447,359 research outputs found

    Considerations about quality in model-driven engineering

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s11219-016-9350-6The virtue of quality is not itself a subject; it depends on a subject. In the software engineering field, quality means good software products that meet customer expectations, constraints, and requirements. Despite the numerous approaches, methods, descriptive models, and tools, that have been developed, a level of consensus has been reached by software practitioners. However, in the model-driven engineering (MDE) field, which has emerged from software engineering paradigms, quality continues to be a great challenge since the subject is not fully defined. The use of models alone is not enough to manage all of the quality issues at the modeling language level. In this work, we present the current state and some relevant considerations regarding quality in MDE, by identifying current categories in quality conception and by highlighting quality issues in real applications of the model-driven initiatives. We identified 16 categories in the definition of quality in MDE. From this identification, by applying an adaptive sampling approach, we discovered the five most influential authors for the works that propose definitions of quality. These include (in order): the OMG standards (e.g., MDA, UML, MOF, OCL, SysML), the ISO standards for software quality models (e.g., 9126 and 25,000), Krogstie, Lindland, and Moody. We also discovered families of works about quality, i.e., works that belong to the same author or topic. Seventy-three works were found with evidence of the mismatch between the academic/research field of quality evaluation of modeling languages and actual MDE practice in industry. We demonstrate that this field does not currently solve quality issues reported in industrial scenarios. The evidence of the mismatch was grouped in eight categories, four for academic/research evidence and four for industrial reports. These categories were detected based on the scope proposed in each one of the academic/research works and from the questions and issues raised by real practitioners. We then proposed a scenario to illustrate quality issues in a real information system project in which multiple modeling languages were used. For the evaluation of the quality of this MDE scenario, we chose one of the most cited and influential quality frameworks; it was detected from the information obtained in the identification of the categories about quality definition for MDE. We demonstrated that the selected framework falls short in addressing the quality issues. Finally, based on the findings, we derive eight challenges for quality evaluation in MDE projects that current quality initiatives do not address sufficiently.F.G, would like to thank COLCIENCIAS (Colombia) for funding this work through the Colciencias Grant call 512-2010. This work has been supported by the Gene-ralitat Valenciana Project IDEO (PROMETEOII/2014/039), the European Commission FP7 Project CaaS (611351), and ERDF structural funds.Giraldo-Velásquez, FD.; España Cubillo, S.; Pastor López, O.; Giraldo, WJ. (2016). Considerations about quality in model-driven engineering. Software Quality Journal. 1-66. https://doi.org/10.1007/s11219-016-9350-6S166(1985). Iso information processing—documentation symbols and conventions for data, program and system flowcharts, program network charts and system resources charts. ISO 5807:1985(E) (pp. 1–25).(2011). Iso/iec/ieee systems and software engineering – architecture description. 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    A plant-wide energy model for wastewater treatment plants: application to anaerobic membrane bioreactor technology

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    [EN] The aim of this study is to propose a detailed and comprehensive plant-wide model for assessing the energy demand of different wastewater treatment systems (beyond the traditional activated sludge) in both steady- and unsteady-state conditions. The proposed model makes it possible to calculate power and heat requirements (W and Q, respectively), and to recover both power and heat from methane and hydrogen capture. In order to account for the effect of biological processes on heat requirements, the model has been coupled to the extended version of the BNRM2 plant-wide mathematical model, which is implemented in DESSAS simulation software. Two case studies have been evaluated to assess the model's performance: (1) modelling the energy demand of two urban wastewater treatment plants based on conventional activated sludge and submerged anaerobic membrane bioreactor (AnMBR) technologies in steady-state conditions and (2) modelling the dynamics of reactor temperature and heat requirements in an AnMBR plant in unsteady-state conditions. The results indicate that the proposed model can be used to assess the energy performance of different wastewater treatment processes and would thus be useful, for example, WWTP design or upgrading or the development of new control strategies for energy savings.This research work has been supported by the Spanish Ministry of Science and Innovation [MICINN, Project CTM2011-28595-C02-01/02] jointly with the European Regional Development Fund (ERDF).Pretel-Jolis, R.; Robles Martínez, Á.; Ruano García, MV.; Seco, A.; Ferrer, J. (2016). A plant-wide energy model for wastewater treatment plants: application to anaerobic membrane bioreactor technology. Environmental Technology. 37(18):2298-2315. https://doi.org/10.1080/09593330.2016.1148903S229823153718Olsson, G., Carlsson, B., Comas, J., Copp, J., Gernaey, K. V., Ingildsen, P., … Åmand, L. (2014). Instrumentation, control and automation in wastewater – from London 1973 to Narbonne 2013. Water Science and Technology, 69(7), 1373-1385. doi:10.2166/wst.2014.057Nicolae, B., & George-Vlad, B. (2015). Life cycle analysis in refurbishment of the buildings as intervention practices in energy saving. Energy and Buildings, 86, 74-85. doi:10.1016/j.enbuild.2014.10.021Corominas, L., Foley, J., Guest, J. S., Hospido, A., Larsen, H. F., Morera, S., & Shaw, A. (2013). Life cycle assessment applied to wastewater treatment: State of the art. Water Research, 47(15), 5480-5492. doi:10.1016/j.watres.2013.06.049Bauer, A., Bösch, P., Friedl, A., & Amon, T. (2009). Analysis of methane potentials of steam-exploded wheat straw and estimation of energy yields of combined ethanol and methane production. Journal of Biotechnology, 142(1), 50-55. doi:10.1016/j.jbiotec.2009.01.017Venkatesh, G., & Elmi, R. A. (2013). Economic–environmental analysis of handling biogas from sewage sludge digesters in WWTPs (wastewater treatment plants) for energy recovery: Case study of Bekkelaget WWTP in Oslo (Norway). Energy, 58, 220-235. doi:10.1016/j.energy.2013.05.025EPA (Environmental Protection Agency). Combined Heat and Power Partnership. Agency of the United States federal government; 2015.Descoins, N., Deleris, S., Lestienne, R., Trouvé, E., & Maréchal, F. (2012). Energy efficiency in waste water treatments plants: Optimization of activated sludge process coupled with anaerobic digestion. Energy, 41(1), 153-164. doi:10.1016/j.energy.2011.03.078Gernaey, K. V., van Loosdrecht, M. C. ., Henze, M., Lind, M., & Jørgensen, S. B. (2004). Activated sludge wastewater treatment plant modelling and simulation: state of the art. Environmental Modelling & Software, 19(9), 763-783. doi:10.1016/j.envsoft.2003.03.005Ferrer, J., Seco, A., Serralta, J., Ribes, J., Manga, J., Asensi, E., … Llavador, F. (2008). DESASS: A software tool for designing, simulating and optimising WWTPs. Environmental Modelling & Software, 23(1), 19-26. doi:10.1016/j.envsoft.2007.04.005Bozkurt, H., Quaglia, A., Gernaey, K. V., & Sin, G. (2015). A mathematical programming framework for early stage design of wastewater treatment plants. Environmental Modelling & Software, 64, 164-176. doi:10.1016/j.envsoft.2014.11.023Jeppsson, U., Rosen, C., Alex, J., Copp, J., Gernaey, K. V., Pons, M.-N., & Vanrolleghem, P. A. (2006). Towards a benchmark simulation model for plant-wide control strategy performance evaluation of WWTPs. Water Science and Technology, 53(1), 287-295. doi:10.2166/wst.2006.031Gomez, J., de Gracia, M., Ayesa, E., & Garcia-Heras, J. L. (2007). Mathematical modelling of autothermal thermophilic aerobic digesters. Water Research, 41(5), 959-968. doi:10.1016/j.watres.2006.11.042Righi, S., Oliviero, L., Pedrini, M., Buscaroli, A., & Della Casa, C. (2013). Life Cycle Assessment of management systems for sewage sludge and food waste: centralized and decentralized approaches. Journal of Cleaner Production, 44, 8-17. doi:10.1016/j.jclepro.2012.12.004Lemos, D., Dias, A. C., Gabarrell, X., & Arroja, L. (2013). Environmental assessment of an urban water system. Journal of Cleaner Production, 54, 157-165. doi:10.1016/j.jclepro.2013.04.029Nowak, O., Enderle, P., & Varbanov, P. (2015). Ways to optimize the energy balance of municipal wastewater systems: lessons learned from Austrian applications. Journal of Cleaner Production, 88, 125-131. doi:10.1016/j.jclepro.2014.08.068Tous M, Ladislav B, Houdková L, Pavlas M, Stehlík P. Waste-to energy (W2E) software – a support tool for decision making process. Brno University of Technology, Institute of Process and Environmental Engineering, Chemical Engineering Transactions, Volume 18; 2009.Pijáková, I. (2015). Application of Dynamic Simulations for Assessment of Urban Wastewater Systems Operation. Chemical and Biochemical Engineering Quarterly Journal, 29(1), 55-62. doi:10.15255/cabeq.2014.2127McCarty, P. L., Bae, J., & Kim, J. (2011). Domestic Wastewater Treatment as a Net Energy Producer–Can This be Achieved? Environmental Science & Technology, 45(17), 7100-7106. doi:10.1021/es2014264Giménez, J. B., Robles, A., Carretero, L., Durán, F., Ruano, M. V., Gatti, M. N., … Seco, A. (2011). Experimental study of the anaerobic urban wastewater treatment in a submerged hollow-fibre membrane bioreactor at pilot scale. Bioresource Technology, 102(19), 8799-8806. doi:10.1016/j.biortech.2011.07.014Smith, A. L., Stadler, L. B., Cao, L., Love, N. G., Raskin, L., & Skerlos, S. J. (2014). 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    An Empirical Study of Cohesion and Coupling: Balancing Optimisation and Disruption

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    Search based software engineering has been extensively applied to the problem of finding improved modular structures that maximise cohesion and minimise coupling. However, there has, hitherto, been no longitudinal study of developers’ implementations, over a series of sequential releases. Moreover, results validating whether developers respect the fitness functions are scarce, and the potentially disruptive effect of search-based remodularisation is usually overlooked. We present an empirical study of 233 sequential releases of 10 different systems; the largest empirical study reported in the literature so far, and the first longitudinal study. Our results provide evidence that developers do, indeed, respect the fitness functions used to optimise cohesion/coupling (they are statistically significantly better than arbitrary choices with p << 0.01), yet they also leave considerable room for further improvement (cohesion/coupling can be improved by 25% on average). However, we also report that optimising the structure is highly disruptive (on average more than 57% of the structure must change), while our results reveal that developers tend to avoid such disruption. Therefore, we introduce and evaluate a multi-objective evolutionary approach that minimises disruption while maximising cohesion/coupling improvement. This allows developers to balance reticence to disrupt existing modular structure, against their competing need to improve cohesion and coupling. The multi-objective approach is able to find modular structures that improve the cohesion of developers’ implementations by 22.52%, while causing an acceptably low level of disruption (within that already tolerated by developers)
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