornerstones of requirements engineering, this requirementsengineering problem has hardly been explored so far. In an at-tempt to avoid re-invention of well-tried solutions, we discovered journalism as a discipline that, as a rich body of methodical knowledge, may act as a source for the guidance of how a require-ments engineer may support the launch of innovation projects. In the role of a journalist, the requirements engineer makes partners and their capabilities visible and thereby allows the parties to iden-tify each other and meet. The transparency that develops between the parties becomes an instrument for consortia to emerge and to eventually answer calls for innovation with appropriate visions for innovation projects. This paper introduces the problem of initiat-ing innovation projects and describes the potential role of journal-ism as a metaphor for addressing the problem. The paper also de-scribes our plans in designing an innovation journalism approach that we hope will enable requirements engineers to increase inno-vation potential and ease the launch of projects that bring about these innovations.

With the growing interest of adopting agile methods in offshored process, many companies realized that the use of agile methods and practices in companies located outside the location of early adopters of agile methods may be challenging. India, the main destination of offshoring contracts, have received particular attention, due to the big cultural differences. Critical analysis of related studies suggests that impeding behaviors are mostly rooted in the hierarchical culture of Indian organizations and related management behavior of command-and-control. But what happens in distributed projects with a more empowering onshore management? In this paper, we present the findings from a multiple-case study of DevOps teams with members from a mature agile company located in Sweden and a more hierarchical offshore vendor from India. Based on two focus groups we list culturally different behaviors of offshore engineers that were reported to impede agile ways of working. Furthermore, we report the findings from surveying 36 offshore team members from five DevOps teams regarding their likely behavior in situations reported to be problematic. Our findings confirm a number of previously reported behaviors rooted in cultural differences that impede the adoption of agile ways of working when collaborating with offshore engineers. At the same time, our survey results suggest that among the five surveyed teams there were teams that succeeded with the cultural integration of the offshore team members. Finally, our findings demonstrate the importance of cultural training especially when onboarding new team members. © The Author(s) 2020. Open access

Software start-up failures are often explained with a poor business model, market issues, insufficient funding, or simply a bad product idea. However, inadequacies in software engineering are relatively unexplored and could be a significant contributing factor to the high start-up failure rate. In this paper we present the analysis of 88 start-up experience reports, revealing three anti-patterns associated with start-up progression phases. The anti-patterns address challenges of releasing the first version of the product, attracting customers, and expanding the product into new markets. The anti-patterns show that challenges and failure scenarios that appear to be business or market related are, at least partially, rooted in engineering inadequacies.

UML activity diagrams and state machines are both used for modeling system behavior from the user perspective and are frequently the basis for deriving system test cases. In practice, system test cases are often derived manually from UML activity diagrams or state machines. For this task, comprehensibility of respective models is essential and a relevant question for practice to support model selection and design, as well as subsequent test derivation. Therefore, the objective of this paper is to compare the comprehensibility of UML activity diagrams and state machines during manual test case derivation. We investigate the comprehensibility of UML activity diagrams and state machines in a controlled student experiment. Three measures for comprehensibility have been investigated: (1) the self-assessed comprehensibility, (2) the actual comprehensibility measured by the correctness of answers to comprehensibility questions, and (3) the number of errors made during test case derivation. The experiment was performed and internally replicated with overall 84 participants divided into three groups at two institutions. Our experiment indicates that activity diagrams are more comprehensible but also more error-prone with regard to manual test case derivation and discusses how these results can improve system modeling and test case design. open access

To assess the benefits of introducing Agile practices, it is important to get a clear understanding of the baseline situation, i.e. the situation before their introduction. Without a clear baseline, we cannot properly assess the extent of impacts, both positive and negative, of introducing Agile practices. This paper provides a preliminary guideline to help researchers in capturing and reporting baseline situations. The guideline has been developed through the study of literature and interviews with industry practitioners, and validated by experts in academia.

In this paper, we present experiences from eight years of developing a financial transaction engine, using what can be described as an integration-test-centric software development process.We discuss the product and the relation between three different categories of its software and how the relative weight of these artifacts has varied over the years.In addition to the presentation, some challenges and future research directions are discussed. https://profes2018.wordpress.com/

Context: The development of software-intensive systems includes many decisions involving various stakeholders with often conflicting interests and viewpoints. Objective: Decisions are rarely systematically documented and sporadically explored. This limits the opportunity for learning and improving on important decisions made in the development of software-intensive systems. Method: In this work, we enable support for the systematic documentation of decisions, improve their traceability and contribute to potentially improved decision-making in strategic, tactical and operational contexts. Results: We constructed a taxonomy for documentation supporting decision-making, called GRADE. GRADE was developed in a research project that required composition of a common dedicated language to make feasible the identification of new opportunities for better decision support and evaluation of multiple decision alternatives. The use of the taxonomy has been validated through thirty three decision cases from industry. Conclusion: This paper occupies this important yet greatly unexplored research gap by developing the GRADE taxonomy that serves as a common vocabulary to describe and classify decision-making with respect to architectural assets. © 2018 Elsevier B.V.

Improved information flow analysis in the context of value stream mapping.A practical methodology for process assessment and improvement using Lean principles.Evaluation of the proposal in large-scale commercial software development.Provides guidance by reporting details of the operationalization and the outcome. Value stream mapping (VSM) has been successfully applied in the context of software process improvement. However, its current adaptations from Lean manufacturing focus mostly on the flow of artifacts and have taken no account of the essential information flows in software development. A solution specifically targeted toward information flow elicitation and modeling is FLOW. This paper aims to propose and evaluate the combination of VSM and FLOW to identify and alleviate information and communication related challenges in large-scale software development. Using case study research, FLOW-assisted VSM was used for a large product at Ericsson AB, Sweden. Both the process and the outcome of FLOW-assisted VSM have been evaluated from the practitioners' perspective. It was noted that FLOW helped to systematically identify challenges and improvements related to information flow. Practitioners responded favorably to the use of VSM and FLOW, acknowledged the realistic nature and impact on the improvement on software quality, and found the overview of the entire process using the FLOW notation very useful. The combination of FLOW and VSM presented in this study was successful in systematically uncovering issues and characterizing their solutions, indicating their practical usefulness for waste removal with a focus on information flow related issues.

Systematic literature reviews in software engineering are necessary to synthesize evidence from multiple studies to provide knowledge and decision support. However, synthesis methods are underutilized in software engineering research. Moreover, translation of synthesized data (outcomes of a systematic review) to provide recommendations for practitioners is seldom practiced. The objective of this paper is to introduce the use of Bayesian synthesis in software engineering research, in particular to translate research evidence into practice by providing the possibility to combine contextualized expert opinions with research evidence. We adopted the Bayesian synthesis method from health research and customized it to be used in software engineering research. The proposed method is described and illustrated using an example from the literature. Bayesian synthesis provides a systematic approach to incorporate subjective opinions in the synthesis process thereby making the synthesis results more suitable to the context in which they will be applied. Thereby, facilitating the interpretation and translation of knowledge to action/application. None of the synthesis methods used in software engineering allows for the integration of subjective opinions, hence using Bayesian synthesis can add a new dimension to the synthesis process in software engineering research.

Background: Developers and development teams in large-scale software development are often required to learn continuously. Organizations also face the need to train and support new developers and teams on-boarded in ongoing projects. Although learning is associated with performance improvements, experience shows that training and learning does not always result in a better performance or significant improvements might take too long. Aims: In this paper, we report our experiences from establishing an approach to measure learning results and associated performance impact for developers and teams in Ericsson. Method: Experiences reported herein are a part of an exploratory case study of an on-going large-scale distributed project in Ericsson. The data collected for our measurements included archival data and expert knowledge acquired through both unstructured and semi-structured interviews. While performing the measurements, we faced a number of challenges, documented in the form of lessons learned. Results: We aggregated our experience in eight lessons learned related to collection, preparation and analysis of data for further measurement of learning potential and performance in large-scale distributed software development. Conclusions: Measuring learning and performance is a challenging task. Major problems were related to data inconsistencies caused by, among other factors, distributed nature of the project. We believe that the documented experiences shared herein can help other researchers and practitioners to perform similar measurements and overcome the challenges of large-scale distributed software projects, as well as proactively address these challenges when establishing project measurement programs.

Shared understanding of requirements between stakeholders and the development team is a critical success factor for requirements engineering. Workshops are an effective means for achieving such shared understanding since stakeholders and team representatives can meet and discuss what a planned software system should be and how it should support achieving stakeholder goals. However, some important intended recipients of the requirements are often not present in such workshops: the developers. Thus, they cannot benefit from the in-depth understanding of the requirements and of the rationales for these requirements that develops during the workshops. The simple handover of a requirements specification hardly compensates the rich requirements understanding that is needed for the development of an acceptable system. To compensate the lack of presence in a requirements workshop, we propose to record that requirements workshop on video. If workshop participants agree to be recorded, a video is relatively simple to create and is able to capture much more aspects about requirements and rationales than a specification document. This paper presents the workshop video technique and a phenomenological evaluation of its use for requirements communication from the perspective of software developers. The results show how the technique was appreciated by observers of the video, present positive and negative feedbacks from the observers, and lead to recommendations for implementing the technique in practice. FI-STAR