Title: An Approach for Experience Reuse within the Context of Decision Making

Abstract: Effective knowledge management (KM) is critical for organizations in the public and private sectors.  Projects success depends heavily on the experience of organizational individuals.  Much of such experience is manifested in a form of lessons learned (LL) by individuals over time.  The problem is that LL management systems (LLMSs) poorly serve their intended goal of promoting knowledge sharing and reuse.  Two reasons are paramount for this failure.  First, most lessons are described as a set of free-text fields buried in LL databases.  Second, LLMSs are typically not integrated into the organization’s projects development processes.  This seminar presents an experience reuse approach for effective experience dissemination within the context of decision making.

Title: Independent System Assurance™:  A Methodology and Environment

Abstract: The Independent System Assurance™ (ISA) is a proprietary of SONEX, Enterprises, Inc.   ISA incorporates Quality Assurance and Configuration Management into the broader Independent Verification and Validation function.  The innovative ISA™ concept, consistent with current industrial standards, introduces a repertoire of effective AI-based tools oriented on enhancing the success potential of major programs.  These tools assure Program Manager near real-time oversight and assessment of all technical, life cycle and program management activities.  This seminar presents the ISA AI-based tools along with related open research problems.

Title: Handling Imprecision and Uncertainty in Software Quality Control

Abstract: In today's software systems development, non-functional requirements (e.g., dependability, maintainability) are becoming more and more important. Simultaneously, the increasing pressure to develop software in less time and at lower costs may suggest compromising such quality features. These constraints necessitate that tools for effective and efficient quality control are available to software quality engineers. Many approaches have been suggested to build such tools. However, these approaches fail to effectively make use of variety of accessible quality-related information.  This is due to the fact that such information is characterized as being imprecise and uncertain. This seminar presents a framework that utilizes Type-2 fuzzy logic to allow effective utilization of imprecise and uncertain information during the course of quality control.

 

Title: Automatic Software Test Data Generation:  An Evolutionary Approach

Abstract: The software industry has learned over time that software testing costs a considerable amount of a software project budget.  Hence, software quality managers have been looking for solutions to reduce testing costs and time. As for black-box testing, present attempts for automating acceptance test scenarios generation rely on the requirements specification and use cases. However, the problem is that these attempts assume that exhaustive requirements specification is feasible, which is not the case. Accordingly, specification-based acceptance test scenarios generation would not be effective enough. On the other hand, present approaches for automatic generation of test cases for white-box testing have shown to be ineffectual. This seminar presents attempts for using Genetic Algorithms for automatic test data generation for acceptance testing as a form of white-box testing and for black-box testing considering path-coverage as the adequacy criterion.