Software development effort estimation using function points and simpler functional measures: a comparison

Background-Functional Size Measures are widely used for estimating the development effort of software. After the introduction of Function Points, a few "simplified"measures have been proposed, aiming to make measurement simpler and quicker, but also to make measures applicable when fully detailed software specifications are not yet available. It has been shown that, in general, software size measures expressed in Function Points do not support more accurate effort estimation with respect to simplified measures. Objective-Many practitioners believe that when considering "complex"projects, i.e., project that involve many complex transactions and data, traditional Function Points measures support more accurate estimates than simpler functional size measures that do not account for greater-Then-Average complexity. In this paper, we aim to produce evidence that confirms or disproves such belief. Method-Based on a dataset that contains both effort and size data, an empirical study is performed, to provide some evidence concerning the relations that link functional size (measured in different ways) and development effort. Results-Our analysis shows that there is no statistically significant evidence that Function Points are generally better at estimating more complex projects than simpler measures. Function Points appeared better in some specific conditions, but in those conditions they also performed worse than simpler measures when dealing with less complex projects. Conclusions-Traditional Function Points do not seem to effectively account for software complexity. To improve effort estimation, researchers should probably dedicate their effort to devise a way of measuring software complexity that can be used in effort models together with (traditional or simplified) functional size measures

COVID-19 and Biomedical Experts: When Epistemic Authority is (Probably) Not Enough

This critical essay evaluates the potential integration of distinct kinds of expertise in policymaking, especially during situations of critical emergencies, such as the COVID-19 pandemic. This article relies on two case studies: (i) herd immunity (UK) and (ii) restricted access to ventilators for disabled people (USA). These case studies are discussed as examples of experts’ recommendations that have not been widely accepted, though they were made within the boundaries of expert epistemic authority. While the fundamental contribution of biomedical experts in devising public health policies during the COVID-19 pandemic is fully recognized, this paper intends to discuss potential issues and limitations that may arise when adopting a strict expert-based approach. By drawing attention to the interests of minorities (disenfranchized and underrepresented groups), the paper also claims a broader notion of “relevant expertise.” This critical essay thus calls for the necessity of wider inclusiveness and representativeness in the process underlying public health policymaking

Estimating functional size of software with confidence intervals

In many projects, software functional size is measured via the IFPUG (International Function Point Users Group) Function Point Analysis method. However, applying Function Point Analysis using the IFPUG process is possible only when functional user requirements are known completely and in detail. To solve this problem, several early estimation methods have been proposed and have become de facto standard processes. Among these, a prominent one is the ‘NESMA (Netherlands Software Metrics Association) estimated’ (also known as High-level Function Point Analysis) method. The NESMA estimated method simplifies the measurement by assigning fixed weights to Base Functional Components, instead of determining the weights via the detailed analysis of data and transactions. This makes the process faster and cheaper, and applicable when some details concerning data and transactions are not yet known. The accuracy of the mentioned method has been evaluated, also via large-scale empirical studies, showing that the yielded approximate measures are sufficiently accurate for practical usage. However, a limitation of the method is that it provides a specific size estimate, while other methods can provide confidence intervals, i.e., they indicate with a given confidence level that the size to be estimated is in a range. In this paper, we aim to enhance the NESMA estimated method with the possibility of computing a confidence interval. To this end, we carry out an empirical study, using data from real-life projects. The proposed approach appears effective. We expect that the possibility to estimate that the size of an application is in a range will help project managers deal with the risks connected with inevitable estimation errors

Using locally weighted regression to estimate the functional size of software: a preliminary study

In software engineering, measuring software functional size via the IFPUG (International Function Point Users Group) Function Point Analysis using the standard manual process can be a long and expensive activity. To solve this problem, several early estimation methods have been proposed and have become de facto standard processes. Among these, a prominent one is High-level Function Point Analysis. Recently, the Simple Function Point method has been released by IFPUG; although it is a proper measurement method, it has a great level of convertibility to traditional Function Points and may be used as an estimation method. Both High-level Function Point Analysis and Simple Function Point skip the difficult and time-consuming activities needed to weight data and transaction functions. This makes the process faster and cheaper, but yields approximate measures. The accuracy of the mentioned method has been evaluated, also via large-scale empirical studies, showing that the yielded approximate measures are sufficiently accurate for practical usage. In this paper, locally weighted regression is applied to the problem outlined above. This empirical study shows that estimates obtained via locally weighted regression are more accurate than those obtained via High-level Function Point Analysis, but are not substantially better than those yielded by alternative estimation methods using linear regression. The Simple Function Point method appears to yield measures that are well correlated with those obtained via standard measurement. In conclusion, locally weighted regression appears to be effective and accurate enough for estimating software functional size

Humoral immune response to different routes of myxomatosis vaccine application

[EN] The aim of our study was to monitor the dynamics of the serological response to different application routes of live attenuated myxomatosis vaccine. The study included 42 Californian breed rabbits, aged 3 mo, of both sexes. They were separated into 7 groups: 6 experimental and 1 control. All experimental groups were vaccinated on day 0 with a single dose of myxomatosis vaccine (min 103.3 tissue culture infective dose 50 [TCID50], max 105.8 TCID50). Three of the groups were injected with monovalent attenuated myxomatosis vaccine using different types of application: intradermal (i.d.), intramuscular (i.m.) and subcutaneous (s.c.). The other 3 groups were injected with bivalent attenuated vaccine against myxomatosis and rabbit haemorrhagic disease; again the routes of administration were i.d., i.m. and s.c.. There were no clinical signs or serious side effects after vaccination. The serological response was evaluated on days 7, 15 and 30 with a monoclonal antibody based-competition enzyme-linked immunosorbent assay (cELISA). More rapid and potent humoral response was detected in groups with i.d. inoculation in comparison to i.m. and s.c. routes. Vaccination with monovalent vaccine against myxomatosis induced higher antibody titre in comparison to bivalent vaccine. Our study showed that the vaccine application route and the type of vaccine used influence the speed and intensity of antibody response.Manev, I.; Genova, K.; Lavazza, A.; Capucci, L. (2018). Humoral immune response to different routes of myxomatosis vaccine application. World Rabbit Science. 26(2):149-154. doi:10.4995/wrs.2018.7021SWORD149154262Alfonso M., Pagès-Manté A. 2003. Serological response to Myxomatosis vaccination by different inoculation systems on farm rabbits. World Rabbit Sci. 2003, 11: 145-156. https://doi.org/10.4995/wrs.2003.504Barcena J., Morales M., Vázquez B., Boga J., Parra F., Lucientes J., Pagès-Manté A., Sánchez-Vizcaino J., Blasco R., Torres J. 2000. Horizontal Transmissible Protection against Myxomatosis and Rabbit Hemorrhagic Disease by Using a Recombinant Myxoma Virus. J. Virol., 74, 1114-1123.Bertagnoli S., Gelfi J., Gall G., Boilletot E., Vautherot J., Rasschaert D., Laurent S., Petit F., Boucraut-Baralon C., Milon A. 1996. Protection against myxomatosis and rabbit viral hemorrhagic disease with recombinant myxoma viruses expressing rabbit hemorrhagic disease virus capsid protein. J. Virol., 70: 5061-5066.Best S., Kerr P. 2000. Coevolution of Host and Virus: The Pathogenesis of Virulent and Attenuated Strains of Myxoma Virus in Resistant and Susceptible European Rabbits. Virology, 267, 36-48. https://doi.org/10.1006/viro.1999.0104Bhanuprakash V., Hosamani M., Venkatesan G., Balamurugan V., Yogisharadhya R., Singh R. 2012. Animal poxvirus vaccines: a comprehensive review Expert Rev. Vaccines, 11, 1355-1374. https://doi.org/10.1586/erv.12.116Calvete C., Estrada R., Lucientes J., Osacar J., Villafuerte R., 2004. Effects of vaccination against viral haemorrhagic disease (VHD) and myxomatosis on long-term mortality rates of European wild rabbits. Vet. Rec., 155: 388-392.Dalton K., Nicieza I., Gullón J., Inza M., Petralanda M., Arroita Z., Parra F. 2012. Analysis of Myxomatosis outbreaks on Spanish rabbit farms. In Proc.: 10th World Rabbit Congress, September 3 - 6, 2012, Sharm El- Sheikh, Egypt, 1203-1207.Dalton K., Nicieza I., de Llano D., Gullón J., Inza M., Petralanda M., Arroita Z., Parra F. 2015. Vaccine breaks: Outbreaks of myxomatosis on Spanish commercial rabbit farms. Vet. Microbiol., 178, 208-216. https://doi.org/10.1016/j.vetmic.2015.05.008Dan M., Baraitareanu S., Danes D., 2014. Serosurveillance of Myxomatosis by Competitive ELISA. Bulletin UASVM Veterinary Medicine. 71, 266-267.Day M., Fenner F., Woodroofe G., McIntyre G.A. 1956. Further studies on the mechanism of mosquito transmission of Myxomatosis in the European rabbit. J. Hyg. Cambridge, 54:258-283.Farsang A., Makranszki L., Dobos-Kovacs M., Virag G., Fabian K., Barna T., Kuclsar G., Kucsera L., Vetesi F. 2003. Occurrence of atypical myxomatosis in central Europe: clinical and virological examinations. Acta Vet. Hung., 51, 493-501. https://doi.org/10.1556/AVet.51.2003.4.7Fenner F., Ratcliffe F. 1965. Myxomatosis. Cambridge University Press, Cambridge, England. Ferreira C., Ramírez E., Castro F., Ferreras P., Alves P., Redpath S., Villafuerte R. 2009. Field experimental vaccination campaigns against myxomatosis and their effectiveness in the wild. Vaccine, 27: 6998-7002. https://doi.org/10.1016/j.vaccine.2009.09.075Jeklova E., Leva L., Matiasovic J., Kovarcik K., Kudlackova H., Nevorankova Z., Psikal I., Faldyna M. 2007. Characterisation of immunosuppression in rabbits after infection with myxoma virus, Vet. Microbiol., 129: 117-130. https://doi.org/10.1016/j.vetmic.2007.11.039Kerr P.J. 1997. An ELISA for Epidemiological Studies of Myxomatosis: Persistance of Antibodies to Myxoma Virus in European Rabbits (Oryctolagus cuniculus). Wildlife Res., 24: 53-65.https://doi.org/10.1071/WR96058Kerr P.J. 2012. Myxomatosis in Australia and Europe: A model for emerging infectious diseases. Antivir. Res., 93: 387-415. https://doi.org/10.1016/j.antiviral.2012.01.009Kim, Y.C., Jarrahian, C., Zehrung, D., Mitragotri, S., Prausnitz , M.R. 2012. Delivery Systems for Intradermal Vaccination. Curr. Top. Microbiol., 351: 77-112. https://doi.org/10.1007/82_2011_123King A., Adams M., Carstens E., Lefkowitz E. 2012. Virus Taxonomy. Classification and Nomenclature of Viruses. Ninth Report of the International Committee on Taxonomy of Viruses, 291-309.Lavazza A., Graziani M., Tranquillo V.M., Botti G., Palotta C., Cerioli M., Capucci L. 2004. Serorological evaluation of the immunity induced in commercial rabbits by vaccination for Myxomatosis and RHD, In Proc.: 8th World Rabbit Congress, September 7-10, 2004, Puebla, Mexico, 569-575.Le Normand B., Chatellier S., Devaud I., Delvecchio A., Lavazza A., Capucci L. 2015. Evaluation de l'immunité humorale consécutive à la vaccination avec Dervaximyxo SG33 chez des lapines reproductrices vaccinées à différents stades du cycle productif. 16e Journées de la Recherche Cunicole. Le Mans, France. 17-20.Lemiere S. 2000. Combined vaccination against myxomatosis and VHD: an innovative approach, In: 7th World Rabbit Congress, Valencia, 4-7th July, Spain, World Rabbit Sci., 8 suppl 1. Vol. B:289-297.Levin C., Perrin H., Combadiere B. 2015. Tailored immunity by skin antigen-presenting cells. Hum. Vacc. Immunother., 11: 27-36. https://doi.org/10.4161/hv.34299Marlier D. 2010. Vaccination strategies against myxomavirus infections: are we really doing the best? Tijdschr Diergeneesk., 135: 194-198.Marlier D., Mainil J., Boucraut-Baralon C., Linden A., Vindevogel H. 2000. The efficacy of two vaccination schemes against expérimental infection with a virulent amyxomatous or a virulent nodular myxoma virus strain. J. Comp. Path. Vol. 122, 115-122. https://doi.org/10.1053/jcpa.1999.0346Marshall I., Regnery C. 1960. Myxomatosis in a California brush rabbit (Sylvilagus bachmani). Nature, 188: 73-74. http://doi.org/10.1038/188073b0Morimoto M. 2009. General Physiology of Rabbits. In: Houdebine LM., Fan J. (eds) Rabbit Biotechnology. Springer, Dordrecht. OIE. 2014. Myxomatosis. Chapter 2.6.1. (NB: Version adopted in May 2014). Manual of Diagnostic Tests and Vaccines for Terrestrial Animals http://www.oie.int/fileadmin/Home/fr/Health_standards/tahm/2.06.01_MYXO.pdf Accessed June 2018.Panchanathan V., Chaudhri G., Karupiah G. 2008. Correlates of protective immunity in poxvirus infection: where does antibody stand? Immunol. Cell Biol., 86, 80-86. https://doi.org/10.1038/sj.icb.7100118Rouco C, Moreno S, Santoro S. 2016. A case of low success of blind vaccination campaigns against myxomatosis and rabbit haemorrhagic disease on survival of adult European wild rabbits. Prev. Vet. Med., 133: 108-113. https://doi.org/10.1016/j.prevetmed.2016.09.013Spibey N., McCabe V., Greenwood N., Jack S., Sutton D., van der Waart L. 2012. Novel bivalent vectored vaccine for control of myxomatosis and rabbit haemorrhagic disease. Vet. Rec., 170: 309. http://dx.doi.org/10.1136/vr.10036

Quantitative risk assessment of hepatitis E virus: modelling the occurrence of viraemic pigs and the presence of the virus in organs of food safety interest

Hepatitis E virus (HEV) is a zoonotic pathogen with consumption of pork and derived products identified in different countries as a risk factor for human exposure to HEV. Great efforts have been made to understand the dynamics of virus transmission within domestic swine populations through modelling. However, from a food safety prospective, it is critical to integrate the parameters involved in the transmission dynamics with those governing the actual presence of HEV in the bloodstream, the liver, gallbladder or faeces. To date, several aspects related to the pathogenesis of the disease are still unknown or characterized by significant levels of uncertainty, making this conjunction challenging. We used published serological data obtained from pigs in a farrow-to-finish farm to implement an Immune-Susceptible-Infected-Recovered (MSIR) model reproducing the on-farm dynamics that lead to the occurrence of viraemic pigs at slaughter. Expert opinion on the length of time infectious HEV can be detected in liver, gallbladder/bile and faeces after recovery from viraemic status were used to inform a stochastic model aimed at estimating the expected proportion of viraemic pigs, pigs with infectious HEV in liver, gallbladder/bile and faeces entering the slaughterhouse. To simulate the potential effect of on-farm mitigation strategies, we estimated the changes in outcomes of interest as a function of variations in the baseline transmission parameters. The model predicted a proportion of viraemic pigs entering the slaughterhouse of 13.8% while the proportions of, and ranged from 13.8% to 94.4%, 13.8% to 94.7% and from 25.3% to 30.8% respectively, due to the uncertainty surrounding the experts’ opinions. Variations in MSIR model’s parameters alert of the need to carefully consider the application of mitigation strategies aimed at delaying the decay of maternal immunity or the peak of the within herd transmission. When the rate of decay of maternal immunity and the transmission rate were decreased between 80% and 5% and 40% and 5% from the baseline values respectively, adverse effects on were observed. The model highlights the relevance of specific aspects in the pathogenesis of the disease from a food safety prospective and it was developed to be easily reproducible and updatable as soon as accurate data becomes available. As presented, the model can be directly connected to existing or future pig-related models to estimate the significance of the identified parameters on the risk of human exposure to HEV through consumption of pork products