Evolving Legacy System\u27s Features into Fine-grained Components Using Regression Test-Cases

Because many software systems used for business today are considered legacy systems, the need for software evolution techniques has never been greater. We propose a novel evolution methodology for legacy systems that integrates the concepts of features, regression testing, and Component-Based Software Engineering (CBSE). Regression test suites are untapped resources that contain important information about the features of a software system. By exercising each feature with its associated test cases using code profilers and similar tools, code can be located and refactored to create components. The unique combination of Feature Engineering and CBSE makes it possible for a legacy system to be modernized quickly and affordably. We develop a new framework to evolve legacy software that maps the features to software components refactored from their feature implementation. In this dissertation, we make the following contributions: First, a new methodology to evolve legacy code is developed that improves the maintainability of evolved legacy systems. Second, the technique describes a clear understanding between features and functionality, and relationships among features using our feature model. Third, the methodology provides guidelines to construct feature-based reusable components using our fine-grained component model. Fourth, we bridge the complexity gap by identifying feature-based test cases and developing feature-based reusable components. We show how to reuse existing tools to aid the evolution of legacy systems rather than re-writing special purpose tools for program slicing and requirement management. We have validated our approach on the evolution of a real-world legacy system. By applying this methodology, American Financial Systems, Inc. (AFS), has successfully restructured its enterprise legacy system and reduced the costs of future maintenance

A sequential addition and migration method for generating microstructures of short fibers with prescribed length distribution

We describe an algorithm for generating fiber-filled volume elements for use in computational homogenization schemes. The algorithm permits to prescribe both a length distribution and a fiber-orientation tensor of second order, and composites with industrial filler fraction can be generated. Typically, for short-fiber composites, data on the fiber-length distribution and on the volume-weighted fiber-orientation tensor of second order is available. We consider a model where the fiber orientation and the fiber length distributions are independent, i.e., uncoupled. We discuss the use of closure approximations for this case and report on identifying the describing parameters of the frequently used Weibull distribution for modeling the fiber-length distribution. We discuss how to integrate these procedures in the Sequential Addition and Migration algorithm, developed for fibers of equal length, and work out algorithmic modifications accounting for possibly rather long fibers. We investigate the capabilities of the introduced methodology for industrial short-fiber composites, demonstrating the rather low dispersion of the effective elastic moduli for the generated unit cells

Economic Analysis of Tradeoffs Between Security and Disaster Recovery

The threat of computer crime is increasingly becoming a big concern for organizations. Organizations have to continuously manage their investment in information security technologies in an attempt to minimize the damage caused by information resource breaches. This article proposes an economic model in an attempt to evaluate the trade-offs between security and disaster-recovery technologies. The article intends to provide a directional strategy for managers in terms of increasing budgetary allocations for each of these technologies. The proposed model presents insights for managers

Is More Information Better? The Effect of Traders\u27 Irrational Behavior on an Artificial Stock Market

This paper presents a computer simulated artificial stock market to examine market rationality issues. We constructeconomicagentswithdifferentdegreesofirrationalitytoparticipateinthestockmarket. Theagents replicate the irrational behaviors described in the psychology and finance literatures and determine the outcome of the market. The main focus of this study is to examine the two contradicting (efficient market versus noise trading) finance hypotheses in the presence of rational and irrational traders

The Experimental Analysis of Information Security Management Issues for Online Financial Services

E-commerce offers the banking industry great opportunity, but also creates a set of new risks and vulnerability such as security threats. Information security, therefore, is an essential management and technical requirement for any efficient and effective financial activities over the Internet. Still, its definition is a complex endeavor due to the constant technological and business change and requires a coordinated match of managerial and technical solutions. This research intends to provide an instrument to test and evaluate the strategies to counter threats facing online financial institutions through an artificial economic setup at the Synthetic Environments for Simulation and Analysis (SEAS) laboratory at the Krannert Graduate School of Management, Purdue University. The research also intends to provide guidelines for forming information security policies and strategies for survival and success in the dynamic and hostile business environment. Initial results indicate that online banks that were proactive in recognizing the threats and devising policies to counter them generated greater revenue and were able to focus on the core activities. Public disclosure of security breaches by the victim banks resulted in better overall health of the simulated economy. The simulation is still in its development and testing phase and the research team intends to present the findings at the conference

The Content Manager: A tool to develop multilingual and multi-prefernce web sites

In this experience paper we outline our experience in developing a multilingual and multiple preference web site. In particular we describe Content Manager, a tool we developed to support the implementation of a business to consumer (B2C) international web site. We also describe the business requirements and challenges that we encountered. There are many commercial tools for managing a web site’s content, but these tools are unable to manage the complexity of diverse languages taxation frameworks, and cultural systems. We found that by separating the content from the source code (as supposed to embedding text within the web page), we were able to focus on the development of the web site instead of worrying about the differences between target countries. Content Manager allowed us to maintain this separation and eased the development process

Selective excitation of the LP11 mode in step index fiber using a phase mask

We present a novel mode selective coupling technique for step index fiber. This technique utilizes phase matching for excitation of higher-order modes while suppressing the fundamental mode. Using this technique, a phase element is fabricated and tested to demonstrate the high coupling efficiency to the LP11 mode. In addition, we derive an analytical expression of the coupling efficiency of the LP11 using a single phase element