Software Process Improvement in Very Small Entities: An investigation of Software Development Knowledge Management and Team issues in maintaining and evolving software process and process improvement.

technique at both management and team level in software development VSEs. These methods assisted the researchers in examining the attitude and perceptions of practitioners towards the research issues. The researchers also made use of survey questionnaires in VSEs in order to gain more input and to validate the qualitative data. The findings from the first stage analysis (qualitative analysis), in which the content analysis and grounded theory coding approaches were used, show the pattern and detailed categories that influence and are related with the software process and process improvement in VSEs. These categories are related to each other and allow the researchers to produce and validate the studies theoretical model. Likewise the second stage analysis (quantitative analysis) assisted the researchers in conforming and enhancing the first stage findings. This investigation shows that SPI programmes in VSEs are being undertaken in a very informal manner and also in indirect ways. The primary reasons identified for the informal nature of VSE SPI are due to cost, time, customer and company size, which give a higher priority to the product rather than process. In relation to teams, the small team size coupled with the working and management style have lead VSEs to be more informal in their knowledge management process and team organization. Moreover VSEs are largely ignoring the best practice SPI models. The reasons and acceptance criteria for this are discussed. This research also confirmed that SPI does not solely depend on technology but also the contributions of human aspects have a strong emphasize, especially in VSEs. Therefore a contribution of this research is to provide an extended knowledge and understanding of SPI research area in general and within VSEs domain in particular

Coordinated constraint relaxation using a distributed agent protocol

The interactions among agents in a multi-agent system for coordinating a distributed, problem solving task can be complex, as the distinct sub-problems of the individual agents are interdependent. A distributed protocol provides the necessary framework for specifying these interactions. In a model of interactions where the agents' social norms are expressed as the message passing behaviours associated with roles, the dependencies among agents can be specified as constraints. The constraints are associated with roles to be adopted by agents as dictated by the protocol. These constraints are commonly handled using a conventional constraint solving system that only allows two satisfactory states to be achieved - completely satisfied or failed. Agent interactions then become brittle as the occurrence of an over-constrained state can cause the interaction between agents to break prematurely, even though the interacting agents could, in principle, reach an agreement. Assuming that the agents are capable of relaxing their individual constraints to reach a common goal, the main issue addressed by this thesis is how the agents could communicate and coordinate the constraint relaxation process. The interaction mechanism for this is obtained by reinterpreting a technique borrowed from the constraint satisfaction field, deployed and computed at the protocol level.The foundations of this work are the Lightweight Coordination Calculus (LCC) and the distributed partial Constraint Satisfaction Problem (CSP). LCC is a distributed interaction protocol language, based on process calculus, for specifying and executing agents' social norms in a multi-agent system. Distributed partial CSP is an extension of partial CSP, a means for managing the relaxation of distributed, over-constrained, CSPs. The research presented in this thesis concerns how distributed partial CSP technique, used to address over-constrained problems in the constraint satisfaction field, could be adopted and integrated within the LCC to obtain a more flexible means for constraint handling during agent interactions. The approach is evaluated against a set of overconstrained Multi-agent Agreement Problems (MAPs) with different levels of hardness. Not only does this thesis explore a flexible and novel approach for handling constraints during the interactions of heterogeneous and autonomous agents participating in a problem solving task, but it is also grounded in a practical implementation

NUMERICAL SIMULATION OF NATURAL CONVECTION HEAT TRANSFER IN NANOFLUIDS

The goal of this thesis is to model the behavior of the nanofluids so that their performances can be evaluated analytically and computationally. In this thesis, we consider analytical models that describe molecular viscosity f.!, thermal conductivity k. density p, specific heat c" and the coefficient of thermal expansion f3 for a nanofluid in terms of volume fraction ljJ of nanoparticles, size of the nanoparticles (e.g radius of the nanoparticle, rp), size of the base fluid molecule (e.g. radius of the liquid molecule, r1) and the temperature T. In order to validate these analytical models, we study numerically the natural convection heat transfer in a closed pipe using the commercially available CFD software FLUENT 6.0, since the experimental data is available for this configuration. In particular, we study the natural convection flow field in two configurations of L/0=0.5 and LID=l.O, where L is the length of the pipe and D is the diameter. For nanofluids, we consider the suspensions of Ab03 and CuO particles in water. Three cases with volume fraction ljJ = 0, l% and 4% for both AhOJ and CuO are considered. It is assumed that the nanoparticles of AbOJ or CuO are uniformly suspended in water; there is no aggregation of nanoparticles in the fluid medium. It is shown that the use of experimentally measured values of k. or the kinetic model of k, gives better correlation with experimental data for heat transfer compared to the Maxwell model