Software development effort prediction is one of the most key activities in software industry. Many models have been proposed to build a relationship between software size and effort; however we still have problems for effort prediction. This is because project data, available in the primary stages of project is often inadequate, unpredictable, uncertain and unclear. The need for accurate effor...

In this study, a genetic programming technique was used with the goal of estimating the effort required in the development of individual projects. Results obtained were compared with those generated by a statistical regression and by a neural network that have already been used to estimate the development effort of individual software projects. A sample of 132 projects developed by 40 programme...

Global Software Development (GSD) is becoming increasingly prevalent, with software development teams being distributed around the world and working in collaboration with partner companies despite geographic and time differences. The main advantage of GSD which makes it attractive is the greater availability of human resources at lower costs. However, there are several disadvantages which are c...

Algorithmic effort prediction models are limited by their inability to cope with uncertainties and imprecision present in software projects early in the development life cycle. In this paper, we present an adaptive fuzzy logic framework for software effort prediction. The training and adaptation algorithms implemented in the framework tolerates imprecision, explains prediction rationale through...

Both Agile Software Development (ASD) and Global Software Development (GSD) are 21 century trends in the software industry. Many studies are reported in the literature wherein software companies have applied an agile method or practice GSD. Given that effort estimation plays a remarkable role in software project management, how do companies perform effort estimation when they use agile method i...

A mathematical model that makes use of data mining and soft computing techniques is proposed to estimate the software development effort. The proposed model works as follows: The parameters that have impact on the development effort are divided into groups based on the distribution of their values in the available dataset. The linguistic terms are identified for the divided groups using fuzzy f...

The use of optimization techniques has been recently proposed to build models for software development effort estimation. In particular, some studies have been carried out using search-based techniques, such as genetic programming, and the results reported seem to be promising. At the best of our knowledge nobody has analyzed the effectiveness of Tabu search for development effort estimation. T...

There have been many developments in the field of mobile technology in the last few years. Mobile technology grown very fast. Initially mobiles were only for rich but now all household have mobiles and using mobile technology because of great development in this field. Which is possible due to research in this area. Not only big companies but individuals also been engaged in this field. Billion...

In this section we will review literature on open source software development projects, focusing on their expended effort as well as achieved efficiency. The paper is based mostly on empirical analyses of open source communities. The main method employed is mining the associated software repositories which are publicly available and contain records of past interactions between participants, or ...

Ontologies play a key role in the Semantic Web the goal of which is to provide an environment able to advance quality of state-of-the-art web applications. Since we expect qualitative gains to come at the costs of increased development effort, we have decided to study the effect of an ontology on web application development effort. We have applied the WEBMO effort estimation model and discovere...