Refinement methods for software architecture design using the software architecture model

Modern software systems are often large and complicated. To better understand, develop, and manage large software systems, researchers have studied software architectures that provide the top level overall structural design of software systems for the last decade. One major research focus on software architectures is formal architecture description languages, but most existing research focuses primarily on the descriptive capability and puts less emphasis on software architecture design methods and formal analysis techniques, which are necessary to develop correct software architecture design. ^ Refinement is a general approach of adding details to a software design. A formal refinement method can further ensure certain design properties. This dissertation proposes refinement methods, including a set of formal refinement patterns and complementary verification techniques, for software architecture design using Software Architecture Model (SAM), which was developed at Florida International University. First, a general guideline for software architecture design in SAM is proposed. Second, specification construction through property-preserving refinement patterns is discussed. The refinement patterns are categorized into connector refinement, component refinement and high-level Petri nets refinement. These three levels of refinement patterns are applicable to overall system interaction, architectural components, and underlying formal language, respectively. Third, verification after modeling as a complementary technique to specification refinement is discussed. Two formal verification tools, the Stanford Temporal Prover (STeP) and the Simple Promela Interpreter (SPIN), are adopted into SAM to develop the initial models. Fourth, formalization and refinement of security issues are studied. A method for security enforcement in SAM is proposed. The Role-Based Access Control model is formalized using predicate transition nets and Z notation. The patterns of enforcing access control and auditing are proposed. Finally, modeling and refining a life insurance system is used to demonstrate how to apply the refinement patterns for software architecture design using SAM and how to integrate the access control model. ^ The results of this dissertation demonstrate that a refinement method is an effective way to develop a high assurance system. The method developed in this dissertation extends existing work on modeling software architectures using SAM and makes SAM a more usable and valuable formal tool for software architecture design. ^

Examining argumentative coherence in essays by undergraduate students of English as a foreign language in Mainland China and their English speaking peers in the United States

I conducted this study to provide insights toward deepening understanding of association between culture and writing by building, assessing, and refining a conceptual model of second language writing. To do this, I examined culture and coherence as well as the relationship between them through a mixed methods research design. Coherence has been an important and complex concept in ESL/EFL writing. I intended to study the concept of coherence in the research context of contrastive rhetoric, comparing the coherence quality in argumentative essays written by undergraduates in Mainland China and their U.S. peers. In order to analyze the complex concept of coherence, I synthesized five linguistic theories of coherence: Halliday and Hasan's cohesion theory, Carroll's theory of coherence, Enkvist's theory of coherence, Topical Structure Analysis, and Toulmin's Model. Based upon the synthesis, 16 variables were generated. Across these 16 variables, Hotelling t-test statistical analysis was conducted to predict differences in argumentative coherence between essays written by two groups of participants. In order to complement the statistical analysis, I conducted 30 interviews of the writers in the studies. Participants' responses were analyzed with open and axial coding. By analyzing the empirical data, I refined the conceptual model by adding more categories and establishing associations among them. The study found that U.S. students made use of more pronominal reference. Chinese students adopted more lexical devices of reiteration and extended paralleling progression. The interview data implied that the difference may be associated with the difference in linguistic features and rhetorical conventions in Chinese and English. As far as Toulmin's Model is concerned, Chinese students scored higher on data than their U.S. peers. According to the interview data, this may be due to the fact that Toulmin's Model, modified as three elements of arguments, have been widely and long taught in Chinese writing instruction while U.S. interview participants said that they were not taught to write essays according to Toulmin's Model. Implications were generated from the process of textual data analysis and the formulation of structural model defining coherence. These implications were aimed at informing writing instruction, assessment, peer-review, and self-revision.

Event mining for system and service management

Modern IT infrastructures are constructed by large scale computing systems and administered by IT service providers. Manually maintaining such large computing systems is costly and inefficient. Service providers often seek automatic or semi-automatic methodologies of detecting and resolving system issues to improve their service quality and efficiency. This dissertation investigates several data-driven approaches for assisting service providers in achieving this goal. The detailed problems studied by these approaches can be categorized into the three aspects in the service workflow: 1) preprocessing raw textual system logs to structural events; 2) refining monitoring configurations for eliminating false positives and false negatives; 3) improving the efficiency of system diagnosis on detected alerts. Solving these problems usually requires a huge amount of domain knowledge about the particular computing systems. The approaches investigated by this dissertation are developed based on event mining algorithms, which are able to automatically derive part of that knowledge from the historical system logs, events and tickets. ^ In particular, two textual clustering algorithms are developed for converting raw textual logs into system events. For refining the monitoring configuration, a rule based alert prediction algorithm is proposed for eliminating false alerts (false positives) without losing any real alert and a textual classification method is applied to identify the missing alerts (false negatives) from manual incident tickets. For system diagnosis, this dissertation presents an efficient algorithm for discovering the temporal dependencies between system events with corresponding time lags, which can help the administrators to determine the redundancies of deployed monitoring situations and dependencies of system components. To improve the efficiency of incident ticket resolving, several KNN-based algorithms that recommend relevant historical tickets with resolutions for incoming tickets are investigated. Finally, this dissertation offers a novel algorithm for searching similar textual event segments over large system logs that assists administrators to locate similar system behaviors in the logs. Extensive empirical evaluation on system logs, events and tickets from real IT infrastructures demonstrates the effectiveness and efficiency of the proposed approaches.^

The refinement and validation of the critical decision making and problem solving scale moral dilema (CDP-MD)

This thesis extended previous research on critical decision making and problem solving by refining and validating a measure designed to assess the use of critical thinking and critical discussion in sociomoral dilemmas. The purpose of this thesis was twofold: 1) to refine the administration of the Critical Thinking Subscale of the CDP to elicit more adequate responses and for purposes of refining the coding and scoring procedures for the total measure, and 2) to collect preliminary data on the initial reliabilities of the measure. Subjects consisted of 40 undergraduate students at Florida International University. Results indicate that the use of longer probes on the Critical Thinking Subscale was more effective in eliciting adequate responses necessary for coding and evaluating the subjects performance. Analyses on the psychometric properties of the measure consisted of test-retest reliability and inter-rater reliability.

Critical problem solving scale : creating and choosing alternative solutions

This thesis extends previous research on critical decision making and problem-solving by refining and validating a self-report measure designed to assess the use of critical decision making and problem solving in making life choices. The analysis was conducted by performing two studies, and therefore collecting two sets of data on the psychometric properties of the measure. Psychometric analyses included: item analysis, internal consistency reliability, interrater reliability, and an exploratory factor analysis. This study also included regression analysis with the Wonderlic, an established measure of general intelligence, to provide preliminary evidence for the construct validity of the measure.

The relationship between the teacher's experience, the teacher's college major, and the teacher's level of education in predicting classroom attitudes in high school science students

A review of the literature reveals few research has attempted to demonstrate if a relationship exists between the type of teacher training a science teacher has received and the perceived attitudes of his/her students. Considering that a great deal of time and energy has been devoted by university colleges, school districts, and educators towards refining the teacher education process, it would be more efficient for all parties involved, if research were available that could discern if certain pathways in achieving that education, would promote the tendency towards certain teacher behaviors occurring in the classroom, while other pathways would lead towards different behaviors. Some of the teacher preparation factors examined in this study include the college major chosen by the science teacher, the highest degree earned, the number of years of teaching experience, the type of science course taught, and the grade level taught by the teacher. This study examined how the various factors mentioned, could influence the behaviors which are characteristic of the teacher, and how these behaviors could be reflective in the classroom environment experienced by the students. The instrument used in the study was the Classroom Environment Scale (CES), Real Form. The measured classroom environment was broken down into three separate dimensions, with three components within each dimension in the CES. Multiple Regression statistical analyses examined how components of the teachers' education influenced the perceived dimensions of the classroom environment from the students. The study occurred in Miami-Dade County Florida, with a predominantly urban high school student population. There were 40 secondary science teachers involved, each with an average of 30 students. The total number of students sampled in the study was 1200. The teachers who participated in the study taught the entire range of secondary science courses offered at this large school district. All teachers were selected by the researcher so that a balance would occur in the sample between teachers who were education major versus science major. Additionally, the researcher selected teachers so that a balance occurred in regards to the different levels of college degrees earned among those involved in the study. Several research questions sought to determine if there was significant difference between the type of the educational background obtained by secondary science teachers and the students' perception of the classroom environment. Other research questions sought to determine if there were significant differences in the students' perceptions of the classroom environment for secondary science teachers who taught biological content, or non-biological content sciences. An additional research question sought to evaluate if the grade level taught would affect the students' perception of the classroom environment. Analysis of the multiple regression were run for each of four scores from the CES, Real Form. For score 1, involvement of students, the results showed that teachers with the highest number of years of experience, with masters or masters plus degrees, who were education majors, and who taught twelfth grade students, had greater amounts of students being attentive and interested in class activities, participating in discussions, and doing additional work on their own, as compared with teachers who had lower experience, a bachelors degree, were science majors, and who taught a grade lower than twelfth. For score 2, task orientation, which emphasized completing the required activities and staying on-task, the results showed that teachers with the highest and intermediate experience, a science major, and with the highest college degree, showed higher scores as compared with the teachers indicating lower experiences, education major and a bachelors degree. For Score 3, competition, which indicated how difficult it was to achieve high grades in the class, the results showed that teachers who taught non-biology content subjects had the greatest effect on the regression. Teachers with a masters degree, low levels of experience, and who taught twelfth grade students were also factored into the regression equation. For Score 4, innovation, which indicated the extent in which the teachers used new and innovative techniques to encourage diverse and creative thinking included teachers with an education major as the first entry into the regression equation. Teachers with the least experience (0 to 3 years), and teachers who taught twelfth and eleventh grade students were also included into the regression equation.