On Effort Estimation in Software Projects

Software engineering is criticized as not being engineering or 'well-developed' science at all. Software engineers seem not to know exactly how long their projects will last, what they will cost, and will the software work properly after release. Measurements have to be taken in software projects to improve this situation. It is of limited use to only collect metrics afterwards. The values of the relevant metrics have to be predicted, too. The predictions (i.e. estimates) form the basis for proper project management. One of the most painful problems in software projects is effort estimation. It has a clear and central effect on other project attributes like cost and schedule, and to product attributes like size and quality. Effort estimation can be used for several purposes. In this thesis only the effort estimation in software projects for project management purposes is discussed. There is a short introduction to the measurement issues, and some metrics relevantin estimation context are presented. Effort estimation methods are covered quite broadly. The main new contribution in this thesis is the new estimation model that has been created. It takes use of the basic concepts of Function Point Analysis, but avoids the problems and pitfalls found in the method. It is relativelyeasy to use and learn. Effort estimation accuracy has significantly improved after taking this model into use. A major innovation related to the new estimationmodel is the identified need for hierarchical software size measurement. The author of this thesis has developed a three level solution for the estimation model. All currently used size metrics are static in nature, but this new proposed metric is dynamic. It takes use of the increased understanding of the nature of the work as specification and design work proceeds. It thus 'grows up' along with software projects. The effort estimation model development is not possible without gathering and analyzing history data. However, there are many problems with data in software engineering. A major roadblock is the amount and quality of data available. This thesis shows some useful techniques that have been successful in gathering and analyzing the data needed. An estimation process is needed to ensure that methods are used in a proper way, estimates are stored, reported and analyzed properly, and they are used for project management activities. A higher mechanism called measurement framework is also introduced shortly. The purpose of the framework is to define and maintain a measurement or estimationprocess. Without a proper framework, the estimation capability of an organization declines. It requires effort even to maintain an achieved level of estimationaccuracy. Estimation results in several successive releases are analyzed. It isclearly seen that the new estimation model works and the estimation improvementactions have been successful. The calibration of the hierarchical model is a critical activity. An example is shown to shed more light on the calibration and the model itself. There are also remarks about the sensitivity of the model. Finally, an example of usage is shown.

Cost Estimation of Engineering Environment Services

Työn tavoitteena oli kehittää tutkittavan insinööriyksikön projektien kustannusestimointiprosessia, siten että yksikön johdolla olisi tulevaisuudessa käytettävänään tarkempaa kustannustietoa. Jotta tämä olisi mahdollista, ensin täytyi selvittää yksikön toimintatavat, projektien kustannusrakenteet sekä kustannusatribuutit. Tämän teki mahdolliseksi projektien kustannushistoriatiedon tutkiminen sekä asiantuntijoiden haastattelu. Työn tuloksena syntyi kohdeyksikön muiden prosessien kanssa yhteensopiva kustannusestimointiprosessi sekä –malli.Kustannusestimointimenetelmän ja –mallin perustana on kustannusatribuutit, jotka määritellään erikseen tutkittavassa ympäristössä. Kustannusatribuutit löydetään historiatietoa tutkimalla, eli analysoimalla jo päättyneitä projekteja, projektien kustannusrakenteita sekä tekijöitä, jotka ovat vaikuttaneet kustannusten syntyyn. Tämän jälkeen kustannusatribuuteille täytyy määritellä painoarvot sekä painoarvojen vaihteluvälit. Estimointimallin tarkuutta voidaan parantaa mallin kalibroinnilla. Olen käyttänyt Goal – Question – Metric (GQM) –menetelmää tutkimuksen kehyksenä.

Performance persistence of equity funds in the Russian stock market

This thesis investigates performance persistence among the equity funds investing in Russia during 2003-2007. Fund performance is measured using several methods including the Jensen alpha, the Fama-French 3- factor alpha, the Sharpe ratio and two of its variations. Moreover, we apply the Bayesian shrinkage estimation in performance measurement and evaluate its usefulness compared with the OLS 3-factor alphas. The pattern of performance persistence is analyzed using the Spearman rank correlation test, cross-sectional regression analysis and stacked return time series. Empirical results indicate that the Bayesian shrinkage estimates may provide better and more accurate estimates of fund performance compared with the OLS 3-factor alphas. Secondly, based on the results it seems that the degree of performance persistence is strongly related to length of the observation period. For the full sample period the results show strong signs of performance reversal whereas for the subperiod analysis the results indicate performance persistence during the most recent years.

Bayesian Estimation of Noise

In mathematical modeling the estimation of the model parameters is one of the most common problems. The goal is to seek parameters that fit to the measurements as well as possible. There is always error in the measurements which implies uncertainty to the model estimates. In Bayesian statistics all the unknown quantities are presented as probability distributions. If there is knowledge about parameters beforehand, it can be formulated as a prior distribution. The Bays’ rule combines the prior and the measurements to posterior distribution. Mathematical models are typically nonlinear, to produce statistics for them requires efficient sampling algorithms. In this thesis both Metropolis-Hastings (MH), Adaptive Metropolis (AM) algorithms and Gibbs sampling are introduced. In the thesis different ways to present prior distributions are introduced. The main issue is in the measurement error estimation and how to obtain prior knowledge for variance or covariance. Variance and covariance sampling is combined with the algorithms above. The examples of the hyperprior models are applied to estimation of model parameters and error in an outlier case.

Cost estimation framework for modular product

Cost estimation is an important, but challenging process when designing a new product or a feature of it, verifying the product prices given by suppliers or planning a cost saving actions of existing products. It is even more challenging when the product is highly modular, not a bulk product. In general, cost estimation techniques can be divided into two main groups - qualitative and quantitative techniques - which can further be classified into more detailed methods. Generally, qualitative techniques are preferable when comparing alternatives and quantitative techniques when cost relationships can be found. The main objective of this thesis was to develop a method on how to estimate costs of internally manufactured and commercial elevator landing doors. Because of the challenging product structure, the proposed cost estimation framework is developed under three different levels based on past cost information available. The framework consists of features from both qualitative and quantitative cost estimation techniques. The starting point for the whole cost estimation process is an unambiguous, hierarchical product structure so that the product can be classified into controllable parts and is then easier to handle. Those controllable parts can then be compared to existing past cost knowledge of similar parts and create as accurate cost estimates as possible by that way.

Sensor Fusion of Proprioception, Force and Vision in Estimation and Robot

Sensor-based robot control allows manipulation in dynamic environments with uncertainties. Vision is a versatile low-cost sensory modality, but low sample rate, high sensor delay and uncertain measurements limit its usability, especially in strongly dynamic environments. Force is a complementary sensory modality allowing accurate measurements of local object shape when a tooltip is in contact with the object. In multimodal sensor fusion, several sensors measuring different modalities are combined to give a more accurate estimate of the environment. As force and vision are fundamentally different sensory modalities not sharing a common representation, combining the information from these sensors is not straightforward. In this thesis, methods for fusing proprioception, force and vision together are proposed. Making assumptions of object shape and modeling the uncertainties of the sensors, the measurements can be fused together in an extended Kalman filter. The fusion of force and visual measurements makes it possible to estimate the pose of a moving target with an end-effector mounted moving camera at high rate and accuracy. The proposed approach takes the latency of the vision system into account explicitly, to provide high sample rate estimates. The estimates also allow a smooth transition from vision-based motion control to force control. The velocity of the end-effector can be controlled by estimating the distance to the target by vision and determining the velocity profile giving rapid approach and minimal force overshoot. Experiments with a 5-degree-of-freedom parallel hydraulic manipulator and a 6-degree-of-freedom serial manipulator show that integration of several sensor modalities can increase the accuracy of the measurements significantly.

Mobile system for pump working point estimation

In the current economy situation companies try to reduce their expenses. One of the solutions is to improve the energy efficiency of the processes. It is known that the energy consumption of pumping applications range from 20 up to 50% of the energy usage in the certain industrial plants operations. Some studies have shown that 30% to 50% of energy consumed by pump systems could be saved by changing the pump or the flow control method. The aim of this thesis is to create a mobile measurement system that can calculate a working point position of a pump drive. This information can be used to determine the efficiency of the pump drive operation and to develop a solution to bring pump’s efficiency to a maximum possible value. This can allow a great reduction in the pump drive’s life cycle cost. In the first part of the thesis, a brief introduction in the details of pump drive operation is given. Methods that can be used in the project are presented. Later, the review of available platforms for the project implementation is given. In the second part of the thesis, components of the project are presented. Detailed description for each created component is given. Finally, results of laboratory tests are presented. Acquired results are compared and analyzed. In addition, the operation of created system is analyzed and suggestions for the future development are given.

Estimation of existing cable systems in generator-busbar unit and choice the optimal solution for its modernization

The aim of this master’s thesis is to develop an algorithm to calculate the cable network for heat and power station CHGRES. This algorithm includes important aspect which has an influence on the cable network reliability. Moreover, according to developed algorithm, the optimal solution for modernization cable system from economical and technical point of view was obtained. The conditions of existing cable lines show that replacement is necessary. Otherwise, the fault situation would happen. In this case company would loss not only money but also its prestige. As a solution, XLPE single core cables are more profitable than other types of cable considered in this work. Moreover, it is presented the dependence of value of short circuit current on number of 10/110 kV transformers connected in parallel between main grid and considered 10 kV busbar and how it affects on final decision. Furthermore, the losses of company in power (capacity) market due to fault situation are presented. These losses are commensurable with investment to replace existing cable system.

Bayesian methods for estimation, optimization and experimental design

Mathematical models often contain parameters that need to be calibrated from measured data. The emergence of efficient Markov Chain Monte Carlo (MCMC) methods has made the Bayesian approach a standard tool in quantifying the uncertainty in the parameters. With MCMC, the parameter estimation problem can be solved in a fully statistical manner, and the whole distribution of the parameters can be explored, instead of obtaining point estimates and using, e.g., Gaussian approximations. In this thesis, MCMC methods are applied to parameter estimation problems in chemical reaction engineering, population ecology, and climate modeling. Motivated by the climate model experiments, the methods are developed further to make them more suitable for problems where the model is computationally intensive. After the parameters are estimated, one can start to use the model for various tasks. Two such tasks are studied in this thesis: optimal design of experiments, where the task is to design the next measurements so that the parameter uncertainty is minimized, and model-based optimization, where a model-based quantity, such as the product yield in a chemical reaction model, is optimized. In this thesis, novel ways to perform these tasks are developed, based on the output of MCMC parameter estimation. A separate topic is dynamical state estimation, where the task is to estimate the dynamically changing model state, instead of static parameters. For example, in numerical weather prediction, an estimate of the state of the atmosphere must constantly be updated based on the recently obtained measurements. In this thesis, a novel hybrid state estimation method is developed, which combines elements from deterministic and random sampling methods.

Testing Futures Market Efficiency and Optimal Hedge Ratio Estimation: Evidence from Futures and Options on RTS

This study investigates futures market efficiency and optimal hedge ratio estimation. First, cointegration between spot and futures prices is studied using Johansen method, with two different model specifications. If prices are found cointegrated, restrictions on cointegrating vector and adjustment coefficients are imposed, to account for unbiasedness, weak exogeneity and prediction hypothesis. Second, optimal hedge ratios are estimated using static OLS, and time-varying DVEC and CCC models. In-sample and out-of-sample results for one, two and five period ahead are reported. The futures used in thesis are RTS index, EUR/RUB exchange rate and Brent oil, traded in Futures and options on RTS.(FORTS) For in-sample period, data points were acquired from start of trading of each futures contract, RTS index from August 2005, EUR/RUB exchange rate March 2009 and Brent oil October 2008, lasting till end of May 2011. Out-of-sample period covers start of June 2011, till end of December 2011. Our results indicate that all three asset pairs, spot and futures, are cointegrated. We found RTS index futures to be unbiased predictor of spot price, mixed evidence for exchange rate, and for Brent oil futures unbiasedness was not supported. Weak exogeneity results for all pairs indicated spot price to lead in price discovery process. Prediction hypothesis, unbiasedness and weak exogeneity of futures, was rejected for all asset pairs. Variance reduction results varied between assets, in-sample in range of 40-85 percent and out-of sample in range of 40-96 percent. Differences between models were found small, except for Brent oil in which OLS clearly dominated. Out-of-sample results indicated exceptionally high variance reduction for RTS index, approximately 95 percent.

Development of Cost Estimation with Feedback Information in EPCM Business

Target company of this study is a large machinery company, which is, inter alia, engaged in energy and pulp engineering, procurement and construction management (EPCM) supply business. The main objective of this study was to develop cost estimation of the target company by providing more accurate, reliable and up-to-date information through enterprise resource planning (ERP) system. Another objective was to find cost-effective methods to collect total cost of ownership information to support more informed supplier selection decision making. This study is primarily action-oriented, but also constructive, and it can be divided in two sections: theoretical literature review and empirical study on the abovementioned part of the target company’s business. Development of information collection is, in addition to literature review, based on nearly 30 qualitative interviews of employees at various organizational units, functions and levels at the target company. At the core of development was to make initial data more accurate, reliable and available, a necessary prerequisite for informed use of the information. Certain development suggestions and paths were presented in order to regain confidence in ERP system as information source by reorganizing work breakdown structure and by complementing mere cost information with quantitative, technical and scope information. Several methods to use the information ever more effectively were also discussed. While implementation of the development suggestions outreached the scope of this study, it was forwarded in test environment and interest groups.