Search-based system architecture development using a holistic modeling approach

This dissertation presents an innovative approach to system architecting where search algorithms are used to explore design trade space for good architecture alternatives. Such an approach is achieved by integrating certain model construction, alternative generation, simulation, and assessment processes into a coherent and automated framework. This framework is facilitated by a holistic modeling approach that combines the capabilities of Object Process Methodology (OPM), Colored Petri Net (CPN), and feature model. The resultant holistic model can not only capture the structural, behavioral, and dynamic aspects of a system, allowing simulation and strong analysis methods to be applied, it can also specify the architectural design space. Both object-oriented analysis and design (OOA/D) and domain engineering were exploited to capture design variables and their domains and define architecture generation operations. A fully realized framework (with genetic algorithms as the search algorithm) was developed. Both the proposed framework and its suggested implementation, including the proposed holistic modeling approach and architecture alternative generation operations, are generic. They are targeted at systems that can be specified using object-oriented or process-oriented paradigm. The broad applicability of the proposed approach is demonstrated on two examples. One is the configuration of reconfigurable manufacturing systems (RMSs) under multi-objective optimization and the other is the architecture design of a manned lunar landing system for the Apollo program. The test results show that the proposed approach can cover a huge number of architecture alternatives and support the assessment of several performance measures. A set of quality results was obtained after running the optimization algorithm following the proposed framework --Abstract, page iii

Predicting companies stock price direction by using sentiment analysis of news articles

This paper summarizes our experience teaching several courses at Metropolitan College of Boston University Computer Science department over five years. A number of innovative teaching techniques are presented in this paper. We specifically address the role of a project archive, when designing a course. This research paper explores survey results from every running of courses, from 2014 to 2019. During each class, students participated in two distinct surveys: first, dealing with key learning outcomes, and, second, with teaching techniques used. This paper makes several practical recommendations based on the analysis of collected data. The research validates the value of a sound repository of technical term projects and the role such repository plays in effective teaching and learning of computer science courses.Published versio

A method for using business process models in the elicitation of user stories

Agile software development projects often manage user requirements with models that are called user stories. Approaches for eliciting user stories from customer’s existing documentation are missing. Furthermore, proper understanding of user story’s context requires an understanding of execution-order and integration dependencies among user stories, which are also missing. In this thesis we propose so-called BuPUS method which 1) facilitates elicitation of user stories from existing business process models, and 2) supports better understanding of execution-order and integration dependencies among user stories from customer’s existing documentation. The method associates user stories with corresponding BPMN’s activity elements, or with corresponding text-written use case model’s events. We defined three levels of association granularity: a user story can be more abstract, approximately equal to, or more detailed than its associated business process model’s event/activity element. In our experiments we evaluated these three levels. We run two experiments. We applied comprehension, problem-solving and recall tasks to evaluate the hypotheses which refer to understanding of the dependencies. On the other hand, we measured user story elicitation’s effectiveness with counting correctly defined user stories. The statistical results provide support for eight out of eleven of the hypotheses. The results of our first experiment show, that understanding of the execution-order and integration dependencies among user stories, when associated business process models are available, is significantly greater. In our second experiment, we compared text-written use case model and BPMN model. There appears to be greater understanding of the execution-order dependencies when using BPMN models, while there were no significant differences in understanding integration dependencies. Similarly, for the elicitation of user stories there are no significant differences when using either of the mentioned models

A method for using business process models in the elicitation of user stories

Agile software development projects often manage user requirements with models that are called user stories. Approaches for eliciting user stories from customer’s existing documentation are missing. Furthermore, proper understanding of user story’s context requires an understanding of execution-order and integration dependencies among user stories, which are also missing. In this thesis we propose so-called BuPUS method which 1) facilitates elicitation of user stories from existing business process models, and 2) supports better understanding of execution-order and integration dependencies among user stories from customer’s existing documentation. The method associates user stories with corresponding BPMN’s activity elements, or with corresponding text-written use case model’s events. We defined three levels of association granularity: a user story can be more abstract, approximately equal to, or more detailed than its associated business process model’s event/activity element. In our experiments we evaluated these three levels. We run two experiments. We applied comprehension, problem-solving and recall tasks to evaluate the hypotheses which refer to understanding of the dependencies. On the other hand, we measured user story elicitation’s effectiveness with counting correctly defined user stories. The statistical results provide support for eight out of eleven of the hypotheses. The results of our first experiment show, that understanding of the execution-order and integration dependencies among user stories, when associated business process models are available, is significantly greater. In our second experiment, we compared text-written use case model and BPMN model. There appears to be greater understanding of the execution-order dependencies when using BPMN models, while there were no significant differences in understanding integration dependencies. Similarly, for the elicitation of user stories there are no significant differences when using either of the mentioned models