Problem Statement: Object-oriented design has become a dominant method in software industry and m... more Problem Statement: Object-oriented design has become a dominant method in software industry and many design metrics of object-oriented programs have been proposed for quality prediction, but there is no well-accepted statement on how significant those metrics are. In this study, empirical analysis is carried out to validate object-oriented design metrics for defects estimation. Approach: The Chidamber and Kemerer metrics suite is adopted to estimate the number of defects in the programs, which are extracted from a ...
Context: Lessons learned (LL) records constitute the software organization memory of successes an... more Context: Lessons learned (LL) records constitute the software organization memory of successes and failures. LL are recorded within the organization repository for future reference to optimize planning, gain experience, and elevate market competitiveness. However, manually searching this repository is a daunting task, so it is often disregarded. This can lead to the repetition of previous mistakes or even missing potential opportunities. This, in turn, can negatively affect the organization’s profitability and competitiveness. Objective: We aim to present a novel solution that provides an automatic process to recall relevant LL and to push those LL to project managers. This will dramatically save the time and effort of manually searching the unstructured LL repositories and thus encourage the LL exploitation. Method: We exploit existing project artifacts to build the LL search queries on-the-fly in order to bypass the tedious manual searching. An empirical case study is conducted to build the automatic LL recall solution and evaluate its effectiveness. The study employs three of the most popular information retrieval models to construct the solution. Furthermore, a real-world dataset of 212 LL records from 30 different software projects is used for validation. Top-k and MAP well-known accuracy metrics are used as well. Results: Our case study results confirm the effectiveness of the automatic LL recall solution. Also, the results prove the success of using existing project artifacts to dynamically build the search query string. This is supported by a discerning accuracy of about 70% achieved in the case of top-k. Conclusion: The automatic LL recall solution is valid with high accuracy. It will eliminate the effort needed to manually search the LL repository. Therefore, this will positively encourage project managers to reuse the available LL knowledge – which will avoid old pitfalls and unleash hidden business opportunities.
International Journal of Hybrid Intelligent Systems, 2009
While software development productivity has grown rapidly, the weight values assigned to count st... more While software development productivity has grown rapidly, the weight values assigned to count standard Function Point (FP) created at IBM twenty-five years ago have never been updated. This obsolescence raises critical questions about the validity of the weight ...
Open Source Software (OSS) has been a popular form in software development. In this paper, we use... more Open Source Software (OSS) has been a popular form in software development. In this paper, we use statistical approaches to derive OSS quality estimation models. Our objective is to build estimation models for the number of defects with metrics at project levels. First CATREG (Categorical regression with optimal scaling) is used to obtain quantifications of the qualitative variables. Then the independent variables are validated using the stepwise linear regression. The process is repeated to acquire optimal quantifications and final regression formula. This modeling process is performed based on data from the OSS communities and is proved to be practically valuable.
Third International Conference on Quality Software, 2003. Proceedings., 2003
Abstract A novel neuro-fuzzy constructive cost model (COCOMO) for software estimation is proposed... more Abstract A novel neuro-fuzzy constructive cost model (COCOMO) for software estimation is proposed. The model carries some of the desirable features of the neuro-fuzzy approach, such as learning ability and good interpretability, while maintaining the merits of the COCOMO model. Unlike the standard neural network approach, this model is easily validated by experts and capable of generalization. In addition, it allows inputs to be continuous-rating values and linguistic values, therefore avoiding the problem of similar ...
Developing a software product involves estimating various project parameters. This is typically d... more Developing a software product involves estimating various project parameters. This is typically done in the planning stages of the project when there is much uncertainty and very little information. Coming up with accurate estimates of effort, cost, schedule, and reliability is a critical problem faced by all software project managers. The use of estimation models and commercially available tools in
20th Ieee International Conference on Software Maintenance, Proceedings, 2004
Abstract Accurate software estimation such as cost estimation, quality estimation and risk analys... more Abstract Accurate software estimation such as cost estimation, quality estimation and risk analysis is a major issue in software project management. We present a soft computing framework to tackle this challenging problem. We first use a preprocessing neuro-fuzzy inference system to handle the dependencies among contributing factors and decouple the effects of the contributing factors into individuals. Then we use a neuro-fuzzy bank to calibrate the parameters of contributing factors. In order to extend our framework into fields ...
Abstract Software cost estimation is a crucial element in project management. Failing to use a pr... more Abstract Software cost estimation is a crucial element in project management. Failing to use a proper cost estimation method might lead to project failures. According to the Standish Chaos Report, 65% of software projects are delivered over budget or after the delivery deadline. Conducting software cost estimation in the early stages of the software life cycle is important and this would be helpful to project managers to bid on projects. In this paper, we propose a novel model to predict software effort from use case diagrams using a cascade ...
Problem Statement: Object-oriented design has become a dominant method in software industry and m... more Problem Statement: Object-oriented design has become a dominant method in software industry and many design metrics of object-oriented programs have been proposed for quality prediction, but there is no well-accepted statement on how significant those metrics are. In this study, empirical analysis is carried out to validate object-oriented design metrics for defects estimation. Approach: The Chidamber and Kemerer metrics suite is adopted to estimate the number of defects in the programs, which are extracted from a ...
Context: Lessons learned (LL) records constitute the software organization memory of successes an... more Context: Lessons learned (LL) records constitute the software organization memory of successes and failures. LL are recorded within the organization repository for future reference to optimize planning, gain experience, and elevate market competitiveness. However, manually searching this repository is a daunting task, so it is often disregarded. This can lead to the repetition of previous mistakes or even missing potential opportunities. This, in turn, can negatively affect the organization’s profitability and competitiveness. Objective: We aim to present a novel solution that provides an automatic process to recall relevant LL and to push those LL to project managers. This will dramatically save the time and effort of manually searching the unstructured LL repositories and thus encourage the LL exploitation. Method: We exploit existing project artifacts to build the LL search queries on-the-fly in order to bypass the tedious manual searching. An empirical case study is conducted to build the automatic LL recall solution and evaluate its effectiveness. The study employs three of the most popular information retrieval models to construct the solution. Furthermore, a real-world dataset of 212 LL records from 30 different software projects is used for validation. Top-k and MAP well-known accuracy metrics are used as well. Results: Our case study results confirm the effectiveness of the automatic LL recall solution. Also, the results prove the success of using existing project artifacts to dynamically build the search query string. This is supported by a discerning accuracy of about 70% achieved in the case of top-k. Conclusion: The automatic LL recall solution is valid with high accuracy. It will eliminate the effort needed to manually search the LL repository. Therefore, this will positively encourage project managers to reuse the available LL knowledge – which will avoid old pitfalls and unleash hidden business opportunities.
International Journal of Hybrid Intelligent Systems, 2009
While software development productivity has grown rapidly, the weight values assigned to count st... more While software development productivity has grown rapidly, the weight values assigned to count standard Function Point (FP) created at IBM twenty-five years ago have never been updated. This obsolescence raises critical questions about the validity of the weight ...
Open Source Software (OSS) has been a popular form in software development. In this paper, we use... more Open Source Software (OSS) has been a popular form in software development. In this paper, we use statistical approaches to derive OSS quality estimation models. Our objective is to build estimation models for the number of defects with metrics at project levels. First CATREG (Categorical regression with optimal scaling) is used to obtain quantifications of the qualitative variables. Then the independent variables are validated using the stepwise linear regression. The process is repeated to acquire optimal quantifications and final regression formula. This modeling process is performed based on data from the OSS communities and is proved to be practically valuable.
Third International Conference on Quality Software, 2003. Proceedings., 2003
Abstract A novel neuro-fuzzy constructive cost model (COCOMO) for software estimation is proposed... more Abstract A novel neuro-fuzzy constructive cost model (COCOMO) for software estimation is proposed. The model carries some of the desirable features of the neuro-fuzzy approach, such as learning ability and good interpretability, while maintaining the merits of the COCOMO model. Unlike the standard neural network approach, this model is easily validated by experts and capable of generalization. In addition, it allows inputs to be continuous-rating values and linguistic values, therefore avoiding the problem of similar ...
Developing a software product involves estimating various project parameters. This is typically d... more Developing a software product involves estimating various project parameters. This is typically done in the planning stages of the project when there is much uncertainty and very little information. Coming up with accurate estimates of effort, cost, schedule, and reliability is a critical problem faced by all software project managers. The use of estimation models and commercially available tools in
20th Ieee International Conference on Software Maintenance, Proceedings, 2004
Abstract Accurate software estimation such as cost estimation, quality estimation and risk analys... more Abstract Accurate software estimation such as cost estimation, quality estimation and risk analysis is a major issue in software project management. We present a soft computing framework to tackle this challenging problem. We first use a preprocessing neuro-fuzzy inference system to handle the dependencies among contributing factors and decouple the effects of the contributing factors into individuals. Then we use a neuro-fuzzy bank to calibrate the parameters of contributing factors. In order to extend our framework into fields ...
Abstract Software cost estimation is a crucial element in project management. Failing to use a pr... more Abstract Software cost estimation is a crucial element in project management. Failing to use a proper cost estimation method might lead to project failures. According to the Standish Chaos Report, 65% of software projects are delivered over budget or after the delivery deadline. Conducting software cost estimation in the early stages of the software life cycle is important and this would be helpful to project managers to bid on projects. In this paper, we propose a novel model to predict software effort from use case diagrams using a cascade ...
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