Software Development with Code Maps

Discovering Common Features in Software Code Using Self-Organizing Maps

The self-organizing map is discussed as an unsupervised clustering method. Its ability to form clusters indicates similar features in a data set. Based on this property, it is demonstrated that a self-organizing map is capable of identifying features within software code by grouping procedures with similar properties together. This allows us to identify potential objects, abstract data types or...

Code Architecture and Open Source Software Development

A model is developed to study how the code architecture affects open source software (OSS) development. The model incorporates the resource heterogeneity and diverse motivations of various groups of programmers as well as the strategic interactions among them. We argue that the major advantage brought by a modular architecture of OSS code base is that it reduces both the cognitive cost and the ...

Collaborative Software Development and Topic Maps

Writing Code in the Field: Implications for Robot Software Development

Running robots on a deployment in the “real world” is very different from running them in a laboratory setting. Environmental conditions, such as lighting, are often completely beyond your control. There is often a limited amount of time on-site to test and tune the robot system, and deadlines are generally very inflexible. Finally, the public is notoriously unforgiving of failure. In this chap...

Code Clone Analysis Environment for Supporting Software Development and Maintenance

It is generally said that code clones are one of the factors to make software maintenace difficult. They are pairs or sets of code portions in source files that are identical or similar to each other. If some bugs are found in a code portion, it is nessesary to correct them in its all clones. However, in large-scale sofrware, it is very difficult to find all clones by hand. In this paper, we de...