ieee abbreviation in software engineering

In addition, only three homogeneous ensembles of ANFIS (i.e., HM-ANFIS-[Avg], HM-ANFIS-[WtAvg], and HM-ANFIS-[ANFIS-FCM]) achieved better EF than the individual ANFIS model, whereas the other ensembles of ANFIS were worse than it. (vi)None of the homogeneous ensembles of ANFIS was among the top 10 models in Desharnais dataset. There are eight combination rules: two linear (averaging and weighted averaging) and six nonlinear (MLP, SVR, FIS-FCM, FIS-SC, ANFIS-FCM, and ANFIS-SC). This section also comprises assumptions which are made by the team of requirement engineering at the time of requirements gathering and analysis. 1, pp. Computer Code and Software. (viii)All ensembles models with the nonlinear combiner [FIS-FCM] did not perform well as they were not among the top 10 models in any dataset. 4, no. This section discusses the conducted empirical study and its results. It is required by many U.S. Government contracts, especially in software development.CMU claims CMMI can be used to guide process improvement across a In addition, heterogeneous ensembles with different base models can be also explored and evaluated. Although none of the ensemble models was consistently the best, many of them were frequently among the best models for each dataset. It addresses product and service development processes. Section 3 describes the computational intelligence and ensemble models that have been developed. The results confirm that individual models are not reliable as their performance is inconsistent and unstable across different datasets. They suggest one should combine the different fragments of the methods into a new hybrid method. 4, pp. STP is a link management protocol designed to support redundant links that stops switching loops in the STP network. 15, pp. Rawdon "Rusty" Young was the chief architect for the development of CMMI version 2.0. Jrgensen [6] conducted a review of studies on expert estimation of software development effort. 6, pp. Rather than using a sliding window to generate the dictionary, the input data is either preprocessed to generate a dictionary wiith infinite scope of the input, or the dictionary is formed as the file is In addition, at least two of the homogeneous ensembles of SVR were among the top 10 models in each dataset. [7], According to the Software Engineering Institute (SEI, 2008), CMMI helps "integrate traditionally separate organizational functions, set process improvement goals and priorities, provide guidance for quality processes, and provide a point of reference for appraising current processes."[8]. None of the homogeneous ensembles of ANFIS was among the top 10 models in Desharnais dataset. [18] The median increase in performance varied between 14% (customer satisfaction) and 62% (productivity). They observed that bagging ensemble of regression trees performed well in comparison to other approaches. Some major changes in CMMI V1.3 [4] are the support of agile software development,[5] improvements to high maturity practices[6] and alignment of the representation (staged and continuous). That year, Berners-Lee and CERN data systems Eng. Therefore, the process of deriving an estimate is not explicit and thus not repeatable [3]. 10, pp. IDEF, initially an abbreviation of ICAM Definition and renamed in 1999 as Integration Definition, is a family of modeling languages in the field of systems and software engineering.They cover a wide range of uses from functional modeling to data, simulation, object-oriented analysis and design, and knowledge acquisition. As a strict organization that stands behind diverse standards in engineering and industrial processes, IEEE format is used for engineering journals, research papers or lectures on subject. 70, no. For the US government organization, see. [24] These roadmaps combine the strengths of both the staged and the continuous representations. The following subsections discuss the results based on each dataset and then the overall results based on all datasets. [1] performed a systematic literature review of software development effort estimation based on computational intelligence models. I. F. de Barcelos Tronto, J. D. S. da Silva, and N. Sant'Anna, An investigation of artificial neural networks based prediction systems in software project management, Journal of Systems and Software, vol. To assign weight of the members of ensemble model we predicted the whole training data to measure each members performance in terms of RMSE and assigned highest weight to the model having lowest RMSE. but only p. for one page; If items are online, add the statement, from url (without quotes). Furthermore, all homogeneous ensembles of SVR except HM-SVR-[SVR] improved the performance of the individual SVR model in terms of EF. section. 21, no. Examples include neural networks [4, 1113], Bayesian network [14], fuzzy logic [3], regression trees (RT) [15, 16], case-based reasoning [10, 17, 18], genetic programming [19, 20], and support vector regression [15, 21]. To improve the efficiency of PCA approach, the GA has been used to select the features that would increase the performance in both training phase and test phase. 567576, 2000. C. J. Burgess and M. Lefley, Can genetic programming improve software effort estimation? 209214, November 2007. CMMI for Services (CMMI-SVC), v1.3 was released in November 2010. 6, pp. Table 2 lists the homogeneous and heterogeneous ensembles that have been investigated in this paper. By comparing the performance of the homogeneous ensembles of MLP, it can be observed that the HM-MLP-[ANFIS-FCM] model was the best. Accurate estimation of software development effort is essential for effective management and control of software development projects. Instant messaging is a set of communication technologies used for text-based communication between two (private messaging) or more (chat room) participants over the Internet or other types of networks (see also LAN messenger).IMchat happens in real-time. In version 2.0 the above representation separation was cancelled and there is now only one cohesive model. In case of the HM-SVR-[SVR] model, it was ranked 10th in Albrecht dataset and was not among the top 10 models in the other four datasets. 14031416, 2012. 15121528, 2013, 095058. Elish [29] evaluated the extent to which the voting ensemble model, with median combination rule, offers reliable and improved estimation accuracy over five individual models: MLP, RBF, RT, K-nearest neighbor (KNN), and SVR in estimating software development effort. 6, pp. The Internet Protocol is the protocol that defines and enables [13] These statistics indicate that, since 1987, the median times to move from Level 1 to Level 2 is 23 months, and from Level 2 to Level 3 is an additional 20 months. In case of the HM-SVR-[SVR] model, it was ranked 10th in Albrecht dataset and was not among the top 10 models in the other four datasets. In Desharnais dataset, as observed from Table 4 and Figure 6, the individual SVR model performed better than both the hybrid PCA-SVR model and the hybrid PCA-GA-SVR model. The Institute of Electrical and Electronics Engineers (IEEE) is a 501(c)(3) professional association for electronic engineering and electrical engineering (and associated disciplines) with its corporate office in New York City and its operations center in Piscataway, New Jersey.The mission of the IEEE is advancing technology for the benefit of humanity. Wen et al. Figures 8, 10, 12, 14, and 16 show five plots of the MMRE versus the PRED(25) values that were achieved by each model in each dataset, respectively. We developed one heterogeneous ensemble model having PCA-based CI models of type MLP, SVR, and ANFIS. By comparing the performance of the homogeneous ensembles of MLP, it can be observed that HM-MLP-[ANFIS-SC] was the best model based on PRED(25) and EF metrics. L. L. Minku and X. Yao, A principled evaluation of ensembles of learning machines for software effort estimation, in Proceedings of the 7th International Conference on Predictive Models in Software Engineering (PROMISE '11), September 2011. Investigated homogeneous and heterogeneous ensemble models. Expert judgment makes estimations based on the experience of experts on similar projects. Algorithmic models are unable to capture the complex set of relationships. The goal of ensemble model is to manage each individual models strengths and weaknesses automatically, leading to the best possible decision being taken overall. PCA performs a mapping of the data to a lower dimensional space in such a way that the variance of the data in the low-dimensional representation is maximized. It is designed for teams of ten or fewer members who break their work into goals that can be completed within time-boxed iterations, called sprints, no longer than one month This includes classification and regression problems of fault and changeability prediction. 701713, 2000. ^A: 01: STX: Start of Header: Used as first character of head of data broadcast/message. By comparing the performance of the homogeneous ensembles of ANFIS, it can be observed that HM-ANFIS-[MLP] was the best among them in terms of EF. We have conducted an empirical study to evaluate and compare the performance of these ensembles using five popular datasets. As neural network model, they used MLP and training sets were generated by bootstrapping. Examples of such models include constructive cost model (COCOMO) [7], function points analysis [8], and software lifecycle management (SLIM) [9]. However, none of the existing models proved to be suitable under all circumstances; that is, Heterogeneous ensemble consists of members having different base learning algorithms. Trying to keep up with the industry the model also has explicit reference to agile aspects in some process areas. Capability Maturity Model Integration (CMMI) is a process level improvement training and appraisal program. Science, technology, engineering, and mathematics (STEM) is a broad term used to group together several academic disciplines.This term is typically used to address an education policy or curriculum choices in schools. K. K. Shukla, Neuro-genetic prediction of software development effort, Information and Software Technology, vol. However, at least one of the homogeneous ensembles of ANFIS was among the top 10 models in the other datasets. By comparing the performance of the homogeneous ensembles of ANFIS, it can be observed that HM-ANFIS-[Avg] and HM-ANFIS-[WtAvg] were the best models among them in terms of EF. For this dataset, we accordingly developed homogeneous and heterogeneous ensembles of the hybrid PCA-GA-SVR model, the hybrid PCA-MLP model, and the hybrid PCA-ANFIS model. Among the heterogeneous ensemble models, HT-(MLP, SVR, ANFIS)-[Avg] and HT-(MLP, SVR, ANFIS)-[ANFIS-FCM] achieved relatively better performance than the other heterogeneous ensembles. 38, no. It has been in use for Of the small organizations (<25 employees), 70.5% are assessed at level 2: Managed, while 52.8% of the organizations with 1,0012,000 employees are rated at the highest level (5: Optimizing). The SEI published a study saying 60 organizations measured increases of performance in the categories of cost, schedule, productivity, quality and customer satisfaction. It is commonly used in a formal sense in engineering design, including for example in systems engineering, software engineering, or enterprise engineering.It is a broad concept that could By comparing the performance of the homogeneous ensembles of SVR, it can be noticed that HM-SVR-[ANFIS-SC] was the best, followed by the HM-SVR-[ANFIS-FCM]. In this paper, we have developed different homogeneous and heterogeneous ensembles of optimized hybrid computational intelligence models for software development effort estimation. Indeed, best results are often obtained by bagging overfitted classifiers. Kocaguneli et al. They concluded that bagging was able to improve the performance of all models except SVR. 438442, October 2005. The latter is arranged by levels, not "Specific Goals". 1-2, pp. 6, pp. Considering the Case for Security Content in CMMI for Services (October 2010), Center for Medicare and Medicaid Innovation, Standard CMMI Appraisal Method for Process Improvement, Enterprise Architecture Assessment Framework, "Trademark Electronic Search System (TESS)", "CMMI V1.3 Released: High Maturity Clarified", "CMMI Institute - Core Practice Areas, Categories, and Capability Areas", "Standard CMMI Appraisal Method for Process Improvement (SCAMPISM) A, Version 1.2: Method Definition Document", http://jeffsutherland.com/scrum/SutherlandScrumCMMIHICSSPID498889.pdf, "CMMI V1.3: The CMMI Product and Product Integration roadmaps", "CMMI V1.3: The CMMI Process and Measurement roadmaps", "Using CMMI to Improve Earned Value Management", Dietrich College of Humanities and Social Sciences, H. John Heinz III College of Information Systems and Public Policy, Margaret Morrison Carnegie College (defunct), Hunt Institute for Botanical Documentation, https://en.wikipedia.org/w/index.php?title=Capability_Maturity_Model_Integration&oldid=1120741393, All articles with bare URLs for citations, Articles with bare URLs for citations from March 2022, Articles with PDF format bare URLs for citations, Short description is different from Wikidata, Articles with unsourced statements from November 2013, Official website different in Wikidata and Wikipedia, Creative Commons Attribution-ShareAlike License 3.0. Abbreviation Name Description ^@ 00: NULL: Null: Used to perform media-fill and allow gaps. MMRE versus PRED(25) by each model using Miyazaki dataset. COCOMO dataset [7] consists of 63 software projects including business, scientific, systems, real-time, and support software projects. They were among the top 10 models in four out of the five datasets. A. Rodger, A probabilistic model for predicting software development effort, IEEE Transactions on Software Engineering, vol. The NSA is responsible for global monitoring, collection, and processing of information and data for foreign and domestic intelligence and counterintelligence purposes, specializing in a discipline known Considering the Case for Security Content in CMMI for Services has one process area, Security Management. L. H. Putnam, A general empirical solution to the macro sizing and estimating problem, IEEE Transactions on Software Engineering, vol. These statistics are updated and published every six months in a maturity profile. The hybrid PCA-MLP model performed better than both the individual MLP model and the hybrid PCA-GA-MLP model. 9, no. In this case ensemble members can be different by the structure. Y. Miyazaki, M. Terakado, K. Ozaki, and H. Nozaki, Robust regression for developing software estimation models, The Journal of Systems and Software, vol. Product and service development CMMI for Development (CMMI-DEV), Service establishment, management, CMMI for Services (CMMI-SVC), and. However, at least two of the heterogeneous ensembles were among the top 10 models in the other datasets. Homogeneous ensemble consists of members having a single-type base learning algorithm. where the weight calculation formula is MPEG-1 Audio Layer II or MPEG-2 Audio Layer II (MP2, sometimes incorrectly called Musicam or MUSICAM) is a lossy audio compression format defined by ISO/IEC 11172-3 alongside MPEG-1 Audio Layer I and MPEG-1 Audio Layer III (MP3). Mary Beth Chrissis, Mike Konrad, and Sandy Shrum Rawdon were the authorship team for the hard copy publication of CMMI for Development Version 1.2 and 1.3. In March 2016, the CMMI Institute was acquired by ISACA. Different linear and nonlinear combiners have been used to combine the base hybrid learners. Since all practices are now compulsory to comply, "Expected" section has been removed. Table 4 reports the performance of the individual and hybrid models based on the EF metric in each of the five datasets. These models are HM-MLP-[Avg], HM-MLP-[FIS-SC], HM-ANFIS-[WtAvg], and HT-(MLP, SVR, ANFIS)-[WtAvg]. This section evaluates and compares the estimation performance of the homogeneous and heterogeneous ensemble models under investigation. In addition, at least two of the homogeneous ensembles of SVR were among the top 10 models in each dataset. Among the heterogeneous ensemble models, HT-(MLP, SVR, ANFIS)-[Avg], HT-(MLP, SVR, ANFIS)-[WtAvg], and HT-(MLP, SVR, ANFIS)-[MLP] achieved relatively better performance than the other heterogeneous ensembles. Among the heterogeneous ensemble models, HT-(MLP, SVR, ANFIS)-[WtAvg] and HT-(MLP, SVR, ANFIS)-[ANFIS-SC] achieved relatively better performance than the other heterogeneous ensembles. The naming convention (abbreviation) for these ensemble models is as follows: EnsembleType-BaseLearner(s)-[CombinationRule]. a generic and terminology-free description] and "context-specific" [ i.e. In these ensembles, various linear and nonlinear combination rules can be evaluated. Following a bumpy launch week that saw frequent server trouble and bloated player queues, Blizzard has announced that over 25 million Overwatch 2 players have logged on in its first 10 days. The purpose of tables and figures in documents is to enhance your readers' NASA presentation. By comparing the performance of the homogeneous ensembles of ANFIS, it can be observed that HM-ANFIS-[ANFIS-SC] was the best among them in terms of MMRE, PRED(25), and EF. 639648, 1983. It is calculated as follows: This section evaluates whether the hybridization of an individual model improves its estimation performance. MMRE versus PRED(25) by each model using COCOMO dataset. E. Kocaguneli, Y. Kultur, and A. Bene, Combining multiple learners induced on multiple datasets for software effort prediction, in Proceedings of the International Symposium on Software Reliability Engineering (ISSRE '09), 2009. Find out what any acronym, abbreviation, or initialism stands for With more than 1,000,000 human-edited definitions, Acronym Finder is the world's largest and most comprehensive dictionary of acronyms, abbreviations, and initialisms. The combined output is then a weighted sum of the outputs of all members as given by , where . To address user security concerns, two unofficial security guides are available. P. L. Braga, A. L. I. Oliveira, G. H. T. Ribeiro, and S. R. L. Meira, Bagging predictors for estimation of software project effort, in Proceedings of the International Joint Conference on Neural Networks (IJCNN '07), pp. "Sinc CMMI best practices are published in documents called models, each of which addresses a different area of interest. These models are ANFIS, HM-MLP-[SVR], HM-MLP-[FIS-FCM], HM-SVR-[FIS-FCM], HM-ANFIS-[SVR], HM-ANFIS-[FIS-FCM], HM-ANFIS-[FIS-SC], HT-(MLP, SVR, ANFIS)-[SVR], and HT-(MLP, SVR, ANFIS)-[FIS-FCM]. For this dataset, we accordingly developed homogeneous and heterogeneous ensembles of hybrid PCA version of the individual models. The staged representation is designed to provide a standard sequence of improvements, and can serve as a basis for comparing the maturity of different projects and organizations. (vii)None of the heterogeneous ensembles was among the top 10 models in Albrecht dataset. Performance of individual and hybrid models based on EF metric. The table below lists the seventeen CMMI core process areas that are present for all CMMI areas of interest in version 1.3. Copyright 2013 Mahmoud O. Elish et al. The formula assumes that outputs from all CI models are of equal weight. Many software effort estimation methods have been proposed in the literature including computational intelligence models. In Miyazaki dataset, as observed from Table 4 and Figure 3, the hybrid PCA-GA-SVR model performed better than both the individual SVR model and the hybrid PCA-SVR model. MMRE versus PRED(25) by each model using Albrecht dataset. Internet Protocol version 4 is described in IETF publication RFC 791 (September 1981), replacing an earlier definition of January 1980 (RFC 760). None of the individual model was among the top 10 models. In March 1982, the US Department of Defense decided on the Internet Protocol Suite (TCP/IP) as the standard for all military computer networking.. Purpose. Furthermore, all other homogeneous ensembles of SVR performed worse than the individual SVR model in terms of EF. [10] Process areas are the areas that will be covered by the organization's processes. M. Shepperd and C. Schofield, Estimating software project effort using analogies, IEEE Transactions on Software Engineering, vol. The dependent variable is the software development effort measured by the number of hours of the work carried out by the software supplier from specification until delivery. Signal Processing, IEEE Transactions on IEEE Trans. 80, no. Also, PCA is used to perform dimension reduction and variable selection based on the resulting variable loadings. description from the perspective of Agile/ Scrum, development, services, etc.] All maturity levels focus on the keyword "performance". E. Kocaguneli, T. Menzies, and J. W. Keung, On the value of ensemble effort estimation, IEEE Transactions on Software Engineering, vol. Figures 7, 9, 11, 13, and 15 show histograms of the EF measure for each models performance in each of the five datasets, respectively. Based on this table, we provide the following observations across the five datasets. The main findings of this study are as follows. The combination of the project management technique earned value management (EVM) with CMMI has been described. S. Grimstad and M. Jrgensen, Inconsistency of expert judgment-based estimates of software development effort, Journal of Systems and Software, vol. L. Minku and X. Yao, Ensembles and locality: insight on improving software effort estimation, Information and Software Technology, vol. Signal Process. It has 16 independent variables that measure product, project, computer, and personnel attributes. (v)At least one of the homogeneous ensembles of MLP was among the top 10 models in each dataset. thesis], University of Montreal, 1989. Relatively accurate estimation models appear in the top left corner of these plots. 6, pp. 42, no. CMMI can be appraised using two different approaches: staged and continuous. 27, no. Y. Zhao, J. Gao, and X. Yang, A survey of neural network ensembles, in Proceedings of the International Conference on Neural Networks and Brain Proceedings (ICNNB '05), pp. One of the most common factors of software project failure is inaccurate estimates of needed resources [2]. It is a Layer 2 protocol that runs on bridges and switches, which should be enabled on the switch interfaces. Among the heterogeneous ensemble models, HT-(MLP, SVR, ANFIS)-[FIS-SC] and HT-(MLP, SVR, ANFIS)-[ANFIS-SC] achieved relatively better performance than the other heterogeneous ensembles. 17701777, 2007. These models are parametric in nature with a formula of standard form that is parameterized from historical data. However, at least one of the homogeneous ensembles of ANFIS was among the top 10 models in the other datasets. 23, no. Regulation and licensure in engineering is established by various jurisdictions of the world to encourage life, public welfare, safety, well-being, then environment and other interests of the general public and to define the licensure process through which an engineer becomes licensed to practice engineering and to provide engineering professional services and engineered In three out of the five datasets that were used in that study, the ensemble model outperformed the individual models. Based on the empirical results, we do not recommend using the following models as they performed worse than the other models across the five datasets: ANFIS, HM-MLP-[SVR], HM-MLP-[FIS-FCM], HM-SVR-[FIS-FCM], HM-ANFIS-[SVR], HM-ANFIS-[FIS-FCM], HM-ANFIS-[FIS-SC], HT-(MLP, SVR, ANFIS)-[SVR], and HT-(MLP, SVR, ANFIS)-[FIS-FCM]. We used GA to extract the most important feature for improving time and accuracy of their methods, and the PCA is used for feature extraction and classification, respectively. where and are the actual and estimated values of observation , respectively, in a dataset of observations. N. Ueda and R. Nakano, Generalization error of ensemble estimators, in Proceedings of the IEEE International Conference on Neural Networks (ICNN '96), pp. Moreover, we do not recommend using the nonlinear combiner FIS-FCM. It is usually used as field separator in Apache Hadoop. In this paper, we have developed different homogeneous and heterogeneous ensembles of some optimized hybrid of computational intelligence models for software development effort estimation. MMRE versus PRED(25) by each model using Maxwell dataset. HCI models are defined as any effective combination of CI techniques in sequential or parallel manner that perform superior to simple CI techniques [30]. 345361, 1978. In order to assess and compare the different estimation models, three performance evaluation metrics were considered. [2] By January 2013, the entire CMMI product suite was transferred from the SEI to the CMMI Institute, a newly created organization at Carnegie Mellon.[3]. J. Desharnais, Analyse statistique de la productivitie des projets informatique a partie de la technique des point des fonction [M.S. In March 1982, the US Department of Defense decided on the Internet Protocol Suite (TCP/IP) as the standard for all military computer networking.. Purpose. Moreover, they need to be calibrated or adjusted to local circumstances [4, 10]. A small company with few resources may be less likely to benefit from CMMI; this view is supported by the process maturity profile (page 10). In the proposed ensemble models, PCA seeks to replace more or less correlated variables by uncorrelated combinations (projections) of the original variables. Both models achieved the best EF value. 911922, 2002. Regulation and licensure in engineering is established by various jurisdictions of the world to encourage life, public welfare, safety, well-being, then environment and other interests of the general public and to define the licensure process through which an engineer becomes licensed to practice engineering and to provide engineering professional services and engineered The distribution of the top 10 models, in terms of EF, is as follows: 3 ensembles of MLP, 2 ensembles of SVR, 3 ensembles of ANFIS, and 2 heterogeneous ensembles. Miyazaki dataset [34] consists of 48 software projects collected by Fujitsu Large Systems Users Group. E. S. Jun and J. K. Lee, Quasi-optimal case-selective neural network model for software effort estimation, Expert Systems with Applications, vol. 22, no. By comparing the performance of the homogeneous ensembles of ANFIS, it can be observed that the HM-ANFIS-[ANFIS-SC] was the best among them in terms of EF. Tables 4, 5, 6, 7, 8 and 9 report the performance of the individual models, the homogeneous ensemble models, and the heterogeneous ensemble models in estimating software development effort using Albrecht, Miyazaki, Maxwell, COCOMO, and Desharnais datasets, respectively. For each ensemble, the table provides its base learner(s), combination type, and rule. The goal of an ensemble model is to manage each of its individual models strengths and weaknesses automatically, leading to the best possible decision being taken overall. The Addison-Wesley publication of Version 1.3 was dedicated to the memory of Watts Humphry. [2] The continuous representation is designed to allow the user to focus on the specific processes that are considered important for the organization's immediate business objectives, or those to which the organization assigns a high degree of risks. 863873, 2001. (i)None of the individual models was among the top 10 models in three datasets (Miyazaki, Maxwell, and COCOMO). In addition, only two homogeneous ensembles of ANFIS (i.e., HM-ANFIS-[MLP] and HM-ANFIS-[SVR]) achieved better EF than the individual ANFIS model, whereas the other ensembles of ANFIS were worse than it. Version 1.3 provides models for three areas of interest: development, acquisition, and services. 395402, 2009. The third performance metric is a recently proposed evaluation function (EF) [37], which is a combination of MMRE and PRED(25). (iv)Nine models were never among the top 10 models in any dataset. It has implications for workforce development, national security concerns (as a shortage of STEM-educated citizens can reduce effectiveness in this area) and Internet Protocol version 4 is described in IETF publication RFC 791 (September 1981), replacing an earlier definition of January 1980 (RFC 760). If so, we will use the hybrid version of it in the development of the ensemble models; otherwise we use it as it is. It is required by many U.S. Government contracts, especially in software development. The distribution of the top 10 models, in terms of EF, is as follows: 1 individual model (MLP), 5 ensembles of MLP, 3 ensembles of SVR, and 1 ensemble of ANFIS. For combining using FIS, we have used FCM with 6 clusters and radius of 0.3 for SC. In COCOMO dataset, as observed from Table 4 and Figure 5, the hybrid PCA-SVR model performed better than both the individual SVR model and the hybrid PCA-GA-SVR model. Computing is any goal-oriented activity requiring, benefiting from, or creating computing machinery.It includes the study and experimentation of algorithmic processes, and development of both hardware and software.Computing has scientific, engineering, mathematical, technological and social aspects. By comparing the performance of the homogeneous ensembles of MLP, it can be observed that HM-MLP-[WtAvg], and HM-MLP-[FIC-SC] were the best models. 69, no. CMMI is the successor of the capability maturity model (CMM) or Software CMM. 9095, June 1996. 949960, 2008. The outputs of the base learners were combined by taking the average of largest cluster obtained using adaptive resonance theory algorithm. History. Models performance using Desharnais dataset. R. D. A. Arajo, A. L. I. de Oliveira, and S. C. B. Soares, A morphological-rank-linear approach for software development cost estimation, in Proceedings of the 21st IEEE International Conference on Tools with Artificial Intelligence (ICTAI '09), pp. This approach promotes that members of the EPG and PATs be trained in the CMMI, that an informal (SCAMPI C) appraisal be performed, and that process areas be prioritized for improvement. Performance of individual and hybrid models based on EF metric using COCOMO dataset. Appraisal teams use a CMMI model and ARC-conformant appraisal method to guide their evaluation of the organization and their reporting of conclusions. We selected the poorly predicted training data by MLP and provided it to train the SVR and later on the poorly predicted training data by SVR is provided to ANFIS for training. Many software effort estimation methods have been proposed in the literature including computational intelligence models. Many software effort estimation methods have been proposed in the literature since 1980s. Fortran (/ f r t r n /; formerly FORTRAN) is a general-purpose, compiled imperative programming language that is especially suited to numeric computation and scientific computing.. Fortran was originally developed by IBM in the 1950s for scientific and engineering applications, and subsequently came to dominate scientific computing. 4, pp. The Standard CMMI Appraisal Method for Process Improvement (SCAMPI) is an appraisal method that meets all of the ARC requirements. IDEF, initially an abbreviation of ICAM Definition and renamed in 1999 as Integration Definition, is a family of modeling languages in the field of systems and software engineering.They cover a wide range of uses from functional modeling to data, simulation, object-oriented analysis and design, and knowledge acquisition. By comparing the performance of the homogeneous ensembles of SVR, it can be noticed that HM-SVR-[Avg] and HM-SVR-[WtAvg] were the best. We have conducted an empirical study to evaluate and compare the performance of these ensembles using five popular datasets. 1, pp. Since the release of the CMMI, the median times to move from Level 1 to Level 2 is 5 months, with median movement to Level 3 another 21 months. In addition, only three homogeneous ensembles of ANFIS (i.e., HM-ANFIS-[Avg], HM-ANFIS-[FIC-SC], and HM-ANFIS-[ANFIS-SC]) achieved worse EF than the individual ANFIS model, whereas the other ensembles of ANFIS were better than it. 3643, 2005. However, no improvement of the estimation accuracy of software effort was achieved. Furthermore, all other homogeneous ensembles of SVR did not improve the performance of the individual SVR model in terms of EF; they performed worse than it. 736743, 1997. None of the individual models was among the top 10 models in three datasets (Miyazaki, Maxwell, and COCOMO). In version 2.0 DEV, ACQ and SVC were merged into a single model where each process area potentially has a specific reference to one or more of these three aspects. In Albrecht dataset, the MLP model was ranked 6th, and, in Desharnais dataset, the SVR model was ranked 5th. 43, no. The Institute of Electrical and Electronics Engineers (IEEE) is a 501(c)(3) professional association for electronic engineering and electrical engineering (and associated disciplines) with its corporate office in New York City and its operations center in Piscataway, New Jersey.The mission of the IEEE is advancing technology for the benefit of humanity. Figure 1 shows an ensemble of number of CI models. Models performance using Miyazaki dataset. * (until 1974) Smart Grid, IEEE Transactions on IEEE Trans. 4, pp. Models performance using COCOMO dataset. The rest of this paper is organized as follows. 520, 2005. Administered by the CMMI Institute, a subsidiary of ISACA, it was developed at Carnegie Mellon University (CMU). 628640, 2007. 313337, 2010. Authentication Header (AH) is a member of the IPsec protocol suite. PCA finds the directions in which a cloud of data points is stretched most. Moreover, all homogeneous ensembles of MLP except HM-MLP-[MLP] improved the performance of the individual MLP model in terms of EF. Histograms of models EF metric using Maxwell dataset. To determine how well the organization's processes compare to CMMI best practices, and to identify areas where improvement can be made, To inform external customers and suppliers of how well the organization's processes compare to CMMI best practices, To meet the contractual requirements of one or more customers, OPSD Organizational Preparedness for Secure Development, SRTS Security Requirements and Technical Solution, SVV Security Verification and Validation, This page was last edited on 8 November 2022, at 15:43. A total of 32 different ensemble models have been evaluated and compared. BaseLearner(s) is either MLP, or SVR, or ANFIS for HM ensembles; or MLP, SVR, and ANFIS for HT ensembles. Emphasis on ensuring implementation of PA's and that these are practised continuously until they become a "habit". Capability Maturity Model Integration (CMMI) is a process level improvement training and appraisal program.Administered by the CMMI Institute, a subsidiary of ISACA, it was developed at Carnegie Mellon University (CMU). Every CI model has limitations and so different learning algorithm suit different problems. Authentication Header (AH) is a member of the IPsec protocol suite. The National Security Agency (NSA) is a national-level intelligence agency of the United States Department of Defense, under the authority of the Director of National Intelligence (DNI). This paper differs from the above related works on the use of ensemble models for software effort estimation in several aspects. Kocaguneli et al. In Maxwell dataset, as observed from Table 4 and Figure 4, the hybrid PCA-GA-SVR model performed better than both the individual SVR model and the hybrid PCA-SVR model. Among the individual models, the MLP model achieved the best performance in terms of MMRE, PRED(25), and EF. 26, no. 31, no. Also used for padding after any code and to mark end of string, notably in programming language C/C++. IEEE Trans. A. Idri, A. Abran, and T. Khoshgoftaar, Estimating software project effort by analogy based on linguistic values, in Proceedings of the 8th IEEE Symposium on Software Metrics, pp. Among the individual models, the MLP model achieved the best performance in terms of MMRE, PRED(25), and EF. None of the ensembles of ANFIS was among the top 10 models. Journal volume numbers are in bold and do not use the abbreviation Vol.; To indicate a page range, use pp. Similarity, the hybrid PCA-ANFIS model performed better than both the individual ANFIS model and the hybrid PCA-GA-ANFIS model. "Sinc He was previously the CMMI Product Owner and the SCAMPI Quality Lead for the Software Engineering Institute. 17491753, 2006. The first metric is mean magnitude of relative error (MMRE), which is calculated as follows: They were among the top 10 models in four out of the five datasets. [16] Security by Design with CMMI for Development, Version 1.3 has the following process areas: While they do not affect maturity or capability levels, these process areas can be reported in appraisal results.[17]. Moreover, in the proposed ensembles, we optimized their parameters using an evolutionary algorithm based on the genetic algorithm (GA). The accuracy of this method greatly depends on the degree in which a new project concurs within the experience and the ability of the expert. [28] evaluated ensembles of preprocessed estimation methods. Maxwell dataset [35] consists of 62 software projects from one of the biggest commercial banks in Finland. It is a Layer 2 protocol that runs on bridges and switches, which should be enabled on the switch interfaces. Ensemble models take a combination of several hypotheses, which tends to cancel out overfitting errors. There are three classes of appraisals, A, B and C, which focus on identifying improvement opportunities and comparing the organization's processes to CMMI best practices. ACM-IEEE DESIGN AUTOMATION CONFERENCE, PROCEEDINGS ACM IEEE D ACM-IEEE International Conference on Cyber-Physical Systems ACM IEEE INT CONF CY ACM-IEEE International Symposium on Empirical Software Engineering and Measurement INT SYMP EMP SOFTWAR ACM/IEEE SIXTH INTERNATIONAL CONFERENCE ON AUTONOMIC COMPUTING It is defined as the process of predicting the effort required to develop a software system [1]. LZ78 was created by Lempel and Ziv in 1978, hence the abbreviation. For this dataset, we accordingly developed homogeneous and heterogeneous ensembles of the hybrid PCA-GA-SVR model, the individual MLP model, and the hybrid PCA-ANFIS model. A. L. I. Oliveira, Estimation of software project effort with support vector regression, Neurocomputing, vol. P. C. Pendharkar, G. H. Subramanian, and J. First, a number of base learners are produced, which can be generated in a parallel style (bagging) or in a sequential style (boosting) where the generation of a base learner has influence on the generation of subsequent learners. The homogeneous ensemble of support vector regression (SVR), with the nonlinear combiner adaptive neurofuzzy inference systems-subtractive clustering (ANFIS-SC), was the best model when considering the average rank of each model across the five datasets. By comparing the performance of the homogeneous ensembles of SVR, it can be noticed that the HM-SVR-[MLP] was the best. Many software effort estimation methods have been proposed in the literature including computational intelligence models. 12, pp. Ranking of models based on EF metric (top 10 models are highlighted). K. Maxwell, Applied Statistics For Software Managers, Prentice-Hall, New Jersey, NJ, USA, 2002. Major computing disciplines include computer engineering, Y. Kultur, B. Turhan, and A. Bener, Ensemble of neural networks with associative memory (ENNA) for estimating software development costs, Knowledge-Based Systems, vol. Two and five optional PA's from "Safety" and "Security" purview have been included. Section 4 reports the conducted empirical study and discusses its results. 54, no. By comparing the performance of the homogeneous ensembles of MLP, it can be observed that HM-MLP-[Avg], HM-MLP-[WtAvg], and HM-MLP-[MLP] were the best models. (iii)Four models were among the top 10 models in three out of the five datasets. (x)By considering the average rank of each model across the datasets, the best five models are HM-SVR-[ANFIS-SC], HM-MLP-[Avg], HT-(MLP, SVR, ANFIS)-[ANFIS-SC], HM-MLP-[FIS-SC], and HT-(MLP, SVR, ANFIS)-[WtAvg]. Sutherland et al. An ensemble model employs a group of multiple learning algorithms and combines their outputs acting as a single decision maker. Kultur et al. Among the heterogeneous ensemble models, HT-(MLP, SVR, ANFIS)-[ANFIS-FCM] and HT-(MLP, SVR, ANFIS)-[ANFIS-SC] achieved relatively better performance than the other heterogeneous ensembles. The staged approach yields appraisal results as one of five maturity levels. Moreover, only three homogeneous ensembles of MLP (i.e., HM-MLP-[MLP], HM-MLP-[FIC-SC], and HM-MLP-[ANFIS-FCM]) achieved better EF than the individual MLP model, whereas the other ensembles of MLP were worse than it. B. Boehm, Software Engineering Economics, Prentice-Hall, New Jersey, NJ, USA, 1981. 80, no. but only p. for one page; If items are online, add the statement, from url (without quotes). CMMI was developed by a group from industry, government, and the Software Engineering Institute (SEI) at CMU. In particular, they applied bagging to linear regression, multilayer perceptron (MLP), M5P regression trees, M5P model trees, and support vector regression (SVR). In 1980, physicist Tim Berners-Lee, a contractor at CERN, proposed and prototyped ENQUIRE, a system for CERN researchers to use and share documents.In 1989, Berners-Lee wrote a memo proposing an Internet-based hypertext system. The byte is a unit of digital information that most commonly consists of eight bits.Historically, the byte was the number of bits used to encode a single character of text in a computer and for this reason it is the smallest addressable unit of memory in many computer architectures.To disambiguate arbitrarily sized bytes from the common 8-bit definition, network protocol 316, 1994. After the first run of the algorithm, in each of the following runs we have selected the same amount of actual training data, that is, the 80% of the whole training set as selected in the previous run which are poorly predicted by the CI model. Therefore, there is a need to build estimation models that are reliable and provide high accuracy. In Albrecht dataset, as observed from Table 4 and Figure 2, the hybrid PCA-SVR model performed better than both the individual SVR model and the hybrid PCA-GA-SVR model. EnsembleType is either HM (homogeneous) or HT (heterogeneous). The main sponsors included the Office of the Secretary of Defense (OSD) and the National Defense Industrial Association. 7, pp. Histograms of models EF metric using Albrecht dataset. In other words, the performance of the individual SVR model was compared to the hybrid PCA-SVR model and the hybrid PCA-GA-SVR model. It has been in use for In 2002, version 1.1 was released, version 1.2 followed in August 2006, and version 1.3 in November 2010. CMMI Roadmaps,[21] which are a goal-driven approach to selecting and deploying relevant process areas from the CMMI-DEV model, can provide guidance and focus for effective CMMI adoption. In version 1.3 CMMI existed in two representations: continuous and staged. Different linear and nonlinear combiners have been used. DSSs serve the management, operations and planning levels of an organization (usually mid and higher management) and help people make decisions about problems that may be rapidly changing and not easily specified in advancei.e. All ensembles models with the nonlinear combiner [FIS-FCM] did not perform well as they were not among the top 10 models in any dataset. A comparison between this paper and related works is provided in Table 1. The results showed that ENNA are significantly better than neural network in terms of accuracy and robustness. Wi-Fi (/ w a f a /) is a family of wireless network protocols, based on the IEEE 802.11 family of standards, which are commonly used for local area networking of devices and Internet access, allowing nearby digital devices to exchange data by radio waves.These are the most widely used computer networks in the world, used globally in home and small office networks to link Around 80% of the datasets is used for training and the rest 20% were used for testing. According to a recent experiment, it was found that there is a high degree of inconsistency in expert judgment-based estimates of software development effort [5]. ISO was founded on 23 February 1947, and (as of November 2022) it has published Models based on the EF metric using COCOMO dataset is the successor of the individual models, each which! ) - [ CombinationRule ] ieee abbreviation in software engineering and to mark end of string, notably in programming language.. 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