software remodularization consists in reorganizing software entities into modules such that pairs of entities belonging to the same modules are more similar than those belonging to different modules. In recent years, ...
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software remodularization consists in reorganizing software entities into modules such that pairs of entities belonging to the same modules are more similar than those belonging to different modules. In recent years, Search-based software engineering (SBSE) approach has gained unprecedented growth for solving software remodularization problem. Most of the previous studies remodularize the software system by optimizing the structural coupling and cohesion metrics as objective functions. These metrics are defined in terms of the number of structural relationships counts, rather than taking patterns of relationships. It has been observed that the computation of coupling and cohesion based on patterns of relationships (i.e., information-theory based) are more accurate than the number of relationships. This paper proposes an information-theoretic software remodularization where an entropy-based similarity measure is introduced as an objective function along with other objective functions i.e., inter-module class change coupling, intra-module class change coupling, module size index (MSI), and module count index (MCI) and is further optimized using many-objective meta-heuristic algorithm. To evaluate the effectiveness of the proposed approach, seven object-oriented software systems have been remodularized using NSGA-III, MOEA/D, IBEA, and TAA algorithms. The results are compared with existing multi-objective formulation of remodularization problem in terms of authoritative software remodularization, non-extreme distribution, and stability. The experimentation results suggest that the proposed approach can be a good alternative to improve the quality of software systems. The findings suggest that the approach is more suitable for generating remodularization solution good from both quality metrics and developers perspective.
Mutation testing is an effective adequacy criteria and has been researched upon a lot in the past decades, but lacks practical application due to its high cost. Mutation testing for test data generation has not been s...
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ISBN:
(纸本)9781479980475
Mutation testing is an effective adequacy criteria and has been researched upon a lot in the past decades, but lacks practical application due to its high cost. Mutation testing for test data generation has not been studied much. This paper is an up-to-date review of the technologies that have been applied with mutation testing for automatic generation of test data which is optimized regarding time, cost and code coverage. The survey reveals an increase in interest regarding the meta-heuristic techniques along with mutation testing.
softwareengineering is decision intensive. Evidence-based software engineering is suggested for decision-making concerning the use of methods and technologies when developing software. software development often incl...
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softwareengineering is decision intensive. Evidence-based software engineering is suggested for decision-making concerning the use of methods and technologies when developing software. software development often includes the reuse of software assets, for example, open-source components. Which components to use have implications on the quality of the software (e.g., maintainability). Thus, research is needed to support decision-making for composite software. This paper presents a roadmap for research required to support evidence-based decision-making for choosing and integrating assets in composite software systems. The roadmap is developed as an output from a 5-year project in the area, including researchers from three different organizations. The roadmap is developed in an iterative process and is based on (1) systematic literature reviews of the area;(2) investigations of the state of practice, including a case survey and a survey;and (3) development and evaluation of solutions for asset identification and selection. The research activities resulted in identifying 11 areas in need of research. The areas are grouped into two categories: areas enabling evidence-based decision-making and those related to supporting the decision-making. The roadmap outlines research needs in these 11 areas. The research challenges and research directions presented in this roadmap are key areas for further research to support evidence-based decision-making for composite software.
Efforts to support high performance computing (HPC) applications' requirements in the context of cloud computing have motivated us to design HPC Shelf, a cloud computing services platform to build and deploy large...
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Efforts to support high performance computing (HPC) applications' requirements in the context of cloud computing have motivated us to design HPC Shelf, a cloud computing services platform to build and deploy large-scale parallel computing systems. We introduce Alite, the contextual contract system of HPC Shelf, to select component implementations according to requirements of the host application, target parallel computing platform characteristics (e.g., clusters and MPPs), quality of service (QoS) properties, and cost restrictions. It is evaluated through a small-scale case study employing two complementary component-based frameworks. The first one aims to represent components that implement linear algebra computations based on the BLAS interface. In turn, the second one aims to represent parallel computing platforms on the IaaS cloud offered by Amazon EC2 Service.
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