| 1. |
- Afzal, Wasif, et al.
(author)
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Genetic programming for cross-release fault count predictions in large and complex software projects
- 2010
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In: Evolutionary Computation and Optimization Algorithms in Software Engineering. - : IGI Global, Hershey, USA. - 9781615208098
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Book chapter (peer-reviewed)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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| 2. |
- Alahyari, Hiva, 1979, et al.
(author)
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A study of value in agile software development organizations
- 2017
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In: Journal of Systems and Software. - : Elsevier BV. - 0164-1212 .- 1873-1228. ; 125, s. 271-288
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Journal article (peer-reviewed)abstract
- The Agile manifesto focuses on the delivery of valuable software. In Lean, the principles emphasise value, where every activity that does not add value is seen as waste. Despite the strong focus on value, and that the primary critical success factor for software intensive product development lies in the value domain, no empirical study has investigated specifically what value is. This paper presents an empirical study that investigates how value is interpreted and prioritised, and how value is assured and measured. Data was collected through semi-structured interviews with 23 participants from 14 agile software development organisations. The contribution of this study is fourfold. First, it examines how value is perceived amongst agile software development organisations. Second, it compares the perceptions and priorities of the perceived values by domains and roles. Third, it includes an examination of what practices are used to achieve value in industry, and what hinders the achievement of value. Fourth, it characterises what measurements are used to assure, and evaluate value-creation activities. (C) 2016 Elsevier Inc. All rights reserved.
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| 3. |
- Alahyari, Hiva, 1979, et al.
(author)
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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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In: Information and Software Technology. - : Elsevier B.V.. - 0950-5849 .- 1873-6025. ; 107, s. 78-94
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Journal article (peer-reviewed)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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| 4. |
- Alégroth, Emil, 1984-, et al.
(author)
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Characteristics that affect Preference of Decision Models for Asset Selection : An Industrial Questionnaire Survey
- 2020
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In: Software quality journal. - : Springer. - 0963-9314 .- 1573-1367. ; 28:4, s. 1675-1707
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Journal article (peer-reviewed)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. |
- Alexandre, Rui Carlos Josino, et al.
(author)
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Cybersecurity Risk Assessment for Medium-Risk Drones : A Systematic Literature Review
- 2023
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In: 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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Research review (peer-reviewed)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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| 7. |
- Badampudi, Deepika, 1984-, et al.
(author)
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An Evaluation of Knowledge Translation in Software Engineering
- 2019
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In: International Symposium on Empirical Software Engineering and Measurement. - : IEEE Computer Society. - 9781728129686 ; , s. 13-18
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Conference paper (peer-reviewed)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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| 8. |
- Badampudi, Deepika, 1984-, et al.
(author)
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Contextualizing research evidence through knowledge translation in software engineering
- 2019
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In: 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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Conference paper (peer-reviewed)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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| 9. |
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| 10. |
- Bauer, Andreas, et al.
(author)
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Code review guidelines for GUI-based testing artifacts
- 2023
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In: Information and Software Technology. - : Elsevier. - 0950-5849 .- 1873-6025. ; 163
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Research review (peer-reviewed)abstract
- Context: Review of software artifacts, such as source or test code, is a common practice in industrial practice. However, although review guidelines are available for source and low-level test code, for GUI-based testing artifacts, such guidelines are missing. Objective: The goal of this work is to define a set of guidelines from literature about production and test code, that can be mapped to GUI-based testing artifacts. Method: A systematic literature review is conducted, using white and gray literature to identify guidelines for source and test code. These synthesized guidelines are then mapped, through examples, to create actionable, and applicable, guidelines for GUI-based testing artifacts. Results: The results of the study are 33 guidelines, summarized in nine guideline categories, that are successfully mapped as applicable to GUI-based testing artifacts. Of the collected literature, only 10 sources contained test-specific code review guidelines. These guideline categories are: perform automated checks, use checklists, provide context information, utilize metrics, ensure readability, visualize changes, reduce complexity, check conformity with the requirements and follow design principles and patterns. Conclusion: This pivotal set of guidelines provides an industrial contribution in filling the gap of general guidelines for review of GUI-based testing artifacts. Additionally, this work highlights, from an academic perspective, the need for future research in this area to also develop guidelines for other specific aspects of GUI-based testing practice, and to take into account other facets of the review process not covered by this work, such as reviewer selection. © 2023 The Author(s)
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