| 1. |
- Pernstal, J., et al.
(författare)
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FLEX-RCA: a lean-based method for root cause analysis in software process improvement
- 2019
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Ingår i: Software Quality Journal. - : Springer Science and Business Media LLC. - 1573-1367 .- 0963-9314. ; 27:1, s. 389-428
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Tidskriftsartikel (refereegranskat)abstract
- Software process improvement (SPI) is an instrument to increase the productivity of, and the quality of work, in software organizations. However, a majority of SPI frameworks are too extensive or provide guidance and potential improvement areas at a high level, indicating only the symptoms, not the causes. Motivated by the industrial need of two Swedish automotive companies to systematically uncover the underlying root causes of high-level improvement issues identified in an SPI project-assessing inter-departmental interactions in large-scale software systems development-this paper advances a root cause analysis (RCA) method building on Lean Six Sigma, called Flex-RCA. Flex-RCA is used to delve deeper into challenges identified to find root causes as a part of the evaluation and subsequent improvement activities. We also demonstrate and evaluate Flex-RCA's industrial applicability in a case study. An overall conclusion is that the use of Flex-RCA was successful, showing that it had the desired effect of both producing a broad base of causes on a high level and, more importantly, enabling an exploration of the underlying root causes.
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| 2. |
- Pernstål, Joakim, et al.
(författare)
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Communication Problems in Software Development : A Model and Its Industrial Application
- 2019
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Ingår i: International journal of software engineering and knowledge engineering. - : World Scientific Publishing Co. Pte Ltd. - 0218-1940. ; 29:10, s. 1497-1538
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Tidskriftsartikel (refereegranskat)abstract
- Attaining effective communication within and across organizational units is among the most critical challenges for success in software development organizations. This paper presents a novel model, supporting analysis of problems in inter-departmental communication events. The model was developed and designed based on industrial needs emphasizing flexibility, applicability and scalability. The model covers central communication aspects in order to provide a useful approximation of communication problems rather than in-depth modeling on message-by message basis. Other event-specific information, such as costs, can then be attached to enrich analysis and understanding. To exemplify and evaluate the model and collect feedback from industry, it was applied to 16 events at a Swedish automotive manufacturer where communication between two departments had broken down during development of software-intensive systems. The evaluation showed that the model helped structure and conduct systematic data collection and analysis of dysfunctional communication patterns. We found that insufficient understanding of the matters being communicated was prevalent, but also more specifically, requirements were insufficiently balanced, detailed and specified over the full system development cycle. Besides, the long-term cost for the company was analyzed in depth for each event, yielding a total estimated cost for the analyzed communication events of 11.2MUS$. © 2019 World Scientific Publishing Company.
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| 3. |
- Afzal, Wasif, et al.
(författare)
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Genetic programming for cross-release fault count predictions in large and complex software projects
- 2010
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Ingår i: Evolutionary Computation and Optimization Algorithms in Software Engineering. - : IGI Global, Hershey, USA. - 9781615208098
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Bokkapitel (refereegranskat)abstract
- Software fault prediction can play an important role in ensuring software quality through efficient resource allocation. This could, in turn, reduce the potentially high consequential costs due to faults. Predicting faults might be even more important with the emergence of short-timed and multiple software releases aimed at quick delivery of functionality. Previous research in software fault prediction has indicated that there is a need i) to improve the validity of results by having comparisons among number of data sets from a variety of software, ii) to use appropriate model evaluation measures and iii) to use statistical testing procedures. Moreover, cross-release prediction of faults has not yet achieved sufficient attention in the literature. In an attempt to address these concerns, this paper compares the quantitative and qualitative attributes of 7 traditional and machine-learning techniques for modeling the cross-release prediction of fault count data. The comparison is done using extensive data sets gathered from a total of 7 multi-release open-source and industrial software projects. These software projects together have several years of development and are from diverse application areas, ranging from a web browser to a robotic controller software. Our quantitative analysis suggests that genetic programming (GP) tends to have better consistency in terms of goodness of fit and accuracy across majority of data sets. It also has comparatively less model bias. Qualitatively, ease of configuration and complexity are less strong points for GP even though it shows generality and gives transparent models. Artificial neural networks did not perform as well as expected while linear regression gave average predictions in terms of goodness of fit and accuracy. Support vector machine regression and traditional software reliability growth models performed below average on most of the quantitative evaluation criteria while remained on average for most of the qualitative measures.
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| 4. |
- Alahyari, Hiva, 1979, et al.
(författare)
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An exploratory study of waste in software development organizations using agile or lean approaches : A multiple case study at 14 organizations
- 2019
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Ingår i: Information and Software Technology. - : Elsevier B.V.. - 0950-5849 .- 1873-6025. ; 107, s. 78-94
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 5. |
- Alégroth, Emil, 1984-, et al.
(författare)
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Characteristics that affect Preference of Decision Models for Asset Selection : An Industrial Questionnaire Survey
- 2020
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Ingår i: Software quality journal. - : Springer. - 0963-9314 .- 1573-1367. ; 28:4, s. 1675-1707
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Tidskriftsartikel (refereegranskat)abstract
- Modern software development relies on a combination of development and re-use of technical asset, e.g. software components, libraries and APIs.In the past, re-use was mostly conducted with internal assets but today external; open source, customer off-the-shelf (COTS) and assets developed through outsourcing are also common.This access to more asset alternatives presents new challenges regarding what assets to optimally chose and how to make this decision.To support decision-makers, decision-theory has been used to develop decision models for asset selection.However, very little industrial data has been presented in literature about the usefulness, or even perceived usefulness, of these models.Additionally, only limited information has been presented about what model characteristics that determine practitioner preference towards one model over another.Objective: The objective of this work is to evaluate what characteristics of decision models for asset selection that determine industrial practitioner preference of a model when given the choice of a decision-model of high precision or a model with high speed.Method: An industrial questionnaire survey is performed where a total of 33 practitioners, of varying roles, from 18 companies are tasked to compare two decision models for asset selection.Textual analysis and formal and descriptive statistics are then applied on the survey responses to answer the study's research questions.Results: The study shows that the practitioners had clear preference towards the decision model that emphasised speed over the one that emphasised decision precision.This conclusion was determined to be because one of the models was perceived faster, had lower complexity, had, was more flexible in use for different decisions, was more agile how it could be used in operation, its emphasis on people, its emphasis on ``good enough'' precision and ability to fail fast if a decision was a failure.Hence, seven characteristics that the practitioners considered important for their acceptance of the model.Conclusion: Industrial practitioner preference, which relates to acceptance, of decision models for asset selection is dependent on multiple characteristics that must be considered when developing a model for different types of decisions such as operational day-to-day decisions as well as more critical tactical or strategic decisions.The main contribution of this work are seven identified characteristics that can serve as industrial requirements for future research on decision models for asset selection.
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| 6. |
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| 7. |
- Alexandre, Rui Carlos Josino, et al.
(författare)
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Cybersecurity Risk Assessment for Medium-Risk Drones : A Systematic Literature Review
- 2023
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Ingår i: IEEE Aerospace and Electronic Systems Magazine. - : Institute of Electrical and Electronics Engineers (IEEE). - 0885-8985 .- 1557-959X. ; 38:6, s. 28-43
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Forskningsöversikt (refereegranskat)abstract
- The increased demand for Remotely Piloted Aircraft Systems (RPAS) in Beyond Visual Line-Of-Sight (BVLOS) operations gives rise to a set of concerns regarding cybersecurity that, if not addressed, can lead to the unsafe operation of RPASs. To assist the airworthiness evaluation that is performed by Civil Aviation Authorities (CAAs), we identified several processes that are used to evaluate the cybersecurity of RPAS. We conducted a Systematic Literature Review (SLR) by selecting 30 papers (out of 211 screened) that were published during the past five years. The results of our SLR indicate the importance of cybersecurity to the safe operation of RPAS. It is evident that there is a lack of a systematic process to enable a cybersecurity review of RPAS. We observe that common cyber threats to RPAS are related to jamming, spoofing, and DOS/DDOS (Denial of Service/Distributed Denial of Service). Processes relevant to the assessment of RPAS cybersecurity exist, however they differ in safety concerns from our perspective. In addition, with only one exception, the methods have not been used, and/or the use has not been reported as pertaining to industrial application. The most frequently cited vulnerabilities are those related to GPS and datalinks.
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| 8. |
- Badampudi, Deepika, 1984-, et al.
(författare)
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An Evaluation of Knowledge Translation in Software Engineering
- 2019
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Ingår i: International Symposium on Empirical Software Engineering and Measurement. - : IEEE Computer Society. - 9781728129686 ; , s. 13-18
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Konferensbidrag (refereegranskat)abstract
- Knowledge translation is defined, in health sciences, as 'the exchange, synthesis and ethically sound application of research results in practice'. The objective of this paper is to implement and conduct a feasibility evaluation of a knowledge translation framework in software engineering. We evaluated the outcome of the knowledge translation framework in an industrial setting, along with the effectiveness of the interventions undertaken as part of knowledge translation in a multi-case study. The results of the evaluation suggest that the practitioners perceive the knowledge translation framework to be valuable and useful. In conclusion, this paper contributes towards the reporting of a systematic implementation of knowledge translation and evaluating its use in software engineering. © 2019 IEEE.
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| 9. |
- Badampudi, Deepika, 1984-, et al.
(författare)
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Contextualizing research evidence through knowledge translation in software engineering
- 2019
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Ingår i: PROCEEDINGS OF EASE 2019 - EVALUATION AND ASSESSMENT IN SOFTWARE ENGINEERING. - New York, NY, USA : Association for Computing Machinery. - 9781450371452 ; , s. 306-311
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Konferensbidrag (refereegranskat)abstract
- Usage of software engineering research in industrial practice is a well-known challenge. Synthesis of knowledge from multiple research studies is needed to provide evidence-based decision-support for industry. The objective of this paper is to present a vision of how a knowledge translation framework may look like in software engineering research, in particular how to translate research evidence into practice by combining contextualized expert opinions with research evidence. We adopted the framework of knowledge translation from health care research, adapted and combined it with a Bayesian synthesis method. The framework provided in this paper includes a description of each step of knowledge translation in software engineering. Knowledge translation using Bayesian synthesis intends to provide a systematic approach towards contextualized, collaborative and consensus-driven application of research results. In conclusion, this paper contributes towards the application of knowledge translation in software engineering through the presented framework. © 2019 Association for Computing Machinery.
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