• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.865-876
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• 2002

Successful project planning relies on a good estimation of the effort required to complete a project, together with the schedule options that may be available. Existing software effort estimation models are present only the total effort and instantaneous effort function for the software life-cycle. Also, Putnam presents constant effort rate in each phase. However, the size of total effort varies according to the software projects under the influence of its size, complexity and operational environment. As a result, the allocated effort in each phase also differs from one project to another. This paper suggests models for effort allocation in planning, specifying, building, testing and implementing phases followed by the project size and development types. These models are derived from 155 different projects. Therefore, these models can be considered as a practical guideline in management of project schedule and effort allocation.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.20-28
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• 2004

Estimation of software project cost, effort, and duration in the early stage of software development cycle is a difficult and key problem in software engineering. Most of development effort and duration estimation models presented by regression model of simple relation function point vs. effort and effort vs. duration instead of considering developer's productivity. But different project have need for different effort according to developer's productivity if the projects are same software size. Also, different duration takes according to developer's productivity if the projects require the same effort. Therefore, models that take into account of productivity have a limited application in actual development project. This paper presents models that can be estimate the duration according to productivity in order to compensate a shortcoming of the previous models. Propose model that could presume development period by various methods based on productivity and compared models' performance. As a result of performance comparison, an estimating model of development period from software size got simple and most good result. The model gives decision-making information of development duration to project management in the early stage of software life cycle.

• Journal of the Korea Computer Industry Society
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• v.3 no.3
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• pp.295-306
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• 2002

Successful project planning relies on a good estimation of the effort required to complete a project, together with the schedule options that may be available. Despite the extensive research done developing new and better models, existing software effort estimation models are present only the total effort and instantaneous effort function for the software life-cycle. Also, Putnam presents constant effort rate in each phase. However, the size of total effort are variable according to the software projects under the influence of its size, complexity and operational environment. As a result, the allocated effort in each phase also differ from project to project. This paper suggests the criteria for effort allocation in planning, specifying, building, testing and implementing phase followed by the project total effort. These criteria are derived from 183 different projects. This result can be considered as a practical guideline in management of project schedule and effort allocation.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.259-266
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• 2002

The main issue in software development is the ability of software project effort and cost estimation in the early phase of software life cycle. The regression models for project effort and cost estimation are presented by function point that is a software sire. The data sets used to conduct previous studies are of ten small and not too recent. Applying these models to 789 project data developed from 1990 ; the models only explain fewer than 0.53 $R^2$(Coefficient of determination) of the data variation. Homogeneous group in accordance with project delivery rate (PDR) divides the data sets. Then this paper presents general effort estimation models using project delivery rate. The presented model has a random distribution of residuals and explains more than 0.93 $R^2$ of data variation in most of PDR ranges.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.6
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• pp.429-437
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• 2019

This paper deals with a ZEM (Zero-Effort-Miss) based guidance law for the interception of moving targets and characteristics of the guidance law according to time-to-go estimation methods. To derive the ZEM vector feedback guidance command, we introduce a polynomial function with unknown coefficient, and then we determine the coefficient to satisfy initial and terminal constraints. Since the directions of the guidance command and ZEM vectors are adjusted by the time-to-go, general time-to-go estimation methods are proposed, which can generate the vertical and horizontal guidance commands with respect to an arbitrary reference frame. By performing various numerical simulations, the performance and characteristics of the proposed methods are investigated.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.99-106
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• 2013

Generally, software development schedule compression is decided within 75% of nominal schedule. However, there are some difficulties when we judge the possibility of development schedule compression because a nominal schedule has not been definitely. Therefore, this paper investigates various nominal schedule estimation models and decides the optimum range. Basing on the performance of ISBSG Release 8,614 projects are extracted from the actual 1,595 projects. We presented development effort estimation model from those data. Also, we derived the development schedule model from the development effort. When you apply the proposed model, you will be able to estimate development effort and schedule required for the development more actually.

• 한국IT서비스학회:학술대회논문집
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• 2003.11a
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• pp.616-623
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• 2003

Since the computing environment changes very rapidly, the estimation of software effort is very difficult because it is not easy to collect a sufficient number of relevant cases from the historical data. If we pinpoint the cases, the number of cases becomes too small. However if we adopt too many cases, the relevance declines. So in this paper we attempt to balance the number of cases and relevance. Since many researches on software effort estimation showed that the neural network models perform at least as well as the other approaches, so we selected the neural network model as the basic estimator. We propose a search method that finds the right level of relevant cases for the neural network model. For the selected case set, eliminating the qualitative input factors with the same values can reduce the scale of the neural network model. Since there exists a multitude of combinations of case sets, we need to search for the optimal reduced neural network model and corresponding case set. To find the quasi-optimal model from the hierarchy of reduced neural network models, we adopted the beam search technique and devised the Case-Set Selection Algorithm. This algorithm can be adopted in the case-adaptive software effort estimation systems.

• The KIPS Transactions:PartD
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• v.11D no.7 s.96
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• pp.1483-1490
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• 2004

To accomplish a project successfuly, we have to estimate develpment effort accurately. But, development effort is different to software size and operation environment. Usually, we made use of function point for estimating development effort. In this paper. we make use of 789 project data. It is related to development projects in 1990`s. We investigate the variable affecting development effort. Also, we exedcute multiple liner regression analysis for looking linear relation about variables. We find the regression equation for multistage by dividing PDR that influ-enced development effort step by step.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.173-182
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• 2004

The research to estimate development effort of software has been progress. But, it is not easy gain that testing data for estimating of development effort. Also, if we get the testing data, it is important that analysis testing data. In this paper, we study the data analysis of software development effort using the 789 software development projects which developed in the 1990's. Software development scale and software development team site are various. Using the characteristic of factor, we have to study characteristic of data and we estimate the development effort step by step. First, we prove the difference of development effort with the 789 project data according to development type, development environment, the development language etc. Also, we execute the crosstabs analysis that team site and function point.

• Journal of the Korea Computer Industry Society
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• v.7 no.3
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• pp.191-198
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• 2006

Area of software measurement is active more than thirty years. There is a huge collection of researches but still no concrete software development effort, duration and cost estimation model. The data sets used to conduct previous studies in the duration estimation model are often small and not too recent, these types of models should not be apply in recent projects that have complex architecture and various development environment. Therefore, Oligny et al. presents empirical models that predict software project duration in accordance with project platform based on project effort using the log data transformation. These models are based on the analysis of 396 project data provided by release 4 of the ISBSG Benchmark. Applying Oligny et al.'s models to 534 project data provided release 6 of the ISBSG Benchmark, the project duration is affected by development type more than development platform. Therefore, This paper presents the model of duration estimation according to development type. This paper proves the duration is more affected by development type than development platform. And, The model according to development type is more adequate for duration estimation.