| 1. |
- Usman, Muhammad, 1978-, et al.
(författare)
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Compliance Requirements in Large-Scale Software Development : An Industrial Case Study
- 2020
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Ingår i: Lecture Notes in Computer Science. - Cham : Springer-Verlag Tokyo Inc.. - 9783030641474 ; , s. 385-401
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Konferensbidrag (refereegranskat)abstract
- 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. © 2020, Springer Nature Switzerland AG.
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| 2. |
- Felderer, Michael, 1978-, et al.
(författare)
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The Evolution of Empirical Methods in Software Engineering
- 2020
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Ingår i: Contemporary Empirical Methods in Software Engineering. - Cham : Springer Nature. - 9783030324889 ; , s. 1-24
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Bokkapitel (refereegranskat)abstract
- Empirical methods like experimentation have become a powerful means to drive the field of software engineering by creating scientific evidence on software development, operation, and maintenance, but also by supporting practitioners in their decision-making and learning. Today empirical methods are fully applied in software engineering. However, they have developed in several iterations since the 1960s. In this chapter we tell the history of empirical software engineering and present the evolution of empirical methods in software engineering in five iterations, i.e., (1) mid-1960s to mid-1970s, (2) mid-1970s to mid-1980s, (3) mid-1980s to end of the 1990s, (4) the 2000s, and (5) the 2010s. We present the five iterations of the development of empirical software engineering mainly from a methodological perspective and additionally take key papers, venues, and books, which are covered in chronological order in a separate section on recommended further readings, into account. We complement our presentation of the evolution of empirical software engineering by presenting the current situation and an outlook in Sect. 4 and the available books on empirical software engineering. Furthermore, based on the chapters covered in this book we discuss trends on contemporary empirical methods in software engineering related to the plurality of research methods, human factors, data collection and processing, aggregation and synthesis of evidence, and impact of software engineering research.
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| 3. |
- Garousi, Vahid, et al.
(författare)
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Benefitting from the Grey Literature in Software Engineering Research
- 2020
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Ingår i: Contemporary Empirical Methods in Software Engineering. - Cham : Springer Nature. - 9783030324889 ; , s. 385-413
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Bokkapitel (refereegranskat)abstract
- Researchers generally place the most trust in peer-reviewed, published information, such as journals and conference papers. By contrast, software engineering (SE) practitioners typically do not have the time, access, or expertise to review and benefit from such publications. As a result, practitioners are more likely to turn to other sources of information that they trust, e.g., trade magazines, online blog posts, survey results, or technical reports, collectively referred to as grey literature (GL). Furthermore, practitioners also share their ideas and experiences as GL, which can serve as a valuable data source for research. While GL itself is not a new topic in SE, using, benefitting, and synthesizing knowledge from the GL in SE is a contemporary topic in empirical SE research and we are seeing that researchers are increasingly benefitting from the knowledge available within GL. The goal of this chapter is to provide an overview of GL in SE, together with insights on how SE researchers can effectively use and benefit from the knowledge and evidence available in the vast amount of GL.
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| 4. |
- Garousi, Vahid, et al.
(författare)
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Closing the Gap Between Software Engineering Education and Industrial Needs
- 2020
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Ingår i: IEEE Software. - : IEEE Computer Society. - 0740-7459 .- 1937-4194. ; 7:2, s. 68-77
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Tidskriftsartikel (refereegranskat)abstract
- According to different reports, many recent software engineering graduates often face difficulties when beginning their professional careers, due to misalignment of the skills learnt in their university education with what is needed in industry. To address that need, many studies have been conducted to align software engineering education with industry needs. To synthesize that body of knowledge, we present in this paper a systematic literature review (SLR) which summarizes the findings of 33 studies in this area. By doing a meta-analysis of all those studies and using data from 12 countries and over 4,000 data points, this study will enable educators and hiring managers to adapt their education / hiring efforts to best prepare the software engineering workforce. IEEE
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| 5. |
- Garousi, Vahid, et al.
(författare)
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Exploring the industry's challenges in software testing : An empirical study
- 2020
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Ingår i: Journal of Software. - : WILEY. - 2047-7473 .- 2047-7481. ; 32:8
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Tidskriftsartikel (refereegranskat)abstract
- Context Software testing is an important and costly software engineering activity in the industry. Despite the efforts of the software testing research community in the last several decades, various studies show that still many practitioners in the industry report challenges in their software testing tasks. Objective To shed light on industry's challenges in software testing, we characterize and synthesize the challenges reported by practitioners. Such concrete challenges can then be used for a variety of purposes, eg, research collaborations between industry and academia. Method Our empirical research method is opinion survey. By designing an online survey, we solicited practitioners' opinions about their challenges in different testing activities. Our dataset includes data from 72 practitioners from eight different countries. Results Our results show that test management and test automation are considered the most challenging among all testing activities by practitioners. Our results also include a set of 104 concrete challenges in software testing that may need further investigations by the research community. Conclusion We conclude that the focal points of industrial work and academic research in software testing differ. Furthermore, the paper at hand provides valuable insights concerning practitioners' "pain" points and, thus, provides researchers with a source of important research topics of high practical relevance.
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| 6. |
- Garousi, Vahid, et al.
(författare)
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NLP-assisted software testing : a systematic mapping of the literature
- 2020
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Ingår i: Information and Software Technology. - : Elsevier B.V.. - 0950-5849 .- 1873-6025. ; 126
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Forskningsöversikt (refereegranskat)abstract
- 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.
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| 7. |
- Grossmann, Juergen, et al.
(författare)
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A Taxonomy to Assess and Tailor Risk-Based Testing in Recent Testing Standards
- 2020
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Ingår i: IEEE Software. - : IEEE COMPUTER SOC. - 0740-7459 .- 1937-4194. ; 37:1, s. 40-49
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Tidskriftsartikel (refereegranskat)abstract
- This article provides a taxonomy for risk-based testing that serves as a tool to define, tailor, or assess such approaches. In this setting, the taxonomy is used to systematically identify deviations between the requirements from public standards and the individual testing approaches.
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| 8. |
- Lenz, Luca, et al.
(författare)
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Explainable Priority Assessment of Software-Defects using Categorical Features at SAP HANA
- 2020
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Ingår i: ACM International Conference Proceeding Series. - New York, NY, USA : Association for Computing Machinery. - 9781450377317 ; , s. 366-367
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Konferensbidrag (refereegranskat)abstract
- We want to automate priority assessment of software defects. To do so we provide a tool which uses an explainability-driven framework and classical machine learning algorithms to keep the decisions transparent. Differing from other approaches we only use objective and categorical fields from the bug tracking system as features. This makes our approach lightweight and extremely fast. We perform binary classification with priority labels corresponding to deadlines. Additionally, we evaluate the tool on real data to ensure good performance in the practical use case. © 2020 ACM.
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| 9. |
- Rainer, Austen W., et al.
(författare)
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Retrieving and mining professional experience of software practice from grey literature : An exploratory review
- 2020
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Ingår i: IET Software. - : John Wiley & Sons. - 1751-8806 .- 1751-8814. ; 14:6, s. 665-676
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Forskningsöversikt (refereegranskat)abstract
- Retrieving and mining practitioners' self-reports of their professional experience of software practice could provide valuable evidence for research. The authors are, however, unaware of any existing reviews of research conducted in this area. The authors reviewed and classified previous research, and identified insights into the challenges research confronts when retrieving and mining practitioners' self-reports of their experience of software practice. They conducted an exploratory review to identify and classify 42 studies. They analysed a selection of those studies for insights on challenges to mining professional experience. They identified only one directly relevant study. Even then this study concerns the software professional's emotional experiences rather than the professional's reporting of behaviour and events occurring during software practice. They discussed the challenges concerning: the prevalence of professional experience; definitions, models and theories; the sparseness of data; units of discourse analysis; annotator agreement; evaluation of the performance of algorithms; and the lack of replications. No directly relevant prior research appears to have been conducted in this area. They discussed the value of reporting negative results in secondary studies. There are a range of research opportunities but also considerable challenges. They formulated a set of guiding questions for further research in this area. © 2020 Institution of Engineering and Technology. All rights reserved.
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| 10. |
- Santoso, Ario, et al.
(författare)
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Specification-driven predictive business process monitoring
- 2020
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Ingår i: Software and Systems Modeling. - : Springer Verlag. - 1619-1366 .- 1619-1374. ; 19:6, s. 1307-1343
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Tidskriftsartikel (refereegranskat)abstract
- Predictive analysis in business process monitoring aims at forecasting the future information of a running business process. The prediction is typically made based on the model extracted from historical process execution logs (event logs). In practice, different business domains might require different kinds of predictions. Hence, it is important to have a means for properly specifying the desired prediction tasks, and a mechanism to deal with these various prediction tasks. Although there have been many studies in this area, they mostly focus on a specific prediction task. This work introduces a language for specifying the desired prediction tasks, and this language allows us to express various kinds of prediction tasks. This work also presents a mechanism for automatically creating the corresponding prediction model based on the given specification. Differently from previous studies, instead of focusing on a particular prediction task, we present an approach to deal with various prediction tasks based on the given specification of the desired prediction tasks. We also provide an implementation of the approach which is used to conduct experiments using real-life event logs. © 2019, The Author(s).
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