Inheritance and templates are key concepts in object-oriented programming (OOP), and are essential for achieving reusability and extendibility. The aim of this paper is to explore traditional Halstead's metrics and use them to propose more software metrics related to generic method and attributes in an object-oriented software. These metrics measure quantitative generic construct with inheritance in an object-oriented code. Two metrics GRr (Generic Reusability Ratio) and ERr (Effort Ratio) are proposed in this paper. First metric GRr (Generic Reusability Ratio) measures impact of template in program volume and second metric ERr (Effort Ratio) measures impact of template in development effort. These metrics will be a tool for estimating and evaluating costs of program design and program tests as well as program complexity.
In spite of large acceptance of object-oriented paradigm, many programmers don't have a firm grip on the design principles and the intimate mechanisms of object-orientation and this result into to a lot of poor designed large scale OO systems. Coupling in the software is one of the most vibrant internal quality attribute to measure the design performance. In this paper, we propose M essage Received Coupling (M RC) and Degree of Coupling (DC) metrics for the automatic detection of a set of design problems along with an algorithm to apply these metrics to redesign an object-oriented source code, if necessary. We also design a M ethod Calling Graph (M CG) that helps in calculating the value of proposed metrics. The revised set of metrics helps the developers to decide whether a design needs to be changed or left in its original form.
There are many algorithms and techniques for estimating the reliability of Component Based Software Systems (CBSSs). Accurate estimation depends on two factors: component reliability and glue code reliability. Still much more research is expected to estimate reliability in a better way. A number of soft computing approaches for estimating CBSS reliability has been proposed. These techniques learnt from the past and capture existing patterns in data. In this paper, we proposed new model for estimating CBSS reliability known as Modified Neuro Fuzzy Inference System (MNFIS). This model is based on four factors Reusability, Operational, Component dependency, Fault Density. We analyze the proposed model for diffent data sets and also compare its performance with that of plain Fuzzy Inference System. Our experimental results show that, the proposed model gives better reliability as compare to FIS.
Background: The soil nematodes can affect the crops in various ways. The plant-parasitic nematodes can lead to severe yield losses. The extent of crop yield loss depends on the susceptibility of the variety or host tolerance, population density of the nematode and various environmental variables. However, no tool is available for the prediction of nematode population buildup in soil therefore it has been difficult to issue advisories for timely management of these pathogens. Here we developed a method to accurately predict the nematode population buildup in soil for its timely management. Methods: Nematode population index of a plant-parasitic nematode Tylenchorynchus was taken from two crops i.e. mung bean and crotalaria. The model was developed considering various weather variables to predict the population of the Tylenchorynchus in the fields of mung bean and crotalaria. Weather parameters such as maximum and minimum temperature, relative humidity, wind speed and sunshine hours were considered for developing the model for Tylenchorynchus population prediction. Stepwise regression method was applied to predict the nematode population. Result: The regression analysis between estimated and observed values of Tylenchorynchus population gave the R2 value as 0.98 for mung bean and 0.87 for crotalaria. Well timed prediction can help the growers to apply the required management practices to make it beneficial economically. This method can be extended to predict the population buildup of other serious nematode pests of crops.
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