The Software Development Project Scheduling Problem is similar to the well-known Resource-Constrained Multi-Project Scheduling Problem (RCMPSP). It consists in determining a schedule of tasks taking into consideration resource availabilities and precedence constraints, while optimizing an objective. Like RCMPSP, it is an NP-hard problem. In this paper, a task segmentation scheme to schedule a software development project is proposed and the average duration of the multiple concurrent projects is minimized using the Particle Swarm Optimization (PSO) meta-heuristic. PSO is a recent meta-heuristic algorithm, known for its simplicity in programming and its rapid convergence. A series of experiments show optimum results for several software development schedule scenarios.

In the area of plant monitoring and operations, concurrency stems from various kinds of actions taken by different participants with different missions or roles. In developing a system for supporting it, a key issue is to identify the specifics of concurrency in the business process. By applying the framework of domain analysis, modeling and engineering, a domain model to specify the process is developed. The authors' method consists of SPECgram (System Perspective Capture Diagram) and CARDgram (Collaborative Action-Reaction Diagram). SPECgram identifies the structure of the domain with the focus on the relationship between the plant and the business process for monitoring and operating it. CARDgram specifies resources shared by the agents and the nature of "cooperation" among them. Agents cooperate by recognizing the missions and actions of the other agents. This "mission traversable" cooperation among the agents is also modeled.

The authors present the Triadic Domain Model (TDM)-based system development environment. The main purpose is to integrate system specification, system design and system implementation of a software system using domain specific properties. TDM consists of a domain problem model, domain product model and domain process model.>

The paper describes an application of artificial intelligence technology to the implementation of a rapid prototyping method in object-oriented performance design (OOPD) for real-time systems. OOPD consists of two prototyping phases for real-time systems. Each of these phases consists of three steps: prototype construction, prototype execution, and prototype evaluation. We present artificial intelligence based methods and tools to be applied to the individual steps. In the prototype construction step, a rapid construction mechanism using reusable software components is implemented based on planning. In the prototype execution step, a hybrid inference mechanism is used to execute the constructed prototype described in declarative knowledge representation. MENDEL, which is a Prolog based concurrent object-oriented language, can be used as a prototype construction tool and a prototype execution tool. In the prototype evaluation step, an expert system which is based on qualitative reasoning is implemented to detect and diagnose bottlenecks and generate an improvement plan for them.>

A software prototyping environment called TransObj (TRANSaction and OBJect) is used for designing real-time Transaction-based Concurrent Software Systems (TCSS). In a TCSS design process, a software designer should perform both functional design and performance design. The designer should change his design view from a transaction-based paradigm to an object-based paradigm during the TCSS design process. Recognition of re-entrant functional objects and serially reusable functional objects in the TCSS should be required. TransObj includes the Stepwise Prototyping Method (SPM), and two SPM-based tools: Prolog-based TransObj (P-TransObj) and GPSS-based TransObj (G-TransObj). SPM enables the designer to advance both functional design and performance design for the TCSS prototype as controling the change of design view paradigms. P-TransObj mainly checks the prototype in a microscopic view on a personal computer. G-TransObj mainly checks the same prototype with a longer time span on a large-scale computer.

The qualitative method is proposed for parameter tuning of synchronized queuing network bottlenecks (SQN). The bottleneck diagnosis expert system for SQN (BDES-S) can carry out parameter tuning in order to diagnose and improve bottlenecks of SQN. BDES-S can produce several alternative qualitative improvement plans for the bottleneck. BDES-S is a novel system for applying the qualitative reasoning to the SQN. >