CONTENTS

208 C ĂLIN ENĂCHESCU(1) AND DUMITRU R ĂDOIU(2)
the development and can be used for the cost estimation only in the final phases of
development when the entire software project has been finalized [2].
• Functional Points metrics (FP): this software metrics takes into account
the program functionalities (e.g. number of interrogations, reports), program complexity
(e.g. number of logical files) and a large number of ”adjustment” factors (e.g.
does the system require real time processing?) [2].
• Object points metrics (OPM): this hybrid software metrics (borrows concepts
from Functional Points metrics and object-oriented paradigm although the concept
”object” is not used as it is used in object oriented paradigm literature) assesses
the complexity of required ”objects” like: user screens, reports, 3GL components etc.
Each object is estimated, a weight between 1 and 10 being attached to each object,
simple objects like user screens are estimated with weight 1 and complex objects (3GL
component) are weighted with 10. One of the most largely used cost estimation model
is COCOMO II [4] which is prized for its results in making estimations in the initial
stages of the software development project.
4. Cost estimation for software development projects based on
neural networks
There are two general methods to estimate the cost for software development
projects: algorithmic methods and heuristic methods. The heuristic methods are
generally based on statistical decisions, on regression models or on complex analytical
differential equations [1].
4.1. Preliminaries. As we have already discussed, cost estimation for software development
projects has remained for decades one of the major problems to be solved
in software engineering [15].
Algorithm-based computers are programmed, i.e. there must be a set of rules
which, a priori, characterize the calculation that is implemented by the computer.
Neural computation, based on neural networks, solve problems by learning, they
absorb experience, and modify their internal structure in order to accomplish a given
task [9].
In order to solve a problem using a neural network we have to decide regarding
the architecture of the neural network, learning algorithm and upon several issues
that are influencing the learning process, like: data encoding, learning rate, weight
initialization, activation functions etc. [7]. We are using in our model for cost estimation
for software development projects based on neural networks a Multi Layer
Perceptron [6] architecture and a specialized Back Propagation type of learning algorithm
[7]. The training set used (COCOMO’81) contains historical data from 63
software development projects. The training samples have each 17 attributed related
to the software development projects.
4.2. Learning data encoding. Learning data encoding is necessary before star-ting
the learning process in order to make all attributes comparable in their influence upon
the learning process. The learning process will stop when a certain error is reached,