Programming computers has been a herculean task for most programmers especially when codes grow into complex and larger software systems with multiple subprograms. Object Oriented Programming (OOP) has reduced the difficulty in the development of elegant and scalable software by presenting robust concepts such as composition, inheritance and aggregation. All these concepts have enormous assistance to the software developer in code reuse. Also these techniques can be used to build applications which can be delivered to customers in a record time. In this research a critical study, review and implementation of software building and enhancement using aggregation and inheritance. A module is built with attributes defining it properties and methods its characteristics. Incrementally more modules were added to the previous modules using either aggregation or inheritance technique. This incremental approach has proven tremendous success in software development. This as buttressed by many software development theories have shown that: software is built not manufactured; software is a collection of programs with functions and attributes based on its enhancement, also incremental software development which involves building systems from sub-systems gives a better understanding of software development process. Also the process of writing bug-free programs can be achieved with lesser difficulty which can be achieved when programs are built using modular or incremental software development approach, which employs mostly aggregation while moderately using inheritance only if all the properties and methods of those modules are needed wholesomely in classes. The result from the research will help programmers to enhance codes with much mastery.

This research is carried-out to evaluate the effectiveness of data mining in determining viability of routes, efficient scheduling and assigning of vehicles to commuters. The study was guided by the following objectives: modification of Apriori algorithm, implementation using C programming language, analyses and deductions from the results to determine if a given route is feasible. Data Mining (association rule) technique has been used to identify geographical locations where accidents have occurred and their characteristics, in road management to develop effective accident preventive measures, to determine estimated travel time and in market basket analysis applied in grocery stores. Data was collected from three transport companies for each route. The data was inputted into the program implemented using modified Apriori algorithm. The study findings revealed the volume of commuters per route and how vehicles can be assigned and scheduled. Using the above findings, effective transport service system is designed using routes viability