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This thesis proposes a new model to identify conflicts in the requirements gathering process. The... more This thesis proposes a new model to identify conflicts in the requirements gathering process. The model is based on the matrix mechanism to identify the quality based conflicts. Various models such as “Analysis of conflicts among non-functional requirements using integrated analysis of functional and non-functional requirements”, “The FRIDA Model” and “Identifying requirement conflicts and cooperation: how automated traceability can help” are studied critically in this thesis with the help of a case study using repository system of University of Southern California / Center for Software Engineering (USC/CSE). A number of limitations have been observed from the above models which are a). The automation of the models is very difficult in term of logic building b). There are many conflict identification models which only deal with the product requirements rather than process requirements c). Quality based requirement conflict identification results in the identification of false conflicts which cause over head on the negotiation process d). Most of the conflict identification models are not only difficult in paper implementation but their automation is also very difficult. The proposed model which is tested theoretically overcomes many of the above mentioned problems. The proposed model uses the matrix mechanism to identify the quality based conflicts and the conflicting quality attributes are mapped to low level functionality using the matrices to identify the potential conflicts. The proposed model achieves the simplification of automation, identification of conflicts among product and process requirements, identification of false conflicts, decreases the documentation overhead and transparent identification of conflicts. Most of these achievements are not completely under taken by most of the present models.
Conflicts identification among non-functional requirements is often identified intuitively which ... more Conflicts identification among non-functional requirements is often identified intuitively which impairs conflict analysis practices. This paper proposes a new model to identify conflicts among non-functional requirements. The proposed model uses the matrix mechanism to identify the quality based conflicts among non-functional requirements. The potential conflicts are identified through the mapping of low level conflicting quality attributes to low level functionalities using the matrices. The proposed model achieves the identification of conflicts among product and process requirements, identifies false conflicts, decreases the documentation overhead, and maintains transparency of identified conflicts. The attributes are not concomitantly taken into account by current models in practice.
Software industry has been rapidly growing from the last couple of decades. Due to this gro... more Software industry has been rapidly growing from the last couple of decades. Due to this growth and advancement many issues are going to be occurred. There are number of factors that affect the whole software development process. This research has focused on the most important risk factors that affect the overall software project and risk mitigation reviewed from the literature and my own experience. The main aim of this research is to collect the most important risk factors and risk mitigation for the development of intelligent network using an Artificial Intelligence technique known as Rule Based System. This is helpful for the project managers to make decisions. For the accomplishment of this task Firstly an exploratory survey has been conducted to prioritize the twenty requirements and fifty software risk mitigation factors. A sample of 200 respondents is selected out of which 100 are the university students and 100 are the IT professionals of a well reputed software house. Secondly a Rule Based technique is used to generate the risk mitigation intelligent network. Rules have been stored in the form of risk mitigation in relationship with risk factors. The system follows five steps of execution. First of all risk factors has been prioritized based upon the associations of risk factors and risk mitigation. Secondly, it creates new relationships between them. Thirdly, enter these relationships asrules into the Knowledge Base or Rule Base. At the fourth stage, an RBS engine executes these rules and finally an intelligent risk mitigation network is generated.
This thesis proposes a new model to identify conflicts in the requirements gathering process. The... more This thesis proposes a new model to identify conflicts in the requirements gathering process. The model is based on the matrix mechanism to identify the quality based conflicts. Various models such as “Analysis of conflicts among non-functional requirements using integrated analysis of functional and non-functional requirements”, “The FRIDA Model” and “Identifying requirement conflicts and cooperation: how automated traceability can help” are studied critically in this thesis with the help of a case study using repository system of University of Southern California / Center for Software Engineering (USC/CSE). A number of limitations have been observed from the above models which are a). The automation of the models is very difficult in term of logic building b). There are many conflict identification models which only deal with the product requirements rather than process requirements c). Quality based requirement conflict identification results in the identification of false conflicts which cause over head on the negotiation process d). Most of the conflict identification models are not only difficult in paper implementation but their automation is also very difficult. The proposed model which is tested theoretically overcomes many of the above mentioned problems. The proposed model uses the matrix mechanism to identify the quality based conflicts and the conflicting quality attributes are mapped to low level functionality using the matrices to identify the potential conflicts. The proposed model achieves the simplification of automation, identification of conflicts among product and process requirements, identification of false conflicts, decreases the documentation overhead and transparent identification of conflicts. Most of these achievements are not completely under taken by most of the present models.
Conflicts identification among non-functional requirements is often identified intuitively which ... more Conflicts identification among non-functional requirements is often identified intuitively which impairs conflict analysis practices. This paper proposes a new model to identify conflicts among non-functional requirements. The proposed model uses the matrix mechanism to identify the quality based conflicts among non-functional requirements. The potential conflicts are identified through the mapping of low level conflicting quality attributes to low level functionalities using the matrices. The proposed model achieves the identification of conflicts among product and process requirements, identifies false conflicts, decreases the documentation overhead, and maintains transparency of identified conflicts. The attributes are not concomitantly taken into account by current models in practice.
Software industry has been rapidly growing from the last couple of decades. Due to this gro... more Software industry has been rapidly growing from the last couple of decades. Due to this growth and advancement many issues are going to be occurred. There are number of factors that affect the whole software development process. This research has focused on the most important risk factors that affect the overall software project and risk mitigation reviewed from the literature and my own experience. The main aim of this research is to collect the most important risk factors and risk mitigation for the development of intelligent network using an Artificial Intelligence technique known as Rule Based System. This is helpful for the project managers to make decisions. For the accomplishment of this task Firstly an exploratory survey has been conducted to prioritize the twenty requirements and fifty software risk mitigation factors. A sample of 200 respondents is selected out of which 100 are the university students and 100 are the IT professionals of a well reputed software house. Secondly a Rule Based technique is used to generate the risk mitigation intelligent network. Rules have been stored in the form of risk mitigation in relationship with risk factors. The system follows five steps of execution. First of all risk factors has been prioritized based upon the associations of risk factors and risk mitigation. Secondly, it creates new relationships between them. Thirdly, enter these relationships asrules into the Knowledge Base or Rule Base. At the fourth stage, an RBS engine executes these rules and finally an intelligent risk mitigation network is generated.
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A number of limitations have been observed from the above models which are a). The automation of the models is very difficult in term of logic building b). There are many conflict identification models which only deal with the product requirements rather than process requirements c). Quality based requirement conflict identification results in the identification of false conflicts which cause over head on the negotiation process d). Most of the conflict identification models are not only difficult in paper implementation but their automation is also very difficult. The proposed model which is tested theoretically overcomes many of the above mentioned problems.
The proposed model uses the matrix mechanism to identify the quality based conflicts and the conflicting quality attributes are mapped to low level functionality using the matrices to identify the potential conflicts. The proposed model achieves the simplification of automation, identification of conflicts among product and process requirements, identification of false conflicts, decreases the documentation overhead and transparent identification of conflicts. Most of these achievements are not completely under taken by most of the present models.
Conference Papers by Abdul Hannan
current models in practice.
many issues are going to be occurred. There are number of factors that affect the whole software development process. This research has focused on the most important risk factors that affect the overall software project and risk mitigation reviewed from the literature and my own experience. The main aim of this research is to collect the most important risk factors and risk mitigation for the development of intelligent network using an Artificial Intelligence technique known as Rule Based System. This is helpful for the project managers to make decisions. For the accomplishment of this task Firstly an exploratory survey has been conducted to prioritize the twenty requirements and fifty software risk mitigation factors. A sample of 200 respondents is selected out of which 100 are the university students and 100 are the IT professionals of a well reputed software house. Secondly a Rule Based technique is used to generate the risk mitigation intelligent network. Rules have been stored in the form of risk mitigation in relationship with risk factors. The system follows five steps of execution. First of all risk factors has been prioritized based upon the associations of risk factors and risk mitigation. Secondly, it creates new relationships between them. Thirdly, enter these relationships asrules into the Knowledge Base or Rule Base. At
the fourth stage, an RBS engine executes these rules and finally
an intelligent risk mitigation network is generated.
A number of limitations have been observed from the above models which are a). The automation of the models is very difficult in term of logic building b). There are many conflict identification models which only deal with the product requirements rather than process requirements c). Quality based requirement conflict identification results in the identification of false conflicts which cause over head on the negotiation process d). Most of the conflict identification models are not only difficult in paper implementation but their automation is also very difficult. The proposed model which is tested theoretically overcomes many of the above mentioned problems.
The proposed model uses the matrix mechanism to identify the quality based conflicts and the conflicting quality attributes are mapped to low level functionality using the matrices to identify the potential conflicts. The proposed model achieves the simplification of automation, identification of conflicts among product and process requirements, identification of false conflicts, decreases the documentation overhead and transparent identification of conflicts. Most of these achievements are not completely under taken by most of the present models.
current models in practice.
many issues are going to be occurred. There are number of factors that affect the whole software development process. This research has focused on the most important risk factors that affect the overall software project and risk mitigation reviewed from the literature and my own experience. The main aim of this research is to collect the most important risk factors and risk mitigation for the development of intelligent network using an Artificial Intelligence technique known as Rule Based System. This is helpful for the project managers to make decisions. For the accomplishment of this task Firstly an exploratory survey has been conducted to prioritize the twenty requirements and fifty software risk mitigation factors. A sample of 200 respondents is selected out of which 100 are the university students and 100 are the IT professionals of a well reputed software house. Secondly a Rule Based technique is used to generate the risk mitigation intelligent network. Rules have been stored in the form of risk mitigation in relationship with risk factors. The system follows five steps of execution. First of all risk factors has been prioritized based upon the associations of risk factors and risk mitigation. Secondly, it creates new relationships between them. Thirdly, enter these relationships asrules into the Knowledge Base or Rule Base. At
the fourth stage, an RBS engine executes these rules and finally
an intelligent risk mitigation network is generated.