Design is to create a product in the process that transforms “what you want” to “how you realize it”. Many design methods have been suggested in the software research community in the past. Hence, to know the differences between design methods or to understand the benefits of a single method, many papers about software design methods comparisons have been published. However, most of them are from subjective observations or designer's surveys. In other words, none of the past studies provided an objective basis for design comparison. In addition, there is no systematic and generic approach that can be applied universally to any design method or process in an empirical study. To remedy this, we proposed a Template-based Design Method Comparison Approach (TDMCA). In this paper, we explain TDMCA and demonstrate the evaluation of it. In our evaluation, we use Object-oriented (OO) system designs to validate TDMCA. Therefore, a graph-based similarity is created to measure the result. The evaluation result convinces us that TDMCA can provide the basis for objectively comparing any different design methods.

In this paper, we have described a co-construction process model, in the context of a socio-technical framework, to support the collaborative engineering design. This paper has reviewed our previous work in building a co-construction model on the conceptual, logical, and analytical layers and then proposed an expanded Petri net representation that is developed toward a more comprehensive and operational co-construction model, which captures the key conceptual components of a collaborative engineering design process, describes the possible logic flow between these components, and analyzes their interaction in the design process. In this paper, we have also discussed a case study that was conducted in a real-life engineering design to validate our research. At the end of this paper, we emphasized the importance of this study and outlined the future directions of improving this study.

Decomposition is a common practice in design of technical systems to manage abstractions and to create components that can be developed separately. However, the hierarchical decomposition methods used in current software design are unable to control the dependency and provide the traceability of decisions effectively. As the difficulty of software systems rises along with increasing demands for more function, lower cost, higher quality and shorter delivery time, this shortcoming has become a major challenge in the software design community. One reason for this shortcoming is the failure of clearly differentiating between the functional and physical notions during the design process. To remedy this deficiency, we employ the axiomatic design (AD) theory developed from engineering design to augment object-oriented software design. This paper explains the features of axiomatic design approach and compare it with traditional software design methods. A case study that compares our proposed AD-based software design results with that from traditional object-oriented design approaches is included to demonstrate its applications and benefits in software design. The results show that explicitly managing functional dependencies at early design stages and focusing on decision traceability along the design process can lead to better software systems with higher quality and maintainability.

There have been many R&D efforts in recent years to develop computer environments that directly enhance group problem-solving productivity. An example of such efforts is the computer-based Virtual Teaming Technology (VTT) currently being developed at the Knowledge-based Engineering Systems Research Laboratory (KESRL). The core software environment for KESRL's VTT is called SWIFT (System Workbench for Integrating and Facilitating Teams) and is based on the knowledge processing technology (KPT) previously developed at KESRL to support various engineering design tasks. SWIFT is a flexible environment which enables the rapid development of collaborative applications, linking workers in distributed environments, of many domains. This paper presents the overall system architecture of SWIFT, and introduces the current and future R&D efforts at KESRL in realizing SWIFT for significant industrial applications.

A time-based inductive learning approach to the problem of real-time anomaly detection is described. This approach uses sequential rules that characterize a user's behavior over time. A rulebase is used to store patterns of user activities, and anomalies are reported whenever a user's activity deviates significantly from those specified in the rules. The rules in the rulebase characterize either the sequential relationships between security audit records or the temporal properties of the records. The rules are created in two ways: they are either dynamically generated and modified by a time-based inductive engine in order to adapt to changes in a user's behavior, or they are specified by the security management to implement a site security policy. This approach allows the correlation between adjacent security events to be exploited for the purpose of greater sensitivity in anomaly detection against seemingly intractable (or erratic) activities using statistical approaches. Real-time detection of anomaly activities is possible.>