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| 2. |
- Stanaway, Jeffrey D., et al.
(författare)
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Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: A systematic analysis for the Global Burden of Disease Study 2017
- 2018
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Ingår i: The Lancet. - 1474-547X .- 0140-6736. ; 392:10159, s. 1923-1994
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Tidskriftsartikel (refereegranskat)abstract
- Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk-outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk-outcome pairs, and new data on risk exposure levels and risk- outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017.
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| 3. |
- Abbafati, Cristiana, et al.
(författare)
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- 2020
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Tidskriftsartikel (refereegranskat)
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| 4. |
- Blincoe, Kelly, et al.
(författare)
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High-level software requirements and iteration changes : a predictive model
- 2019
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Ingår i: Empirical Software Engineering. - : Springer Science and Business Media LLC. - 1382-3256 .- 1573-7616. ; 24:3, s. 1610-1648
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Tidskriftsartikel (refereegranskat)abstract
- Knowing whether a software feature will be completed in its planned iteration can help with release planning decisions. However, existing research has focused on predictions of only low-level software tasks, like bug fixes. In this paper, we describe a mixed-method empirical study on three large IBM projects. We investigated the types of iteration changes that occur. We show that up to 54% of high-level requirements do not make their planned iteration. Requirements are most often pushed out to the next iteration, but high-level requirements are also commonly moved to the next minor or major release or returned to the product or release backlog. We developed and evaluated a model that uses machine learning to predict if a high-level requirement will be completed within its planned iteration. The model includes 29 features that were engineered based on prior work, interviews with IBM developers, and domain knowledge. Predictions were made at four different stages of the requirement lifetime. Our model is able to achieve up to 100% precision. We ranked the importance of our model features and found that some features are highly dependent on project and prediction stage. However, some features (e.g., the time remaining in the iteration and creator of the requirement) emerge as important across all projects and stages. We conclude with a discussion on future research directions.
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| 5. |
- Damian, Daniela, et al.
(författare)
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Challenges and Strategies for Managing Requirements Selection in Software Ecosystems
- 2021
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Ingår i: IEEE Software. - 0740-7459. ; 38:6, s. 76-87
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Tidskriftsartikel (refereegranskat)abstract
- In platform software ecosystems, organizations partner and innovate together. Success and innovation depend on managing complex sets of business relationships and stakeholders and using a requirements-selection process. We describe the associated challenges and strategies from the study of two large proprietary platform ecosystems.
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| 6. |
- Dehghan, Ali, et al.
(författare)
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Predicting likelihood of requirement implementation within the planned iteration : An empirical study at IBM
- 2017
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Ingår i: Proceedings - 2017 IEEE/ACM 14th International Conference on Mining Software Repositories, MSR 2017. - 9781538615447 ; , s. 124-134
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Konferensbidrag (refereegranskat)abstract
- There has been a significant interest in the estimation of time and effort in fixing defects among both software practitioners and researchers over the past two decades. However, most of the focus has been on prediction of time and effort in resolving bugs, without much regard to predicting time needed to complete high-level requirements, a critical step in release planning. In this paper, we describe a mixed-method empirical study on three large IBM projects in which we developed and evaluated a process of training a predictive model constituting a set of 29 features in nine categories in order to predict if a requirement will be completed within its planned iteration. We conducted feature engineering through iterative interviews with IBM practitioners as well as analysis of large development repositories of these three projects. Using machine learning techniques, we were able to make predictions on completion time of requirements at four different stages of their lifetime. Using our industrial partner's interest in high precision over recall, we then adopted a cost sensitive learning method and maximized precision of predictions (ranging from 0.8 to 0.97) while maintaining an acceptable recall. We also ranked the features based on their relative importance to the optimized predictive model. We show that although satisfying predictions can be made at early stages, performance of predictions improves over time by taking advantage of requirements' progress data. Furthermore, feature importance ranking results show that although importance of features are highly dependent on project and prediction stage, there are certain features (e.g. requirement creator, time remained to the end of iteration, time since last requirement summary change and number of times requirement has been replanned for a new iteration) that emerge as important across most projects and stages, implying future worthwhile research directions for both researchers and practitioners.
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| 7. |
- Knauss, Eric, 1977, et al.
(författare)
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Continuous Clarification and Emergent Requirements Flows in Open-Commercial Software Ecosystems
- 2018
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Ingår i: Requirements Engineering. - : Springer Science and Business Media LLC. - 0947-3602 .- 1432-010X. ; 23:1, s. 97-117
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Tidskriftsartikel (refereegranskat)abstract
- Software engineering practice has shifted from the development of products in closed environments towards more open and collaborative efforts. Software development has become significantly interdependent with other systems (e.g. services, apps) and typically takes place within large ecosystems of networked communities of stakeholder organizations. Such software ecosystems promise increased innovation power and support for consumer oriented software services at scale and are characterized by a certain openness of their information flows. While such openness supports project and reputation management, it also brings requirements engineering-related challenges within the ecosystem, such as managing dynamic, emergent contributions from the ecosystem stakeholders, as well as collecting their input while protecting their IP. In this paper we report from a study of requirements communication and management practices within IBM(R)'s Collaborative Lifecycle Management(R) product development ecosystem. Our research used multiple methods for data collection, including interviews within several ecosystem actors, on-site participatory observation, and analysis of online project repositories. We chart and describe the flow of product requirements information through the ecosystem, how the open communication paradigm in software ecosystems provides opportunities for 'just-in-time' RE - and which relies on emergent contributions from the ecosystem stakeholders-, as well as some of the challenges faced when traditional requirements engineering approaches are applied within such an ecosystem. More importantly, we discuss two tradeoffs brought about by the openness in software ecosystems: i) allowing open, transparent communication while keeping intellectual property confidential within the ecosystem, and ii) having the ability to act globally on a long-term strategy while empowering product teams to act locally to answer end-users' context specific needs in a timely manner. A sufficient level of openness facilitates contributions of emergent stakeholders. The ability to include important emergent contributors early in requirements elicitation appears to be a crucial asset in software ecosystems.
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| 8. |
- Knauss, Eric, 1977, et al.
(författare)
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Openness and Requirements: Opportunities and Tradeoffs in Software Ecosystems
- 2014
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Ingår i: Proceedings of 22nd International Requirements Engineering Conference (RE '14). - : IEEE. - 9781479930319 ; , s. 213 - 222
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Konferensbidrag (refereegranskat)abstract
- A growing number of software systems is characterized by continuous evolution as well as by significant interdependence with other systems (e.g. services, apps). Such software ecosystems promise increased innovation power and support for consumer oriented software services at scale, and are characterized by a certain openness of their information flows. While such openness supports project and reputation management, it also brings some challenges to Requirements Engineering (RE) within the ecosystem. We report from a mixed-method study of IBM®'s CLM® ecosystem that uses an open commercial development model. We analyzed data from from interviews within several ecosystem actors, participatory observation, and software repositories, to describe the flow of product requirements information through the ecosystem, how the open communication paradigm in software ecosystems provides opportunities for `just-in-time' RE, as well as some of the challenges faced when traditional requirements engineering approaches are applied within such an ecosystem. More importantly, we discuss two tradeoffs brought about the openness in software ecosystems: i) allowing open, transparent communication while keeping intellectual property confidential within the ecosystem, and ii) having the ability to act globally on a long-term strategy while empowering product teams to act locally to answer end-users' context specific needs in a timely manner.
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| 9. |
- Knauss, Eric, 1977, et al.
(författare)
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Patterns of Continuous Requirements Clarification
- 2014
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Ingår i: Requirements Engineering. - : Springer Science and Business Media LLC. - 0947-3602 .- 1432-010X. ; 20:4, s. 383-403
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Tidskriftsartikel (refereegranskat)abstract
- In software projects involving large and of- ten distributed teams, requirements evolve through the collaboration of many stakeholders, supported by online tools such as mailing lists, bug tracking systems, or online discussion forums. In this collaboration, requirements typically evolve from initial ideas, through clarification, to the implementation of a stable requirement. Deviations from this expected course might in- dicate requirements that are poorly understood, need further negotiation, or better alignment with project goals. If not addressed timely, such problems can surface late in the development cycle with negative consequences such as rework, missed schedules, or overrun budget. This paper presents an approach that provides project managers’ with timely awareness of such requirements-related risks, based on automatic analysis of stakeholders’ online requirements communication. We describe a clarification classifier that automatically analyzes requirements communication in a project and detects clarification events, a catalogue of clarification patterns, and a pattern matcher that suggests communication patterns based on our pattern catalogue. Our approach has been empirically constructed and evaluated in a case study in the IBM Rational Team Concert (RTC) project. We discuss the applicability of our approach in other projects as well as avenues for extending our pattern catalogue towards a theory of clarification patterns.
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| 10. |
- Linåker, Johan, et al.
(författare)
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A method for analyzing stakeholders’ influence on an open source software ecosystem’s requirements engineering process
- 2020
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Ingår i: Requirements Engineering. - : Springer Science and Business Media LLC. - 0947-3602 .- 1432-010X. ; 25:1, s. 115-130
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Tidskriftsartikel (refereegranskat)abstract
- For a firm in an open source software (OSS) ecosystem, the requirements engineering (RE) process is rather multifaceted. Apart from its typical RE process, there is a competing process, external to the firm and inherent to the firm’s ecosystem. When trying to impose an agenda in competition with other firms, and aiming to align internal product planning with the ecosystem’s RE process, firms need to consider who and how influential the other stakeholders are, and what their agendas are. The aim of the presented research is to help firms identify and analyze stakeholders in OSS ecosystems, in terms of their influence and interactions, to create awareness of their agendas, their collaborators, and how they invest their resources. To arrive at a solution artifact, we applied a design science research approach where we base artifact design on the literature and earlier work. A stakeholder influence analysis (SIA) method is proposed and demonstrated in terms of applicability and utility through a case study on the Apache Hadoop OSS ecosystem. SIA uses social network constructs to measure the stakeholders’ influence and interactions and considers the special characteristics of OSS RE to help firms structure their stakeholder analysis processes in relation to an OSS ecosystem. SIA adds a strategic aspect to the stakeholder analysis process by addressing the concepts of influence and interactions, which are important to consider while acting in collaborative and meritocratic RE cultures of OSS ecosystems.
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