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Context: To reduce manual effort of extracting test cases from natural-language requirements, many approaches based on Natural Language Processing (NLP) have been proposed in the literature. Given the large amount of approaches in this area, and since many practitioners are eager to utilize such techniques, it is important to synthesize and provide an overview of the state-of-the-art in this area. Objective: Our objective is to summarize the state-of-the-art in NLP-assisted software testing which could benefit practitioners to potentially utilize those NLP-based techniques. Moreover, this can benefit researchers in providing an overview of the research landscape. Method: To address the above need, we conducted a survey in the form of a systematic literature mapping (classification). After compiling an initial pool of 95 papers, we conducted a systematic voting, and our final pool included 67 technical papers. Results: This review paper provides an overview of the contribution types presented in the papers, types of NLP approaches used to assist software testing, types of required input requirements, and a review of tool support in this area. Some key results we have detected are: (1) only four of the 38 tools (11%) presented in the papers are available for download; (2) a larger ratio of the papers (30 of 67) provided a shallow exposure to the NLP aspects (almost no details). Conclusion: This paper would benefit both practitioners and researchers by serving as an “index” to the body of knowledge in this area. The results could help practitioners utilizing the existing NLP-based techniques; this in turn reduces the cost of test-case design and decreases the amount of human resources spent on test activities. After sharing this review with some of our industrial collaborators, initial insights show that this review can indeed be useful and beneficial to practitioners. © 2020 Elsevier B.V., open access

Context: Continuous integration (CI) is a practice that aims to continuously verify quality aspects of a software intensive system both for functional and non-functional requirements (NFRs). Functional requirements are the inputs of development and can be tested in isolation, utilising either manual or automated tests. In contrast, some NFRs are difficult to test without functionality, for NFRs are often aspects of functionality and express quality aspects. Lacking this testability attribute makes NFR testing complicated and, therefore, underrepresented in industrial practice. However, the emergence of CI has radically affected software development and created new avenues for software quality evaluation and quality information acquisition. Research has, consequently, been devoted to the utilisation of this additional information for more efficient and effective NFR verification. Objective: We aim to identify the state-of-the-art of utilising the CI environment for NFR testing, hereinafter referred to as CI-NFR testing. Method: Through rigorous selection, from an initial set of 747 papers, we identified 47 papers that describe how NFRs are tested in a CI environment. Evidence-based analysis, through coding, is performed on the identified papers in this SLR. Results: Firstly, ten CI approaches are described by the papers selected, each describing different tools and nine different NFRs where reported to be tested. Secondly, although possible, CI-NFR testing is associated with eight challenges that adversely affect its adoption. Thirdly, the identified CI-NFR testing processes are tool-driven, but there is a lack of NFR testing tools that can be used in the CI environment. Finally, we proposed a CI framework for NFRs testing. Conclusion: A synthesised CI framework is proposed for testing various NFRs, and associated CI tools are also mapped. This contribution is valuable as results of the study also show that CI-NFR testing can help improve the quality of NFR testing i

Context: GUI-based testing is a sub-field of software testing research that has emerged in the last three decades. GUI-based testing techniques focus on verifying the functional conformance of the system under test (SUT) through its graphical user interface. However, despite the research domains growth, studies in the field have low reproducibility and comparability. One observed cause of these phenomena is identified as a lack of research rigor and commonly used metrics, including coverage metrics. Objective: We aim to identify the most commonly used metrics in the field and formulate a taxonomy of coverage metrics for GUI-based testing research. Method: We adopt an evidence-based approach to build the taxonomy through a systematic literature review of studies in the GUI-based testing domain. Identified papers are then analyzed with Open and Axial Coding techniques to identify hierarchical and mutually exclusive categories of metrics with common characteristics, usages, and applications. Results: Through the analysis of 169 papers and 315 metric definitions, we obtained a taxonomy with 55 codes (common names for metrics), 17 metric categories, and 4 higher level categories: Functional Level, GUI Level, Model Level and Code Level. We measure a higher number of mentions of Model and Code level metrics over Functional and GUI level metrics. Conclusions: We propose a taxonomy for use in future GUI-based testing research to improve the general quality of studies in the domain. In addition, the taxonomy is perceived to help enable more replication studies as well as macro-analysis of the current body of research. © 2022 Elsevier B.V.

In parallel to academic (peer-reviewed) literature (e.g., journal and conference papers), an enormous extent of grey literature (GL) has accumulated since the inception of software engineering (SE). GL is often defined as “literature that is not formally published in sources such as books or journal articles”, e.g., in the form of trade magazines, online blog-posts, technical reports, and online videos such as tutorial and presentation videos. GL is typically produced by SE practitioners. We have observed that researchers are increasingly using and benefitting from the knowledge available within GL. Related to the notion of GL is the notion of Multivocal Literature Reviews (MLRs) in SE, i.e., a MLR is a form of a Systematic Literature Review (SLR) which includes knowledge and/or evidence from the GL in addition to the peer-reviewed literature. MLRs are useful for both researchers and practitioners because they provide summaries of both the state-of-the-art and -practice in a given area. MLRs are popular in other fields and have started to appear in SE community. It is timely then for a Special Issue (SI) focusing on GL and MLRs in SE. From the pool of 13 submitted papers, and after following a rigorous peer review process, seven papers were accepted for this SI. In this introduction we provide a brief overview of GL and MLRs in SE, and then a brief summary of the seven papers published in this SI. © 2021

The relevance of context is particularly stressed in case studies, where it is said that “case study is an empirical method aimed at investigating contemporary phenomena in their context”. In this research, we classify context information and provide a context checklist for industrial software engineering. The checklist serves the purpose of (a) supporting researchers and practitioners in characterizing the context in which they are working; (b) supporting researchers with a checklist to identify relevant contextual information to elicit and report during primary and secondary studies. We utilized a systematic approach for constructing the classification of context information and provided a detailed definition for each item. We collected feedback from researchers as well as practitioners. The usefulness of the checklist was perceived more positively by researchers than practitioners, though they highlighted benefits (raising awareness of the importance of context and usefulness for management). The understandability was perceived positively by both practitioners and researchers. The checklist may serve as a “meta-model”, forming the basis for specific adaptations for different research areas, and as input for researchers deciding which context information to extract in systematic reviews. The checklist may also help researchers in reporting context in research papers. © 2021

Context: Continuous experimentation and A/B testing is an established industry practice that has been researched for more than 10 years. Our aim is to synthesize the conducted research. Objective: We wanted to find the core constituents of a framework for continuous experimentation and the solutions that are applied within the field. Finally, we were interested in the challenges and benefits reported of continuous experimentation. Methods: We applied forward snowballing on a known set of papers and identified a total of 128 relevant papers. Based on this set of papers we performed two qualitative narrative syntheses and a thematic synthesis to answer the research questions. Results: The framework constituents for continuous experimentation include experimentation processes as well as supportive technical and organizational infrastructure. The solutions found in the literature were synthesized to nine themes, e.g. experiment design, automated experiments, or metric specification. Concerning the challenges of continuous experimentation, the analysis identified cultural, organizational, business, technical, statistical, ethical, and domain-specific challenges. Further, the study concludes that the benefits of experimentation are mostly implicit in the studies. Conclusion: The research on continuous experimentation has yielded a large body of knowledge on experimentation. The synthesis of published research presented within include recommended infrastructure and experimentation process models, guidelines to mitigate the identified challenges, and what problems the various published solutions solve. © 2021 The Authors, open access

Context: Continuous experimentation and A/B testing is an established industry practice that has been researched for more than 10 years. Our aim is to synthesize the conducted research. Objective: We wanted to find the core constituents of a framework for continuous experimentation and the solutions that are applied within the field. Finally, we were interested in the challenges and benefits reported of continuous experimentation. Methods: We applied forward snowballing on a known set of papers and identified a total of 128 relevant papers. Based on this set of papers we performed two qualitative narrative syntheses and a thematic synthesis to answer the research questions. Results: The framework constituents for continuous experimentation include experimentation processes as well as supportive technical and organizational infrastructure. The solutions found in the literature were synthesized to nine themes, e.g. experiment design, automated experiments, or metric specification. Concerning the challenges of continuous experimentation, the analysis identified cultural, organizational, business, technical, statistical, ethical, and domain-specific challenges. Further, the study concludes that the benefits of experimentation are mostly implicit in the studies. Conclusion: The research on continuous experimentation has yielded a large body of knowledge on experimentation. The synthesis of published research presented within include recommended infrastructure and experimentation process models, guidelines to mitigate the identified challenges, and what problems the various published solutions solve. © 2021 The Authors, open access

Context: Continuous experimentation and A/B testing is an established industry practice that has been researched for more than 10 years. Our aim is to synthesize the conducted research. Objective: We wanted to find the core constituents of a framework for continuous experimentation and the solutions that are applied within the field. Finally, we were interested in the challenges and benefits reported of continuous experimentation. Methods: We applied forward snowballing on a known set of papers and identified a total of 128 relevant papers. Based on this set of papers we performed two qualitative narrative syntheses and a thematic synthesis to answer the research questions. Results: The framework constituents for continuous experimentation include experimentation processes as well as supportive technical and organizational infrastructure. The solutions found in the literature were synthesized to nine themes, e.g. experiment design, automated experiments, or metric specification. Concerning the challenges of continuous experimentation, the analysis identified cultural, organizational, business, technical, statistical, ethical, and domain-specific challenges. Further, the study concludes that the benefits of experimentation are mostly implicit in the studies. Conclusion: The research on continuous experimentation has yielded a large body of knowledge on experimentation. The synthesis of published research presented within include recommended infrastructure and experimentation process models, guidelines to mitigate the identified challenges, and what problems the various published solutions solve. © 2021 The Authors, open access

Context: Continuous experimentation and A/B testing is an established industry practice that has been researched for more than 10 years. Our aim is to synthesize the conducted research. Objective: We wanted to find the core constituents of a framework for continuous experimentation and the solutions that are applied within the field. Finally, we were interested in the challenges and benefits reported of continuous experimentation. Methods: We applied forward snowballing on a known set of papers and identified a total of 128 relevant papers. Based on this set of papers we performed two qualitative narrative syntheses and a thematic synthesis to answer the research questions. Results: The framework constituents for continuous experimentation include experimentation processes as well as supportive technical and organizational infrastructure. The solutions found in the literature were synthesized to nine themes, e.g. experiment design, automated experiments, or metric specification. Concerning the challenges of continuous experimentation, the analysis identified cultural, organizational, business, technical, statistical, ethical, and domain-specific challenges. Further, the study concludes that the benefits of experimentation are mostly implicit in the studies. Conclusion: The research on continuous experimentation has yielded a large body of knowledge on experimentation. The synthesis of published research presented within include recommended infrastructure and experimentation process models, guidelines to mitigate the identified challenges, and what problems the various published solutions solve. © 2021 The Authors, open access

Context: Continuous experimentation and A/B testing is an established industry practice that has been researched for more than 10 years. Our aim is to synthesize the conducted research. Objective: We wanted to find the core constituents of a framework for continuous experimentation and the solutions that are applied within the field. Finally, we were interested in the challenges and benefits reported of continuous experimentation. Methods: We applied forward snowballing on a known set of papers and identified a total of 128 relevant papers. Based on this set of papers we performed two qualitative narrative syntheses and a thematic synthesis to answer the research questions. Results: The framework constituents for continuous experimentation include experimentation processes as well as supportive technical and organizational infrastructure. The solutions found in the literature were synthesized to nine themes, e.g. experiment design, automated experiments, or metric specification. Concerning the challenges of continuous experimentation, the analysis identified cultural, organizational, business, technical, statistical, ethical, and domain-specific challenges. Further, the study concludes that the benefits of experimentation are mostly implicit in the studies. Conclusion: The research on continuous experimentation has yielded a large body of knowledge on experimentation. The synthesis of published research presented within include recommended infrastructure and experimentation process models, guidelines to mitigate the identified challenges, and what problems the various published solutions solve. © 2021 The Authors, open access

Context: Continuous experimentation and A/B testing is an established industry practice that has been researched for more than 10 years. Our aim is to synthesize the conducted research. Objective: We wanted to find the core constituents of a framework for continuous experimentation and the solutions that are applied within the field. Finally, we were interested in the challenges and benefits reported of continuous experimentation. Methods: We applied forward snowballing on a known set of papers and identified a total of 128 relevant papers. Based on this set of papers we performed two qualitative narrative syntheses and a thematic synthesis to answer the research questions. Results: The framework constituents for continuous experimentation include experimentation processes as well as supportive technical and organizational infrastructure. The solutions found in the literature were synthesized to nine themes, e.g. experiment design, automated experiments, or metric specification. Concerning the challenges of continuous experimentation, the analysis identified cultural, organizational, business, technical, statistical, ethical, and domain-specific challenges. Further, the study concludes that the benefits of experimentation are mostly implicit in the studies. Conclusion: The research on continuous experimentation has yielded a large body of knowledge on experimentation. The synthesis of published research presented within include recommended infrastructure and experimentation process models, guidelines to mitigate the identified challenges, and what problems the various published solutions solve. © 2021 The Authors, open access

Context: Systematic Literature Reviews (SLRs) have been adopted within Software Engineering (SE) for more than a decade to provide meaningful summaries of evidence on several topics. Many of these SLRs are now potentially not fully up-to-date, and there are no standard proposals on how to update SLRs in SE. Objective: The objective of this paper is to propose guidelines on how to best search for evidence when updating SLRs in SE, and to evaluate these guidelines using an SLR that was not employed during the formulation of the guidelines. Method: To propose our guidelines, we compare and discuss outcomes from applying different search strategies to identify primary studies in a published SLR, an SLR update, and two replications in the area of effort estimation. These guidelines are then evaluated using an SLR in the area of software ecosystems, its update and a replication. Results: The use of a single iteration forward snowballing with Google Scholar, and employing as a seed set the original SLR and its primary studies is the most cost-effective way to search for new evidence when updating SLRs. Furthermore, the importance of having more than one researcher involved in the selection of papers when applying the inclusion and exclusion criteria is highlighted through the results. Conclusions: Our proposed guidelines formulated based upon an effort estimation SLR, its update and two replications, were supported when using an SLR in the area of software ecosystems, its update and a replication. Therefore, we put forward that our guidelines ought to be adopted for updating SLRs in SE. © 2020, Open access

Context: Systematic Literature Reviews (SLRs) have been adopted within Software Engineering (SE) for more than a decade to provide meaningful summaries of evidence on several topics. Many of these SLRs are now potentially not fully up-to-date, and there are no standard proposals on how to update SLRs in SE. Objective: The objective of this paper is to propose guidelines on how to best search for evidence when updating SLRs in SE, and to evaluate these guidelines using an SLR that was not employed during the formulation of the guidelines. Method: To propose our guidelines, we compare and discuss outcomes from applying different search strategies to identify primary studies in a published SLR, an SLR update, and two replications in the area of effort estimation. These guidelines are then evaluated using an SLR in the area of software ecosystems, its update and a replication. Results: The use of a single iteration forward snowballing with Google Scholar, and employing as a seed set the original SLR and its primary studies is the most cost-effective way to search for new evidence when updating SLRs. Furthermore, the importance of having more than one researcher involved in the selection of papers when applying the inclusion and exclusion criteria is highlighted through the results. Conclusions: Our proposed guidelines formulated based upon an effort estimation SLR, its update and two replications, were supported when using an SLR in the area of software ecosystems, its update and a replication. Therefore, we put forward that our guidelines ought to be adopted for updating SLRs in SE. © 2020, Open access

Context: Systematic Literature Reviews (SLRs) have been adopted within Software Engineering (SE) for more than a decade to provide meaningful summaries of evidence on several topics. Many of these SLRs are now potentially not fully up-to-date, and there are no standard proposals on how to update SLRs in SE. Objective: The objective of this paper is to propose guidelines on how to best search for evidence when updating SLRs in SE, and to evaluate these guidelines using an SLR that was not employed during the formulation of the guidelines. Method: To propose our guidelines, we compare and discuss outcomes from applying different search strategies to identify primary studies in a published SLR, an SLR update, and two replications in the area of effort estimation. These guidelines are then evaluated using an SLR in the area of software ecosystems, its update and a replication. Results: The use of a single iteration forward snowballing with Google Scholar, and employing as a seed set the original SLR and its primary studies is the most cost-effective way to search for new evidence when updating SLRs. Furthermore, the importance of having more than one researcher involved in the selection of papers when applying the inclusion and exclusion criteria is highlighted through the results. Conclusions: Our proposed guidelines formulated based upon an effort estimation SLR, its update and two replications, were supported when using an SLR in the area of software ecosystems, its update and a replication. Therefore, we put forward that our guidelines ought to be adopted for updating SLRs in SE. © 2020, Open access

Context: Systematic Literature Reviews (SLRs) have been adopted within Software Engineering (SE) for more than a decade to provide meaningful summaries of evidence on several topics. Many of these SLRs are now potentially not fully up-to-date, and there are no standard proposals on how to update SLRs in SE. Objective: The objective of this paper is to propose guidelines on how to best search for evidence when updating SLRs in SE, and to evaluate these guidelines using an SLR that was not employed during the formulation of the guidelines. Method: To propose our guidelines, we compare and discuss outcomes from applying different search strategies to identify primary studies in a published SLR, an SLR update, and two replications in the area of effort estimation. These guidelines are then evaluated using an SLR in the area of software ecosystems, its update and a replication. Results: The use of a single iteration forward snowballing with Google Scholar, and employing as a seed set the original SLR and its primary studies is the most cost-effective way to search for new evidence when updating SLRs. Furthermore, the importance of having more than one researcher involved in the selection of papers when applying the inclusion and exclusion criteria is highlighted through the results. Conclusions: Our proposed guidelines formulated based upon an effort estimation SLR, its update and two replications, were supported when using an SLR in the area of software ecosystems, its update and a replication. Therefore, we put forward that our guidelines ought to be adopted for updating SLRs in SE. © 2020, Open access

Context: Systematic Literature Reviews (SLRs) have been adopted within Software Engineering (SE) for more than a decade to provide meaningful summaries of evidence on several topics. Many of these SLRs are now potentially not fully up-to-date, and there are no standard proposals on how to update SLRs in SE. Objective: The objective of this paper is to propose guidelines on how to best search for evidence when updating SLRs in SE, and to evaluate these guidelines using an SLR that was not employed during the formulation of the guidelines. Method: To propose our guidelines, we compare and discuss outcomes from applying different search strategies to identify primary studies in a published SLR, an SLR update, and two replications in the area of effort estimation. These guidelines are then evaluated using an SLR in the area of software ecosystems, its update and a replication. Results: The use of a single iteration forward snowballing with Google Scholar, and employing as a seed set the original SLR and its primary studies is the most cost-effective way to search for new evidence when updating SLRs. Furthermore, the importance of having more than one researcher involved in the selection of papers when applying the inclusion and exclusion criteria is highlighted through the results. Conclusions: Our proposed guidelines formulated based upon an effort estimation SLR, its update and two replications, were supported when using an SLR in the area of software ecosystems, its update and a replication. Therefore, we put forward that our guidelines ought to be adopted for updating SLRs in SE. © 2020, Open access

Context: Systematic Literature Reviews (SLRs) have been adopted within Software Engineering (SE) for more than a decade to provide meaningful summaries of evidence on several topics. Many of these SLRs are now potentially not fully up-to-date, and there are no standard proposals on how to update SLRs in SE. Objective: The objective of this paper is to propose guidelines on how to best search for evidence when updating SLRs in SE, and to evaluate these guidelines using an SLR that was not employed during the formulation of the guidelines. Method: To propose our guidelines, we compare and discuss outcomes from applying different search strategies to identify primary studies in a published SLR, an SLR update, and two replications in the area of effort estimation. These guidelines are then evaluated using an SLR in the area of software ecosystems, its update and a replication. Results: The use of a single iteration forward snowballing with Google Scholar, and employing as a seed set the original SLR and its primary studies is the most cost-effective way to search for new evidence when updating SLRs. Furthermore, the importance of having more than one researcher involved in the selection of papers when applying the inclusion and exclusion criteria is highlighted through the results. Conclusions: Our proposed guidelines formulated based upon an effort estimation SLR, its update and two replications, were supported when using an SLR in the area of software ecosystems, its update and a replication. Therefore, we put forward that our guidelines ought to be adopted for updating SLRs in SE. © 2020, Open access

Context: A Multivocal Literature Review (MLR) is a form of a Systematic Literature Review (SLR) which includes the grey literature (e.g., blog posts, videos and white papers) in addition to the published (formal) literature (e.g., journal and conference papers). MLRs are useful for both researchers and practitioners since they provide summaries both the state-of-the art and –practice in a given area. MLRs are popular in other fields and have recently started to appear in software engineering (SE). As more MLR studies are conducted and reported, it is important to have a set of guidelines to ensure high quality of MLR processes and their results. Objective: There are several guidelines to conduct SLR studies in SE. However, several phases of MLRs differ from those of traditional SLRs, for instance with respect to the search process and source quality assessment. Therefore, SLR guidelines are only partially useful for conducting MLR studies. Our goal in this paper is to present guidelines on how to conduct MLR studies in SE. Method: To develop the MLR guidelines, we benefit from several inputs: (1) existing SLR guidelines in SE, (2), a literature survey of MLR guidelines and experience papers in other fields, and (3) our own experiences in conducting several MLRs in SE. We took the popular SLR guidelines of Kitchenham and Charters as the baseline and extended/adopted them to conduct MLR studies in SE. All derived guidelines are discussed in the context of an already-published MLR in SE as the running example. Results: The resulting guidelines cover all phases of conducting and reporting MLRs in SE from the planning phase, over conducting the review to the final reporting of the review. In particular, we believe that incorporating and adopting a vast set of experience-based recommendations from MLR guidelines and experience papers in other fields have enabled us to propose a set of guidelines with solid foundations. Conclusion: Having been developed on the basis of sev

Context: A Multivocal Literature Review (MLR) is a form of a Systematic Literature Review (SLR) which includes the grey literature (e.g., blog posts, videos and white papers) in addition to the published (formal) literature (e.g., journal and conference papers). MLRs are useful for both researchers and practitioners since they provide summaries both the state-of-the art and –practice in a given area. MLRs are popular in other fields and have recently started to appear in software engineering (SE). As more MLR studies are conducted and reported, it is important to have a set of guidelines to ensure high quality of MLR processes and their results. Objective: There are several guidelines to conduct SLR studies in SE. However, several phases of MLRs differ from those of traditional SLRs, for instance with respect to the search process and source quality assessment. Therefore, SLR guidelines are only partially useful for conducting MLR studies. Our goal in this paper is to present guidelines on how to conduct MLR studies in SE. Method: To develop the MLR guidelines, we benefit from several inputs: (1) existing SLR guidelines in SE, (2), a literature survey of MLR guidelines and experience papers in other fields, and (3) our own experiences in conducting several MLRs in SE. We took the popular SLR guidelines of Kitchenham and Charters as the baseline and extended/adopted them to conduct MLR studies in SE. All derived guidelines are discussed in the context of an already-published MLR in SE as the running example. Results: The resulting guidelines cover all phases of conducting and reporting MLRs in SE from the planning phase, over conducting the review to the final reporting of the review. In particular, we believe that incorporating and adopting a vast set of experience-based recommendations from MLR guidelines and experience papers in other fields have enabled us to propose a set of guidelines with solid foundations. Conclusion: Having been developed on the basis of sev

Context: A Multivocal Literature Review (MLR) is a form of a Systematic Literature Review (SLR) which includes the grey literature (e.g., blog posts, videos and white papers) in addition to the published (formal) literature (e.g., journal and conference papers). MLRs are useful for both researchers and practitioners since they provide summaries both the state-of-the art and –practice in a given area. MLRs are popular in other fields and have recently started to appear in software engineering (SE). As more MLR studies are conducted and reported, it is important to have a set of guidelines to ensure high quality of MLR processes and their results. Objective: There are several guidelines to conduct SLR studies in SE. However, several phases of MLRs differ from those of traditional SLRs, for instance with respect to the search process and source quality assessment. Therefore, SLR guidelines are only partially useful for conducting MLR studies. Our goal in this paper is to present guidelines on how to conduct MLR studies in SE. Method: To develop the MLR guidelines, we benefit from several inputs: (1) existing SLR guidelines in SE, (2), a literature survey of MLR guidelines and experience papers in other fields, and (3) our own experiences in conducting several MLRs in SE. We took the popular SLR guidelines of Kitchenham and Charters as the baseline and extended/adopted them to conduct MLR studies in SE. All derived guidelines are discussed in the context of an already-published MLR in SE as the running example. Results: The resulting guidelines cover all phases of conducting and reporting MLRs in SE from the planning phase, over conducting the review to the final reporting of the review. In particular, we believe that incorporating and adopting a vast set of experience-based recommendations from MLR guidelines and experience papers in other fields have enabled us to propose a set of guidelines with solid foundations. Conclusion: Having been developed on the basis of sev

Context: A Multivocal Literature Review (MLR) is a form of a Systematic Literature Review (SLR) which includes the grey literature (e.g., blog posts, videos and white papers) in addition to the published (formal) literature (e.g., journal and conference papers). MLRs are useful for both researchers and practitioners since they provide summaries both the state-of-the art and –practice in a given area. MLRs are popular in other fields and have recently started to appear in software engineering (SE). As more MLR studies are conducted and reported, it is important to have a set of guidelines to ensure high quality of MLR processes and their results. Objective: There are several guidelines to conduct SLR studies in SE. However, several phases of MLRs differ from those of traditional SLRs, for instance with respect to the search process and source quality assessment. Therefore, SLR guidelines are only partially useful for conducting MLR studies. Our goal in this paper is to present guidelines on how to conduct MLR studies in SE. Method: To develop the MLR guidelines, we benefit from several inputs: (1) existing SLR guidelines in SE, (2), a literature survey of MLR guidelines and experience papers in other fields, and (3) our own experiences in conducting several MLRs in SE. We took the popular SLR guidelines of Kitchenham and Charters as the baseline and extended/adopted them to conduct MLR studies in SE. All derived guidelines are discussed in the context of an already-published MLR in SE as the running example. Results: The resulting guidelines cover all phases of conducting and reporting MLRs in SE from the planning phase, over conducting the review to the final reporting of the review. In particular, we believe that incorporating and adopting a vast set of experience-based recommendations from MLR guidelines and experience papers in other fields have enabled us to propose a set of guidelines with solid foundations. Conclusion: Having been developed on the basis of sev

Context: A Multivocal Literature Review (MLR) is a form of a Systematic Literature Review (SLR) which includes the grey literature (e.g., blog posts, videos and white papers) in addition to the published (formal) literature (e.g., journal and conference papers). MLRs are useful for both researchers and practitioners since they provide summaries both the state-of-the art and –practice in a given area. MLRs are popular in other fields and have recently started to appear in software engineering (SE). As more MLR studies are conducted and reported, it is important to have a set of guidelines to ensure high quality of MLR processes and their results. Objective: There are several guidelines to conduct SLR studies in SE. However, several phases of MLRs differ from those of traditional SLRs, for instance with respect to the search process and source quality assessment. Therefore, SLR guidelines are only partially useful for conducting MLR studies. Our goal in this paper is to present guidelines on how to conduct MLR studies in SE. Method: To develop the MLR guidelines, we benefit from several inputs: (1) existing SLR guidelines in SE, (2), a literature survey of MLR guidelines and experience papers in other fields, and (3) our own experiences in conducting several MLRs in SE. We took the popular SLR guidelines of Kitchenham and Charters as the baseline and extended/adopted them to conduct MLR studies in SE. All derived guidelines are discussed in the context of an already-published MLR in SE as the running example. Results: The resulting guidelines cover all phases of conducting and reporting MLRs in SE from the planning phase, over conducting the review to the final reporting of the review. In particular, we believe that incorporating and adopting a vast set of experience-based recommendations from MLR guidelines and experience papers in other fields have enabled us to propose a set of guidelines with solid foundations. Conclusion: Having been developed on the basis of sev

Context Empirical research in software engineering contributes towards developing scientific knowledge in this field, which in turn is relevant to inform decision-making in industry. A number of empirical studies have been carried out to date in software engineering, and the need for guidelines for conducting and evaluating such research has been stressed. Objective: The main goal of this mapping study is to identify and summarize the body of knowledge on research guidelines, assessment instruments and knowledge organization systems on how to conduct and evaluate empirical research in software engineering. Method: A systematic mapping study employing manual search and snowballing techniques was carried out to identify the suitable papers. To build up the catalog, we extracted and categorized information provided by the identified papers. Results: The mapping study comprises a list of 341 methodological papers, classified according to research methods, research phases covered, and type of instrument provided. Later, we derived a brief explanatory review of the instruments provided for each of the research methods. Conclusion: We provide: an aggregated body of knowledge on the state of the art relating to guidelines, assessment instruments and knowledge organization systems for carrying out empirical software engineering research; an exemplary usage scenario that can be used to guide those carrying out such studies is also provided. Finally, we discuss the catalog's implications for research practice and the needs for further research. © 2018 Elsevier B.V.

Context: A Multivocal Literature Review (MLR) is a form of a Systematic Literature Review (SLR) which includes the grey literature (e.g., blog posts, videos and white papers) in addition to the published (formal) literature (e.g., journal and conference papers). MLRs are useful for both researchers and practitioners since they provide summaries both the state-of-the art and –practice in a given area. MLRs are popular in other fields and have recently started to appear in software engineering (SE). As more MLR studies are conducted and reported, it is important to have a set of guidelines to ensure high quality of MLR processes and their results. Objective: There are several guidelines to conduct SLR studies in SE. However, several phases of MLRs differ from those of traditional SLRs, for instance with respect to the search process and source quality assessment. Therefore, SLR guidelines are only partially useful for conducting MLR studies. Our goal in this paper is to present guidelines on how to conduct MLR studies in SE. Method: To develop the MLR guidelines, we benefit from several inputs: (1) existing SLR guidelines in SE, (2), a literature survey of MLR guidelines and experience papers in other fields, and (3) our own experiences in conducting several MLRs in SE. We took the popular SLR guidelines of Kitchenham and Charters as the baseline and extended/adopted them to conduct MLR studies in SE. All derived guidelines are discussed in the context of an already-published MLR in SE as the running example. Results: The resulting guidelines cover all phases of conducting and reporting MLRs in SE from the planning phase, over conducting the review to the final reporting of the review. In particular, we believe that incorporating and adopting a vast set of experience-based recommendations from MLR guidelines and experience papers in other fields have enabled us to propose a set of guidelines with solid foundations. Conclusion: Having been developed on the basis of sev

Context: Methodological research on systematic literature reviews (SLRs)in Software Engineering (SE)has so far focused on developing and evaluating guidelines for conducting systematic reviews. However, the support for quality assessment of completed SLRs has not received the same level of attention. Objective: To raise awareness of the need for a critical appraisal tool (CAT)for assessing the quality of SLRs in SE. To initiate a community-based effort towards the development of such a tool. Method: We reviewed the literature on the quality assessment of SLRs to identify the frequently used CATs in SE and other fields. Results: We identified that the CATs currently used is SE were borrowed from medicine, but have not kept pace with substantial advancements in the field of medicine. Conclusion: In this paper, we have argued the need for a CAT for quality appraisal of SLRs in SE. We have also identified a tool that has the potential for application in SE. Furthermore, we have presented our approach for adapting this state-of-the-art CAT for assessing SLRs in SE. © 2019 The Authors, open access

Context: Methodological research on systematic literature reviews (SLRs)in Software Engineering (SE)has so far focused on developing and evaluating guidelines for conducting systematic reviews. However, the support for quality assessment of completed SLRs has not received the same level of attention. Objective: To raise awareness of the need for a critical appraisal tool (CAT)for assessing the quality of SLRs in SE. To initiate a community-based effort towards the development of such a tool. Method: We reviewed the literature on the quality assessment of SLRs to identify the frequently used CATs in SE and other fields. Results: We identified that the CATs currently used is SE were borrowed from medicine, but have not kept pace with substantial advancements in the field of medicine. Conclusion: In this paper, we have argued the need for a CAT for quality appraisal of SLRs in SE. We have also identified a tool that has the potential for application in SE. Furthermore, we have presented our approach for adapting this state-of-the-art CAT for assessing SLRs in SE. © 2019 The Authors, open access

Context: Methodological research on systematic literature reviews (SLRs)in Software Engineering (SE)has so far focused on developing and evaluating guidelines for conducting systematic reviews. However, the support for quality assessment of completed SLRs has not received the same level of attention. Objective: To raise awareness of the need for a critical appraisal tool (CAT)for assessing the quality of SLRs in SE. To initiate a community-based effort towards the development of such a tool. Method: We reviewed the literature on the quality assessment of SLRs to identify the frequently used CATs in SE and other fields. Results: We identified that the CATs currently used is SE were borrowed from medicine, but have not kept pace with substantial advancements in the field of medicine. Conclusion: In this paper, we have argued the need for a CAT for quality appraisal of SLRs in SE. We have also identified a tool that has the potential for application in SE. Furthermore, we have presented our approach for adapting this state-of-the-art CAT for assessing SLRs in SE. © 2019 The Authors, open access

Context: Methodological research on systematic literature reviews (SLRs)in Software Engineering (SE)has so far focused on developing and evaluating guidelines for conducting systematic reviews. However, the support for quality assessment of completed SLRs has not received the same level of attention. Objective: To raise awareness of the need for a critical appraisal tool (CAT)for assessing the quality of SLRs in SE. To initiate a community-based effort towards the development of such a tool. Method: We reviewed the literature on the quality assessment of SLRs to identify the frequently used CATs in SE and other fields. Results: We identified that the CATs currently used is SE were borrowed from medicine, but have not kept pace with substantial advancements in the field of medicine. Conclusion: In this paper, we have argued the need for a CAT for quality appraisal of SLRs in SE. We have also identified a tool that has the potential for application in SE. Furthermore, we have presented our approach for adapting this state-of-the-art CAT for assessing SLRs in SE. © 2019 The Authors, open access

Context: Methodological research on systematic literature reviews (SLRs)in Software Engineering (SE)has so far focused on developing and evaluating guidelines for conducting systematic reviews. However, the support for quality assessment of completed SLRs has not received the same level of attention. Objective: To raise awareness of the need for a critical appraisal tool (CAT)for assessing the quality of SLRs in SE. To initiate a community-based effort towards the development of such a tool. Method: We reviewed the literature on the quality assessment of SLRs to identify the frequently used CATs in SE and other fields. Results: We identified that the CATs currently used is SE were borrowed from medicine, but have not kept pace with substantial advancements in the field of medicine. Conclusion: In this paper, we have argued the need for a CAT for quality appraisal of SLRs in SE. We have also identified a tool that has the potential for application in SE. Furthermore, we have presented our approach for adapting this state-of-the-art CAT for assessing SLRs in SE. © 2019 The Authors, open access

Context: Methodological research on systematic literature reviews (SLRs)in Software Engineering (SE)has so far focused on developing and evaluating guidelines for conducting systematic reviews. However, the support for quality assessment of completed SLRs has not received the same level of attention. Objective: To raise awareness of the need for a critical appraisal tool (CAT)for assessing the quality of SLRs in SE. To initiate a community-based effort towards the development of such a tool. Method: We reviewed the literature on the quality assessment of SLRs to identify the frequently used CATs in SE and other fields. Results: We identified that the CATs currently used is SE were borrowed from medicine, but have not kept pace with substantial advancements in the field of medicine. Conclusion: In this paper, we have argued the need for a CAT for quality appraisal of SLRs in SE. We have also identified a tool that has the potential for application in SE. Furthermore, we have presented our approach for adapting this state-of-the-art CAT for assessing SLRs in SE. © 2019 The Authors, open access

Context: The principal focus of lean is the identification and elimination of waste from the process with respect to maximizing customer value. Similarly, the purpose of agile is to maximize customer value and minimize unnecessary work and time delays. In both cases the concept of waste is important. Through an empirical study, we explore how waste is approached in agile software development organizations. Objective: This paper explores the concept of waste in agile/lean software development organizations and how it is defined, used, prioritized, reduced, or eliminated in practice Method: The data were collected using semi-structured open-interviews. 23 practitioners from 14 embedded software development organizations were interviewed representing two core roles in each organization. Results: Various wastes, categorized in 10 different categories, were identified by the respondents. From the mentioned wastes, not all were necessarily waste per se but could be symptoms caused by wastes. From the seven wastes of lean, Task-switching was ranked as the most important, and Extra-features, as the least important wastes according to the respondents’ opinion. However, most companies do not have their own or use an established definition of waste, more importantly, very few actively identify or try to eliminate waste in their organizations beyond local initiatives on project level. Conclusion: In order to identify, recognize and eliminate waste, a common understanding, and a joint and holistic view of the concept is needed. It is also important to optimize the whole organization and the whole product, as waste on one level can be important on another, thus sub-optimization should be avoided. Furthermore, to achieve a sustainable and effective waste handling, both the short-term and the long-term perspectives need to be considered. © 2018 Elsevier B.V.

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.

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. © 2017 Elsevier B.V.

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. © 2017 Elsevier B.V.

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.

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.

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. © 2017 Elsevier B.V.

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.

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. © 2017 Elsevier B.V.

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.

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. © 2017 Elsevier B.V.

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.

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. © 2017 Elsevier B.V.

Together with Ericsson AB, we are using the design science framework when investigating how to create an intent-driven system for their business support system and its business studio. The aim is to present our initial results on how an extended OODA-loop can be used to realize a robust, but still flexible, software architecture for an intent-driven system. We explain how an extended OODA-loop is constructed and provide suggestions of how different part of it can be implemented. The initial results are promising but further research is needed to use the extended OODA-loop as reusable components in intent-driven systems. Our next step is to extend the generic methods with knowledge representation and reasoning capabilities. © 2019 The Author(s). Published by Elsevier B.V., open access

Together with Ericsson AB, we are using the design science framework when investigating how to create an intent-driven system for their business support system and its business studio. The aim is to present our initial results on how an extended OODA-loop can be used to realize a robust, but still flexible, software architecture for an intent-driven system. We explain how an extended OODA-loop is constructed and provide suggestions of how different part of it can be implemented. The initial results are promising but further research is needed to use the extended OODA-loop as reusable components in intent-driven systems. Our next step is to extend the generic methods with knowledge representation and reasoning capabilities. © 2019 The Author(s). Published by Elsevier B.V., open access

Together with Ericsson AB, we are using the design science framework when investigating how to create an intent-driven system for their business support system and its business studio. The aim is to present our initial results on how an extended OODA-loop can be used to realize a robust, but still flexible, software architecture for an intent-driven system. We explain how an extended OODA-loop is constructed and provide suggestions of how different part of it can be implemented. The initial results are promising but further research is needed to use the extended OODA-loop as reusable components in intent-driven systems. Our next step is to extend the generic methods with knowledge representation and reasoning capabilities. © 2019 The Author(s). Published by Elsevier B.V., open access

Together with Ericsson AB, we are using the design science framework when investigating how to create an intent-driven system for their business support system and its business studio. The aim is to present our initial results on how an extended OODA-loop can be used to realize a robust, but still flexible, software architecture for an intent-driven system. We explain how an extended OODA-loop is constructed and provide suggestions of how different part of it can be implemented. The initial results are promising but further research is needed to use the extended OODA-loop as reusable components in intent-driven systems. Our next step is to extend the generic methods with knowledge representation and reasoning capabilities. © 2019 The Author(s). Published by Elsevier B.V., open access

Together with Ericsson AB, we are using the design science framework when investigating how to create an intent-driven system for their business support system and its business studio. The aim is to present our initial results on how an extended OODA-loop can be used to realize a robust, but still flexible, software architecture for an intent-driven system. We explain how an extended OODA-loop is constructed and provide suggestions of how different part of it can be implemented. The initial results are promising but further research is needed to use the extended OODA-loop as reusable components in intent-driven systems. Our next step is to extend the generic methods with knowledge representation and reasoning capabilities. © 2019 The Author(s). Published by Elsevier B.V., open access

Together with Ericsson AB, we are using the design science framework when investigating how to create an intent-driven system for their business support system and its business studio. The aim is to present our initial results on how an extended OODA-loop can be used to realize a robust, but still flexible, software architecture for an intent-driven system. We explain how an extended OODA-loop is constructed and provide suggestions of how different part of it can be implemented. The initial results are promising but further research is needed to use the extended OODA-loop as reusable components in intent-driven systems. Our next step is to extend the generic methods with knowledge representation and reasoning capabilities. © 2019 The Author(s). Published by Elsevier B.V., open access

In many situations a decision maker (DM) would like to grade a component, or rank several components of the same type. Often a component type has many features, which are deemed as valuable by the DM. Other vital features are not known by the DM but are needed for the component to function. However, it should be possible to guide the DM to find the desired business solution, without putting a requirement of detailed knowledge of the component type on the DM. We propose a framework for component selection with the help of fuzzy decision making. The work is based on algorithms from fuzzy decision making, which we have adapted or extended. The framework was validated by practitioners, which found the framework useful. © 2018 The Author(s)., open access