Pragmatic cost estimation for web applications

Cost estimation for web applications is an interesting and difficult challenge for researchers and industrial practitioners. It is a particularly valuable area of ongoing commercial research. Attaining on accurate cost estimation for web applications is an essential element in being able to provide competitive bids and remaining successful in the market. The development of prediction techniques over thirty years ago has contributed to several different strategies. Unfortunately there is no collective evidence to give substantial advice or guidance for industrial practitioners. Therefore to address this problem, this thesis shows the way by investigating the characteristics of the dataset by combining the literature review and industrial survey findings. The results of the systematic literature review, industrial survey and an initial investigation, have led to an understanding that dataset characteristics may influence the cost estimation prediction techniques. From this, an investigation was carried out on dataset characteristics. However, in the attempt to structure the characteristics of dataset it was found not to be practical or easy to get a defined structure of dataset characteristics to use as a basis for prediction model selection. Therefore the thesis develops a pragmatic cost estimation strategy based on collected advice and general sound practice in cost estimation. The strategy is composed of the following five steps: test whether the predictions are better than the means of the dataset; test the predictions using accuracy measures such as MMRE, Pred and MAE knowing their strengths and weaknesses; investigate the prediction models formed to see if they are sensible and reasonable model; perform significance testing on the predictions; and get the effect size to establish preference relations of prediction models. The results from this pragmatic cost estimation strategy give not only advice on several techniques to choose from, but also give reliable results. Practitioners can be more confident about the estimation that is given by following this pragmatic cost estimation strategy. It can be concluded that the practitioners should focus on the best strategy to apply in cost estimation rather than focusing on the best techniques. Therefore, this pragmatic cost estimation strategy could help researchers and practitioners to get reliable results. The improvement and replication of this strategy over time will produce much more useful and trusted results.Cost estimation for web applications is an interesting and difficult challenge for researchers and industrial practitioners. It is a particularly valuable area of ongoing commercial research. Attaining on accurate cost estimation for web applications is an essential element in being able to provide competitive bids and remaining successful in the market. The development of prediction techniques over thirty years ago has contributed to several different strategies. Unfortunately there is no collective evidence to give substantial advice or guidance for industrial practitioners. Therefore to address this problem, this thesis shows the way by investigating the characteristics of the dataset by combining the literature review and industrial survey findings. The results of the systematic literature review, industrial survey and an initial investigation, have led to an understanding that dataset characteristics may influence the cost estimation prediction techniques. From this, an investigation was carried out on dataset characteristics. However, in the attempt to structure the characteristics of dataset it was found not to be practical or easy to get a defined structure of dataset characteristics to use as a basis for prediction model selection. Therefore the thesis develops a pragmatic cost estimation strategy based on collected advice and general sound practice in cost estimation. The strategy is composed of the following five steps: test whether the predictions are better than the means of the dataset; test the predictions using accuracy measures such as MMRE, Pred and MAE knowing their strengths and weaknesses; investigate the prediction models formed to see if they are sensible and reasonable model; perform significance testing on the predictions; and get the effect size to establish preference relations of prediction models. The results from this pragmatic cost estimation strategy give not only advice on several techniques to choose from, but also give reliable results. Practitioners can be more confident about the estimation that is given by following this pragmatic cost estimation strategy. It can be concluded that the practitioners should focus on the best strategy to apply in cost estimation rather than focusing on the best techniques. Therefore, this pragmatic cost estimation strategy could help researchers and practitioners to get reliable results. The improvement and replication of this strategy over time will produce much more useful and trusted results

Investigating effort prediction of web-based applications using CBR on the ISBSG dataset

As web-based applications become more popular and more sophisticated, so does the requirement for early accurate estimates of the effort required to build such systems. Case-based reasoning (CBR) has been shown to be a reasonably effective estimation strategy, although it has not been widely explored in the context of web applications. This paper reports on a study carried out on a subset of the ISBSG dataset to examine the optimal number of analogies that should be used in making a prediction. The results show that it is not possible to select such a value with confidence, and that, in common with other findings in different domains, the effectiveness of CBR is hampered by other factors including the characteristics of the underlying dataset (such as the spread of data and presence of outliers) and the calculation employed to evaluate the distance function (in particular, the treatment of numeric and categorical data)

Creating Social Value within the Delivery of Construction Projects

The purpose of this paper is to present the current knowledge surrounding social value and show how lean approach supports social value realisation in the delivery of construction projects. A critical literature review was adopted, to gather the current knowledge surrounding social value from mainstream management sciences, construction management and lean literature. A total of 70 studies were critically reviewed. The study reveals that the separation theory propagated by Friedman, (1962), tends to separate social value from economic value, thus making organisations care less about delivering social value. The study found that there is still no clear or single criterion for measuring social value delivered and there is a dearth of scholarly publications on social value especially in construction management literature. The investigation shows that lean production approach has the potentials to enable construction organisations to conceptualise the community and the physical environment where they operate as customers, which contributes to the delivery of social value objectives in construction projects. This study conceptualises the community and the physical environment around where the construction project is executed as customers using lean production approach and shows that the Transformation, Flow & Value view support smooth workflow which enhances the achievement of social value objectives. This creates a new insight into how social value can be realised in construction project delivery. This study extends the on-going debate around the need for social value in construction project delivery and contributes to construction management and lean construction literature on social value. Future studies could build on this to obtain empirical data and develop an approach/method that would support the evidencing of social value delivery in construction projects

Efficient Indicators to Evaluate the Status of Software Development Effort Estimation inside the Organizations

Development effort is an undeniable part of the project management which considerably influences the success of project. Inaccurate and unreliable estimation of effort can easily lead to the failure of project. Due to the special specifications, accurate estimation of effort in the software projects is a vital management activity that must be carefully done to avoid from the unforeseen results. However numerous effort estimation methods have been proposed in this field, the accuracy of estimates is not satisfying and the attempts continue to improve the performance of estimation methods. Prior researches conducted in this area have focused on numerical and quantitative approaches and there are a few research works that investigate the root problems and issues behind the inaccurate effort estimation of software development effort. In this paper, a framework is proposed to evaluate and investigate the situation of an organization in terms of effort estimation. The proposed framework includes various indicators which cover the critical issues in field of software development effort estimation. Since the capabilities and shortages of organizations for effort estimation are not the same, the proposed indicators can lead to have a systematic approach in which the strengths and weaknesses of organizations in field of effort estimation are discovered.Comment: 10 page

An Experimental Comparison of Three Machine Learning Techniques for Web Cost Estimation

Many comparative studies on the performance of machine learning (ML) techniques for web cost estimation (WCE) have been reported in the literature. However, not much attention have been given to understanding the conceptual differences and similarities that exist in the application of these ML techniques for WCE, which could provide credible guide for upcoming practitioners and researchers in predicting the cost of new web projects. This paper presents a comparative analysis of three prominent machine learning techniques – Case-Based Reasoning (CBR), Support Vector Regression (SVR) and Artificial Neural Network (ANN) – in terms of performance, applicability, and their conceptual differences and similarities for WCE by using data obtained from a public dataset (www.tukutuku.com). Results from experiments show that SVR and ANN provides more accurate predictions of effort, although SVR require fewer parameters to generate good predictions than ANN. CBR was not as accurate, but its good explanation attribute gives it a higher descriptive value. The study also outlined specific characteristics of the 3 ML techniques that could foster or inhibit their adoption for WCE

Creating social value within the delivery of construction projects: the role of lean approach

Purpose: The purpose of this paper is to present the current knowledge surrounding social value and show how lean approach supports social value realisation in the delivery of construction projects. Design/methodology/approach: A critical literature review was adopted, to gather the current knowledge surrounding social value from mainstream management sciences, construction management and lean literature. A total of 70 studies were critically reviewed. Findings: The study establishes that the current level of awareness on social value is still low and there is a dearth of scholarly publications on social value especially in construction management literature. The investigation reveals the potentials of lean approach in supporting the delivery of social value on construction projects. Social implication: This study conceptualises the community and the physical environment around where the construction project is executed as customers using lean production approach. It shows that the Transformation, Flow & Value view supports smooth workflow which enhances the achievement of social value objectives. This creates a new insight into how social value can be realised in construction project delivery. Originality and Value: This study extends the on-going debate around the need for social value in construction project delivery and contributes to construction management and lean construction literature on social value. Future studies could build on this to obtain empirical data and develop an approach/method that would support the evidencing of social value delivery on construction projects

Medición y estimación del software: métodos y herramientas para mejorar la calidad del software

El desarrollo de software requiere de la estimación para controlar y administrar los recursos que se necesitan utilizar antes y durante el proyecto. La estimación no es una ciencia exacta dado que existen numerosas variables humanas, técnicas, del entorno y políticas, que intervienen en su proceso y que pueden afectar los resultados finales. Sin embargo, cuando es llevada a cabo en forma sistemática, se pueden lograr resultados con un grado aceptable y convertirla en un instrumento útil para la toma de decisiones. En este trabajo se presentan las líneas de investigación y desarrollo orientadas hacia el análisis, estudio y discusión de métodos de estimación para el desarrollo de software, aplicando técnicas y herramientas que contribuyan a la gestión cuantitativa de proyectos.Eje: Ingeniería de SoftwareRed de Universidades con Carreras en Informática (RedUNCI

Medición y estimación del software: métodos y herramientas para mejorar la calidad del software

El desarrollo de software requiere de la estimación para controlar y administrar los recursos que se necesitan utilizar antes y durante el proyecto. La estimación no es una ciencia exacta dado que existen numerosas variables humanas, técnicas, del entorno y políticas, que intervienen en su proceso y que pueden afectar los resultados finales. Sin embargo, cuando es llevada a cabo en forma sistemática, se pueden lograr resultados con un grado aceptable y convertirla en un instrumento útil para la toma de decisiones. En este trabajo se presentan las líneas de investigación y desarrollo orientadas hacia el análisis, estudio y discusión de métodos de estimación para el desarrollo de software, aplicando técnicas y herramientas que contribuyan a la gestión cuantitativa de proyectos.Eje: Ingeniería de SoftwareRed de Universidades con Carreras en Informática (RedUNCI