2017 8th International Conference on Information Technology (ICIT), 2017
This study examines the adoption of a powerful management system known as Enterprise Resource Pla... more This study examines the adoption of a powerful management system known as Enterprise Resource Planning (ERP) with focus on Jordanian organizations. The study examined the impact of technological, internal, and external factors that influence ERP systems adoption. For this purpose, we have adopted a well known technological-organizational-environmental (TOE) framework. We used semi-structured interviews with ten companies and service providers in Jordan to collect data about using ERP. We've found that there are main factors that play significant roles in Jordanian firms' adoption of ERP systems. These findings have important implications and great value for service providers, managers, and the research community. Providers need to focus on interacting with firms in Jordan that have already adopted ERP in order to convince many others of the technology's benefits. This work is considered one of the first studies on the use of ERP systems by firms in Jordan that employs the famous TOE framework and semi-structured interviews.
The problem of spam e-mail has gained a tremendous amount of attention. Although entities tend to... more The problem of spam e-mail has gained a tremendous amount of attention. Although entities tend to use e-mail spam filter applications to filter out received spam e-mails, marketing companies still tend to send unsolicited e-mails in bulk and users still receive a reasonable amount of spam e-mail despite those filtering applications. This work proposes a new method for classifying e-mails into spam and non-spam. First, several e-mail content features are extracted and then those features are used for classifying each e-mail individually. The classification results of three different classifiers (i.e. Decision Trees, Random Forests and k-Nearest Neighbor) are combined in various voting schemes (i.e. majority vote, average probability, product of probabilities, minimum probability and maximum probability) for making the final decision. To validate our method, two different spam e-mail collections were used.
Proceedings of the 2020 6th International Conference on Computer and Technology Applications, 2020
Promoting the learning environment within Jordanian universities and maximizing the students'... more Promoting the learning environment within Jordanian universities and maximizing the students' academic gain are essential national-level problems. Since learning and teaching systems are main building bricks to grow individuals who are responsible for developing and flourishing culture and civilization for Jordanian society. Educational data mining focuses on developing new smart algorithms devoted to analyzing the resulted data from educational systems; in order to better understand students and the learning environments. In this paper, we are analyzing major factors affecting university students' performance and the effect of social media usage on them. Furthermore, predicting the students' performance by adopting different rule-based data mining algorithms like rule learner based on Repeated Incremental Pruning to Produce Error Reduction (JRIP) and a type of decision tree called (PART). We have conducted a research survey within the University of Jordan students that ...
Software defect prediction is the process of identifying new defects/bugs in software modules. So... more Software defect prediction is the process of identifying new defects/bugs in software modules. Software defect presents an error in a computer program, which is caused by incorrect code or incorrect programming logic. As a result, undiscovered defects lead to a poor quality software products. In recent years, software defect prediction has received a considerable amount of attention from researchers. Most of the previous defect detection algorithms are marred by low defect detection ratios. Furthermore, software defect prediction is very challenging problem due to the high imbalanced distribution, where the bug-free codes are much higher than defective ones. In this paper, the software defect prediction problem is formulated as a classification task, and then it examines the impact of several ensembles methods on the classification effectiveness. In addition, the best ensemble classifier will be selected to be trained again on an over-sampled datasets using the Synthetic Minority Ov...
Software defect prediction (SDP) is crucial in the early stages of defect-free software developme... more Software defect prediction (SDP) is crucial in the early stages of defect-free software development before testing operations take place. Effective SDP can help test managers locate defects and defect-prone software modules. This facilitates the allocation of limited software quality assurance resources optimally and economically. Feature selection (FS) is a complicated problem with a polynomial time complexity. For a dataset with N features, the complete search space has 2N feature subsets, which means that the algorithm needs an exponential running time to traverse all these feature subsets. Swarm intelligence algorithms have shown impressive performance in mitigating the FS problem and reducing the running time. The moth flame optimization (MFO) algorithm is a well-known swarm intelligence algorithm that has been used widely and proven its capability in solving various optimization problems. An efficient binary variant of MFO (BMFO) is proposed in this paper by using the island B...
Over the last few years, the arena of mobile application development has expanded considerably be... more Over the last few years, the arena of mobile application development has expanded considerably beyond the demand of the world's software markets. With the growing number of mobile software companies and the increasing sophistication of smartphone technology, developers have been establishing several categories of applications on dissimilar platforms. However, developers confront several challenges when undertaking mobile application projects. In particular, there is a lack of consolidated systems that can competently, promptly and efficiently provide developers with personalised services. Hence, it is essential to develop tailored systems that can recommend appropriate tools, IDEs, platforms, software components and other correlated artifacts to mobile application developers. This paper proposes a new recommender system framework comprising a robust set of techniques that are designed to provide mobile app developers with a specific platform where they can browse and search for ...
Software defect prediction is a promising approach aiming to improve software quality and testing... more Software defect prediction is a promising approach aiming to improve software quality and testing efficiency by providing timely identification of defect-prone software modules before the actual testing process begins. These prediction results help software developers to effectively allocate their limited resources to the modules that are more prone to defects. In this paper, a hybrid heterogeneous ensemble approach is proposed for the purpose of software defect prediction. Heterogeneous ensembles consist of set of classifiers of different learning base methods in which each of them has its own strengths and weaknesses. The main idea of the proposed approach is to develop expert and robust heterogeneous classification models. Two versions of the proposed approach are developed and experimented. The first is based on simple classifiers, and the second is based on ensemble ones. For evaluation, 21 publicly available benchmark datasets are selected to conduct the experiments and benchm...
The Capability Maturity Model Integration, as part of the software process improvement, has been ... more The Capability Maturity Model Integration, as part of the software process improvement, has been receiving attention due to the belief of its relevance to the customer satisfaction factor. This research aims at offering software companies in Jordan an overview of Capability Maturity Model Integration methodology and its benefits for the software industry. To study the impact of its implementation on customer satisfaction, through the quality of the software, and provide recommendations on increasing the awareness of Capability Maturity Model Integration, a quantitative study is designed. Four perspectives related to Capability Maturity Model Integration have been studied: the effect of its implementation on customer satisfaction as well as software quality, the effect of software quality on customer satisfaction, and the effect of its implementation on customer satisfaction through the software quality. The results concluded that there is a direct effect of implementing Capability Maturity Model Integration on customer satisfaction and software quality. It also shows that higher software quality positively affects customer satisfaction; i.e. software quality plays a mediation role between the effect of Capability Maturity Model Integration implementation and the customer satisfaction.
Productive firms try to deliver high-quality products to be globally competitive. Therefore, soft... more Productive firms try to deliver high-quality products to be globally competitive. Therefore, software development firms need to adhere to a set of best practices that improve their processes. Capability maturity model integration (CMMI) comprehensively assesses the maturity of a firm's processes. Representing a major departure from the traditional method of running quality management in software development firms, the adoption of CMMI has major ramifications and long-lasting effects on a company’s quality procedures. Unfortunately, the literature lacks information as to how firms should implement CMMI. Our research involved conducting an exploratory study examining the major factors that influenced CMMI adoption for Jordanian software development firms. Quality managers from eighteen software development organizations took an open-ended survey. The results show that the main factors in CMMI implementation in Jordanian software development firms were issues of its being too...
Advances in Intelligent Systems and Computing, 2017
Software defect prediction is the process of identifying new defects/bugs in software modules. So... more Software defect prediction is the process of identifying new defects/bugs in software modules. Software defect presents an error in a computer program, which is caused by incorrect code or incorrect programming logic. As a result, undiscovered defects lead to a poor quality software products. In recent years, software defect prediction has received a considerable amount of attention from researchers. Most of the previous defect detection algorithms are marred by low defect detection ratios. Furthermore, software defect prediction is very challenging problem due to the high imbalanced distribution, where the bug-free codes are much higher than defective ones. In this paper, the software defect prediction problem is formulated as a classification task, and then it examines the impact of several ensembles methods on the classification effectiveness. In addition, the best ensemble classifier will be selected to be trained again on an over-sampled datasets using the Synthetic Minority Over-sampling Technique (SMOTE) algorithm to tackle imbalanced distribution problem. The proposed hybrid method is evaluated using four software defects datasets. Experimental results demonstrate that the proposed method can effectively enhance the defect prediction accuracy.
Journal of Software Engineering and Applications, 2016
Fault localization is an important topic in software testing, as it enables the developer to spec... more Fault localization is an important topic in software testing, as it enables the developer to specify fault location in their code. One of the dynamic fault localization techniques is statistical debugging. In this study, two statistical debugging algorithms are implemented, SOBER and Cause Isolation, and then the experimental works are conducted on five programs coded using Python as an example of well-known dynamic programming language. Results showed that in programs that contain only single bug, the two studied statistical debugging algorithms are very effective to localize a bug. In programs that have more than one bug, SOBER algorithm has limitations related to nested predicates, rarely observed predicates and complement predicates. The Cause Isolation has limitations related to sorting predicates based on importance and detecting bugs in predicate condition. The accuracy of both SOBER and Cause Isolation is affected by the program size. Quality comparison showed that SOBER algorithm requires more code examination than Cause Isolation to discover the bugs.
Proceedings of the 7th Conference on 7th Wseas International Conference on Applied Computer Science Volume 7, 2007
Speaker identification applications are the highly commercialized during the speaker recognition ... more Speaker identification applications are the highly commercialized during the speaker recognition and voice biometrics applications. Like other applications it has been experiencing an increasing market and investor interest [1]. However, it is still an open area for research. In this paper we considered creating a real-time speaker identification system as an optimization problem. However, many researches proceeded in this direction. Here, we took a newly proposed technique proposed by Karpov [2] to compare our technique with it. The results, when testing both systems on ELSDSR voices database, show that the newly proposed technique is better than the old proposed one in terms of timing, memory usage and accuracy.
Context: Due to increased competition and the advent of mass customization, many software firms a... more Context: Due to increased competition and the advent of mass customization, many software firms are utilizing product families-groups of related products derived from a product platform-to provide product variety in a cost-effective manner. The key to designing a successful software product family is the product platform, so it is important to determine the most appropriate product platform scope related to business objectives, for product line development. Aim: This paper proposes a novel method to find the optimized scope of a software product platform based on end-user features. Method: The proposed method, PPSMS (Product Platform Scoping Method for Software Product Lines), mathematically formulates the product platform scope selection as an optimization problem. The problem formulation targets identification of an optimized product platform scope that will maximize life cycle cost savings and the amount of commonality, while meeting the goals and needs of the envisioned customers' segments. A simulated annealing based algorithm that can solve problems heuristically is then used to help the decision maker in selecting a scope for the product platform, by performing tradeoff analysis of the commonality and cost savings objectives. Results: In a case study, PPSMS helped in identifying 5 non-dominated solutions considered to be of highest preference for decision making, taking into account both cost savings and commonality objectives. A quantitative and qualitative analysis indicated that human experts perceived value in adopting the method in practice, and that it was effective in identifying appropriate product platform scope.
ABSTRACT Nowadays, software firms are applying the Software Product Line Engineering (SPLE) appro... more ABSTRACT Nowadays, software firms are applying the Software Product Line Engineering (SPLE) approach for its concepts of commonality and variability to provide product variety in a cost-effective manner. Yet, the effect of different amounts of component commonality on the perceived benefits from adopting SPLE is not well understood. Measuring commonality marks the starting point of precise analysis and better understanding of this relationship. In this paper, analytical tools developed in manufacturing are analyzed and adopted (i.e. Commonality Indices (CI)) in order to measure the commonality in SPLE. We used a case study of a Door Lock Control System (DLCS) for evaluating different levels of component commonality. To map the component commonality to the resulting development cost, linear regression is used to assess the relationship between the various commonality indices and the resulting development cost. This study suggests that reusing commonality indices from the manufacturing domain to assess the commonality of products in software product lines is sensible. The linear regression analysis shows that the relationship between those indices and development cost is verifiable, with high R2 value ranges between 0.81 and 0.95, and significant, at the 0.025 ~ 0.005 level.
Proceedings of the 2nd International Conference on Interaction Sciences Information Technology, Culture and Human - ICIS '09, 2009
ABSTRACT Software Product Line, SPL, is a software development strategy in which products are dev... more ABSTRACT Software Product Line, SPL, is a software development strategy in which products are developed from a common set of core assets in a prescribed way with product specific features to satisfy specific market segment [1]. The SPL development process is carried out in two phases: the first phase is about building core assets called domain engineering, which has gained a lot of researchers' attention. The second step is about instantiating the specifics of the products by adding to the common part the specific features that identify the product from the other application engineering. For large and complex domains, it is argued that organizing and retrieving the development of artifacts from the core asset required by the application under development is a way of shortening the application development time, thus reduces the time to market. In this paper, we propose an automation mechanism for organizing the core assets using feature based organization to divide the customized domain feature model based on the application features and their dependencies. When that retrieval step where the artifacts are represented by relations that inherit the dependencies between the features in each division of the feature model, takes place, the final result is a set of development artifacts with their traceability links to be customized based on the application variability model and integrated with the application specific artifacts. To demonstrate our work, we applied this mechanism on a watch, a case study in the digital watch domain.
Proceedings of the 15th International Software Product Line Conference on - SPLC '11, 2011
ABSTRACT Following the dawn of autonomic computing, self-healing systems have been considered as ... more ABSTRACT Following the dawn of autonomic computing, self-healing systems have been considered as an alternative to maintenance and evolution problems. In web-based applications, the uncertainty about the flux of users is a motivation for implementing a self-healing strategy to tackle response time fluctuations. A knowledge base is implemented to support monitoring data and recovery tactics. In this article we present a product line-based self-healing strategy for web-based applications. We present internal variation points as central elements for recovery mechanisms. We also analyze how a strategic involvement of domain knowledge can ameliorate the self-healing capability. We illustrate our approach with the case study of a hotel reservation system.
2017 8th International Conference on Information Technology (ICIT), 2017
This study examines the adoption of a powerful management system known as Enterprise Resource Pla... more This study examines the adoption of a powerful management system known as Enterprise Resource Planning (ERP) with focus on Jordanian organizations. The study examined the impact of technological, internal, and external factors that influence ERP systems adoption. For this purpose, we have adopted a well known technological-organizational-environmental (TOE) framework. We used semi-structured interviews with ten companies and service providers in Jordan to collect data about using ERP. We've found that there are main factors that play significant roles in Jordanian firms' adoption of ERP systems. These findings have important implications and great value for service providers, managers, and the research community. Providers need to focus on interacting with firms in Jordan that have already adopted ERP in order to convince many others of the technology's benefits. This work is considered one of the first studies on the use of ERP systems by firms in Jordan that employs the famous TOE framework and semi-structured interviews.
The problem of spam e-mail has gained a tremendous amount of attention. Although entities tend to... more The problem of spam e-mail has gained a tremendous amount of attention. Although entities tend to use e-mail spam filter applications to filter out received spam e-mails, marketing companies still tend to send unsolicited e-mails in bulk and users still receive a reasonable amount of spam e-mail despite those filtering applications. This work proposes a new method for classifying e-mails into spam and non-spam. First, several e-mail content features are extracted and then those features are used for classifying each e-mail individually. The classification results of three different classifiers (i.e. Decision Trees, Random Forests and k-Nearest Neighbor) are combined in various voting schemes (i.e. majority vote, average probability, product of probabilities, minimum probability and maximum probability) for making the final decision. To validate our method, two different spam e-mail collections were used.
Proceedings of the 2020 6th International Conference on Computer and Technology Applications, 2020
Promoting the learning environment within Jordanian universities and maximizing the students'... more Promoting the learning environment within Jordanian universities and maximizing the students' academic gain are essential national-level problems. Since learning and teaching systems are main building bricks to grow individuals who are responsible for developing and flourishing culture and civilization for Jordanian society. Educational data mining focuses on developing new smart algorithms devoted to analyzing the resulted data from educational systems; in order to better understand students and the learning environments. In this paper, we are analyzing major factors affecting university students' performance and the effect of social media usage on them. Furthermore, predicting the students' performance by adopting different rule-based data mining algorithms like rule learner based on Repeated Incremental Pruning to Produce Error Reduction (JRIP) and a type of decision tree called (PART). We have conducted a research survey within the University of Jordan students that ...
Software defect prediction is the process of identifying new defects/bugs in software modules. So... more Software defect prediction is the process of identifying new defects/bugs in software modules. Software defect presents an error in a computer program, which is caused by incorrect code or incorrect programming logic. As a result, undiscovered defects lead to a poor quality software products. In recent years, software defect prediction has received a considerable amount of attention from researchers. Most of the previous defect detection algorithms are marred by low defect detection ratios. Furthermore, software defect prediction is very challenging problem due to the high imbalanced distribution, where the bug-free codes are much higher than defective ones. In this paper, the software defect prediction problem is formulated as a classification task, and then it examines the impact of several ensembles methods on the classification effectiveness. In addition, the best ensemble classifier will be selected to be trained again on an over-sampled datasets using the Synthetic Minority Ov...
Software defect prediction (SDP) is crucial in the early stages of defect-free software developme... more Software defect prediction (SDP) is crucial in the early stages of defect-free software development before testing operations take place. Effective SDP can help test managers locate defects and defect-prone software modules. This facilitates the allocation of limited software quality assurance resources optimally and economically. Feature selection (FS) is a complicated problem with a polynomial time complexity. For a dataset with N features, the complete search space has 2N feature subsets, which means that the algorithm needs an exponential running time to traverse all these feature subsets. Swarm intelligence algorithms have shown impressive performance in mitigating the FS problem and reducing the running time. The moth flame optimization (MFO) algorithm is a well-known swarm intelligence algorithm that has been used widely and proven its capability in solving various optimization problems. An efficient binary variant of MFO (BMFO) is proposed in this paper by using the island B...
Over the last few years, the arena of mobile application development has expanded considerably be... more Over the last few years, the arena of mobile application development has expanded considerably beyond the demand of the world's software markets. With the growing number of mobile software companies and the increasing sophistication of smartphone technology, developers have been establishing several categories of applications on dissimilar platforms. However, developers confront several challenges when undertaking mobile application projects. In particular, there is a lack of consolidated systems that can competently, promptly and efficiently provide developers with personalised services. Hence, it is essential to develop tailored systems that can recommend appropriate tools, IDEs, platforms, software components and other correlated artifacts to mobile application developers. This paper proposes a new recommender system framework comprising a robust set of techniques that are designed to provide mobile app developers with a specific platform where they can browse and search for ...
Software defect prediction is a promising approach aiming to improve software quality and testing... more Software defect prediction is a promising approach aiming to improve software quality and testing efficiency by providing timely identification of defect-prone software modules before the actual testing process begins. These prediction results help software developers to effectively allocate their limited resources to the modules that are more prone to defects. In this paper, a hybrid heterogeneous ensemble approach is proposed for the purpose of software defect prediction. Heterogeneous ensembles consist of set of classifiers of different learning base methods in which each of them has its own strengths and weaknesses. The main idea of the proposed approach is to develop expert and robust heterogeneous classification models. Two versions of the proposed approach are developed and experimented. The first is based on simple classifiers, and the second is based on ensemble ones. For evaluation, 21 publicly available benchmark datasets are selected to conduct the experiments and benchm...
The Capability Maturity Model Integration, as part of the software process improvement, has been ... more The Capability Maturity Model Integration, as part of the software process improvement, has been receiving attention due to the belief of its relevance to the customer satisfaction factor. This research aims at offering software companies in Jordan an overview of Capability Maturity Model Integration methodology and its benefits for the software industry. To study the impact of its implementation on customer satisfaction, through the quality of the software, and provide recommendations on increasing the awareness of Capability Maturity Model Integration, a quantitative study is designed. Four perspectives related to Capability Maturity Model Integration have been studied: the effect of its implementation on customer satisfaction as well as software quality, the effect of software quality on customer satisfaction, and the effect of its implementation on customer satisfaction through the software quality. The results concluded that there is a direct effect of implementing Capability Maturity Model Integration on customer satisfaction and software quality. It also shows that higher software quality positively affects customer satisfaction; i.e. software quality plays a mediation role between the effect of Capability Maturity Model Integration implementation and the customer satisfaction.
Productive firms try to deliver high-quality products to be globally competitive. Therefore, soft... more Productive firms try to deliver high-quality products to be globally competitive. Therefore, software development firms need to adhere to a set of best practices that improve their processes. Capability maturity model integration (CMMI) comprehensively assesses the maturity of a firm's processes. Representing a major departure from the traditional method of running quality management in software development firms, the adoption of CMMI has major ramifications and long-lasting effects on a company’s quality procedures. Unfortunately, the literature lacks information as to how firms should implement CMMI. Our research involved conducting an exploratory study examining the major factors that influenced CMMI adoption for Jordanian software development firms. Quality managers from eighteen software development organizations took an open-ended survey. The results show that the main factors in CMMI implementation in Jordanian software development firms were issues of its being too...
Advances in Intelligent Systems and Computing, 2017
Software defect prediction is the process of identifying new defects/bugs in software modules. So... more Software defect prediction is the process of identifying new defects/bugs in software modules. Software defect presents an error in a computer program, which is caused by incorrect code or incorrect programming logic. As a result, undiscovered defects lead to a poor quality software products. In recent years, software defect prediction has received a considerable amount of attention from researchers. Most of the previous defect detection algorithms are marred by low defect detection ratios. Furthermore, software defect prediction is very challenging problem due to the high imbalanced distribution, where the bug-free codes are much higher than defective ones. In this paper, the software defect prediction problem is formulated as a classification task, and then it examines the impact of several ensembles methods on the classification effectiveness. In addition, the best ensemble classifier will be selected to be trained again on an over-sampled datasets using the Synthetic Minority Over-sampling Technique (SMOTE) algorithm to tackle imbalanced distribution problem. The proposed hybrid method is evaluated using four software defects datasets. Experimental results demonstrate that the proposed method can effectively enhance the defect prediction accuracy.
Journal of Software Engineering and Applications, 2016
Fault localization is an important topic in software testing, as it enables the developer to spec... more Fault localization is an important topic in software testing, as it enables the developer to specify fault location in their code. One of the dynamic fault localization techniques is statistical debugging. In this study, two statistical debugging algorithms are implemented, SOBER and Cause Isolation, and then the experimental works are conducted on five programs coded using Python as an example of well-known dynamic programming language. Results showed that in programs that contain only single bug, the two studied statistical debugging algorithms are very effective to localize a bug. In programs that have more than one bug, SOBER algorithm has limitations related to nested predicates, rarely observed predicates and complement predicates. The Cause Isolation has limitations related to sorting predicates based on importance and detecting bugs in predicate condition. The accuracy of both SOBER and Cause Isolation is affected by the program size. Quality comparison showed that SOBER algorithm requires more code examination than Cause Isolation to discover the bugs.
Proceedings of the 7th Conference on 7th Wseas International Conference on Applied Computer Science Volume 7, 2007
Speaker identification applications are the highly commercialized during the speaker recognition ... more Speaker identification applications are the highly commercialized during the speaker recognition and voice biometrics applications. Like other applications it has been experiencing an increasing market and investor interest [1]. However, it is still an open area for research. In this paper we considered creating a real-time speaker identification system as an optimization problem. However, many researches proceeded in this direction. Here, we took a newly proposed technique proposed by Karpov [2] to compare our technique with it. The results, when testing both systems on ELSDSR voices database, show that the newly proposed technique is better than the old proposed one in terms of timing, memory usage and accuracy.
Context: Due to increased competition and the advent of mass customization, many software firms a... more Context: Due to increased competition and the advent of mass customization, many software firms are utilizing product families-groups of related products derived from a product platform-to provide product variety in a cost-effective manner. The key to designing a successful software product family is the product platform, so it is important to determine the most appropriate product platform scope related to business objectives, for product line development. Aim: This paper proposes a novel method to find the optimized scope of a software product platform based on end-user features. Method: The proposed method, PPSMS (Product Platform Scoping Method for Software Product Lines), mathematically formulates the product platform scope selection as an optimization problem. The problem formulation targets identification of an optimized product platform scope that will maximize life cycle cost savings and the amount of commonality, while meeting the goals and needs of the envisioned customers' segments. A simulated annealing based algorithm that can solve problems heuristically is then used to help the decision maker in selecting a scope for the product platform, by performing tradeoff analysis of the commonality and cost savings objectives. Results: In a case study, PPSMS helped in identifying 5 non-dominated solutions considered to be of highest preference for decision making, taking into account both cost savings and commonality objectives. A quantitative and qualitative analysis indicated that human experts perceived value in adopting the method in practice, and that it was effective in identifying appropriate product platform scope.
ABSTRACT Nowadays, software firms are applying the Software Product Line Engineering (SPLE) appro... more ABSTRACT Nowadays, software firms are applying the Software Product Line Engineering (SPLE) approach for its concepts of commonality and variability to provide product variety in a cost-effective manner. Yet, the effect of different amounts of component commonality on the perceived benefits from adopting SPLE is not well understood. Measuring commonality marks the starting point of precise analysis and better understanding of this relationship. In this paper, analytical tools developed in manufacturing are analyzed and adopted (i.e. Commonality Indices (CI)) in order to measure the commonality in SPLE. We used a case study of a Door Lock Control System (DLCS) for evaluating different levels of component commonality. To map the component commonality to the resulting development cost, linear regression is used to assess the relationship between the various commonality indices and the resulting development cost. This study suggests that reusing commonality indices from the manufacturing domain to assess the commonality of products in software product lines is sensible. The linear regression analysis shows that the relationship between those indices and development cost is verifiable, with high R2 value ranges between 0.81 and 0.95, and significant, at the 0.025 ~ 0.005 level.
Proceedings of the 2nd International Conference on Interaction Sciences Information Technology, Culture and Human - ICIS '09, 2009
ABSTRACT Software Product Line, SPL, is a software development strategy in which products are dev... more ABSTRACT Software Product Line, SPL, is a software development strategy in which products are developed from a common set of core assets in a prescribed way with product specific features to satisfy specific market segment [1]. The SPL development process is carried out in two phases: the first phase is about building core assets called domain engineering, which has gained a lot of researchers' attention. The second step is about instantiating the specifics of the products by adding to the common part the specific features that identify the product from the other application engineering. For large and complex domains, it is argued that organizing and retrieving the development of artifacts from the core asset required by the application under development is a way of shortening the application development time, thus reduces the time to market. In this paper, we propose an automation mechanism for organizing the core assets using feature based organization to divide the customized domain feature model based on the application features and their dependencies. When that retrieval step where the artifacts are represented by relations that inherit the dependencies between the features in each division of the feature model, takes place, the final result is a set of development artifacts with their traceability links to be customized based on the application variability model and integrated with the application specific artifacts. To demonstrate our work, we applied this mechanism on a watch, a case study in the digital watch domain.
Proceedings of the 15th International Software Product Line Conference on - SPLC '11, 2011
ABSTRACT Following the dawn of autonomic computing, self-healing systems have been considered as ... more ABSTRACT Following the dawn of autonomic computing, self-healing systems have been considered as an alternative to maintenance and evolution problems. In web-based applications, the uncertainty about the flux of users is a motivation for implementing a self-healing strategy to tackle response time fluctuations. A knowledge base is implemented to support monitoring data and recovery tactics. In this article we present a product line-based self-healing strategy for web-based applications. We present internal variation points as central elements for recovery mechanisms. We also analyze how a strategic involvement of domain knowledge can ameliorate the self-healing capability. We illustrate our approach with the case study of a hotel reservation system.
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