Using Bayesian networks to estimate strategic indicators in the context of rapid software development

Background: During Rapid Software Development, a large amount of project and development data can be collected from different and heterogeneous data sources. Aims: Design a methodology to process these data and turn it into relevant strategic indicators to help companies make meaningful decisions. Method: We adapt an existing methodology to create and estimate strategic indicators using Bayesian Networks in the context of Rapid Software Development, and applied it to a use case. Results: Applying the methodology in the use case, we create a model to predict product quality based on software factors and metrics, using companies’ business knowledge and collected data. Conclusions: We proved the methodology’s feasibility and obtained positive feedback from the company’s use case.Postprint (author's final draft

Q-Rapids: Quality-Aware Rapid Software Development: an H2020 Project

This work reports the objectives, current state, and outcomes of the Q-Rapids H2020 project. Q-Rapids (Quality-Aware Rapid Software Development) proposes a data-driven approach to the production of software following very short development cycles. The focus of Q-Rapids is on quality aspects, represented through quality requirements. The Q-Rapids platform, which is the tangible software asset emerging from the project, mines software repositories and usage logs to identify candidate quality requirements that may ameliorate the values of strategic indicators like product quality, time to market or team productivity. Four companies are providing use cases to evaluate the platform and associated processes.Peer ReviewedPostprint (author's final draft

Definition of the on-time delivery indicator in rapid software development

Rapid software development (RSD) is an approach for developing software in rapid iterations. One of the critical success factors of an RSD project is to deliver the product releases on time and with the planned features. In this paper, we elaborate an exploratory definition of the On-Time Delivery strategic indicator in RSD based on the literature and interviews with four companies. This indicator supports decision-makers to detect development problems in order to avoid delays and to estimate the additional time needed when requirements, and specifically quality requirements, are considered.Peer ReviewedPostprint (author's final draft

Recommendation domains for pond aquaculture

This publication introduces the methods and results of a research project that has developed a set of decision-support tools to identify places and sets of conditions for which a particular target aquaculture technology is considered feasible and therefore good to promote. The tools also identify the nature of constraints to aquaculture development and thereby shed light on appropriate interventions to realize the potential of the target areas. The project results will be useful for policy planners and decision makers in national, regional and local governments and development funding agencies, aquaculture extension workers in regional and local governments, and researchers in aquaculture systems and rural livelihoods. (Document contains 40 pages

Airline Catering Supply Chain Performance during Pandemic Disruption: A Bayesian Network Modelling Approach

The supply chain (SC) encompasses all actions related to meeting customer requests and transferring materials upstream to meet those demands. Organisations must operate towards increasing SC efficiency and effectiveness to meet SC objectives. Although most businesses expected the COVID-19 pandemic to severely negatively impact their SCs, they did not know how to model disruptions or their effects on performance in the event of a pandemic, leading to delayed responses, an incomplete understanding of the pandemic’s effects and late deployment of recovery measures. This paper presents a method for modelling and quantifying SC performance assessment for airline catering. In the COVID-19 context, the researchers proposed a Bayesian network (BN) model to measure SC performance and risk events and quantify the consequences of pandemic disruptions. The research simulates and measures the impact of different triggers on SC performance and business continuity using forward and backward propagation analysis, among other BN features, enabling us to combine various SC perspectives and explicitly account for pandemic scenarios. This study’s findings offer a fresh theoretical perspective on the use of BNs in pandemic SC disruption modelling. The findings can be used as a decision-making tool to predict and better understand how pandemics affect SC performance.Airline Catering Supply Chain Performance during Pandemic Disruption: A Bayesian Network Modelling ApproachacceptedVersio

Recommendation domains for pond aquaculture

This publication introduces the methods and results of a research project that has developed a set of decision-support tools to identify places and sets of conditions for which a particular target aquaculture technology is considered feasible and therefore good to promote. The tools also identify the nature of constraints to aquaculture development and thereby shed light on appropriate interventions to realize the potential of the target areas. The project results will be useful for policy planners and decision makers in national, regional and local governments and development funding agencies, aquaculture extension workers in regional and local governments, and researchers in aquaculture systems and rural livelihoods.Pond culture, Freshwater aquaculture, GIS

Predicting water quality and ecological responses

Abstract Changes to climate are predicted to have effects on freshwater streams. Stream flows are likely to change, with implications for freshwater ecosystems and water quality. Other stressors such as population growth, community preferences and management policies can be expected to interact in various ways with climate change and stream flows, and outcomes for freshwater ecosystems and water quality are uncertain. Managers of freshwater ecosystems and water supplies could benefit from being able to predict the scales of likely changes. This project has developed and applied a linked modelling framework to assess climate change impacts on water quality regimes and ecological responses. The framework is designed to inform water planning and climate adaptation activities. It integrates quantitative tools, and predicts relationships between future climate, human activities, water quality and ecology, thereby filling a gap left by the considerable research effort so far invested in predicting stream flows. The modelling framework allows managers to explore potential changes in the water quality and ecology of freshwater systems in response to plausible scenarios for climate change and management adaptations. Although set up for the Upper Murrumbidgee River catchment in southern NSW and ACT, the framework was planned to be transferable to other regions where suitable data are available. The approach and learning from the project appear to have the potential to be broadly applicable. We selected six climate scenarios representing minor, moderate and major changes in flow characteristics for 1oC and 2oC temperature increases. These were combined with four plausible alternative management adaptations that might be used to modify water supply, urban water demand and stream flow regimes in the Upper Murrumbidgee catchment. The Bayesian Network (BN) model structure we used was developed using both a ‘top down’ and ‘bottom up’ approach. From analyses combined with expert advice, we identified the causal structure linking climate variables to stream flow, water quality attributes, land management and ecological responses (top down). The ‘bottom up’ approach focused on key ecological outcomes and key drivers, and helped produce efficient models. The result was six models for macroinvertebrates, and one for fish. In the macroinvertebrate BN models, nodes were discretised using statistical/empirical derived thresholds using new techniques. The framework made it possible to explore how ecological communities respond to changes in climate and management activities. Particularly, we focused on the effects of water quality and quantity on ecological responses. The models showed a strong regional response reflecting differences across 18 regions in the catchment. In two regions the management alternatives were predicted to have stronger effects than climate change. In three other regions the predicted response to climate change was stronger. Analyses of water quality suggested minor changes in the probability of water quality exceeding thresholds designed to protect aquatic ecosystems. The ‘bottom up’ approach limited the framework’s transferability by being specific to the Upper Murrumbidgee catchment data. Indeed, to meet stakeholder questions models need to be specifically tailored. Therefore the report proposes a general model-building framework for transferring the approach, rather than the models, to other regions.  Please cite this report as: Dyer, F, El Sawah, S, Lucena-Moya, P, Harrison, E, Croke, B, Tschierschke, A, Griffiths, R, Brawata, R, Kath, J, Reynoldson, T, Jakeman, T 2013 Predicting water quality and ecological responses, National Climate Change Adaptation Research Facility, Gold Coast, pp. 110 Changes to climate are predicted to have effects on freshwater streams. Stream flows are likely to change, with implications for freshwater ecosystems and water quality. Other stressors such as population growth, community preferences and management policies can be expected to interact in various ways with climate change and stream flows, and outcomes for freshwater ecosystems and water quality are uncertain. Managers of freshwater ecosystems and water supplies could benefit from being able to predict the scales of likely changes. This project has developed and applied a linked modelling framework to assess climate change impacts on water quality regimes and ecological responses. The framework is designed to inform water planning and climate adaptation activities. It integrates quantitative tools, and predicts relationships between future climate, human activities, water quality and ecology, thereby filling a gap left by the considerable research effort so far invested in predicting stream flows. The modelling framework allows managers to explore potential changes in the water quality and ecology of freshwater systems in response to plausible scenarios for climate change and management adaptations. Although set up for the Upper Murrumbidgee River catchment in southern NSW and ACT, the framework was planned to be transferable to other regions where suitable data are available. The approach and learning from the project appear to have the potential to be broadly applicable. We selected six climate scenarios representing minor, moderate and major changes in flow characteristics for 1oC and 2oC temperature increases. These were combined with four plausible alternative management adaptations that might be used to modify water supply, urban water demand and stream flow regimes in the Upper Murrumbidgee catchment. The Bayesian Network (BN) model structure we used was developed using both a ‘top down’ and ‘bottom up’ approach. From analyses combined with expert advice, we identified the causal structure linking climate variables to stream flow, water quality attributes, land management and ecological responses (top down). The ‘bottom up’ approach focused on key ecological outcomes and key drivers, and helped produce efficient models. The result was six models for macroinvertebrates, and one for fish. In the macroinvertebrate BN models, nodes were discretised using statistical/empirical derived thresholds using new techniques. The framework made it possible to explore how ecological communities respond to changes in climate and management activities. Particularly, we focused on the effects of water quality and quantity on ecological responses. The models showed a strong regional response reflecting differences across 18 regions in the catchment. In two regions the management alternatives were predicted to have stronger effects than climate change. In three other regions the predicted response to climate change was stronger. Analyses of water quality suggested minor changes in the probability of water quality exceeding thresholds designed to protect aquatic ecosystems. The ‘bottom up’ approach limited the framework’s transferability by being specific to the Upper Murrumbidgee catchment data. Indeed, to meet stakeholder questions models need to be specifically tailored. Therefore the report proposes a general model-building framework for transferring the approach, rather than the models, to other regions.&nbsp