Maintaining software through intentional source-code views

Maintaining the source code of large software systems is hard. One underlying cause is that existing modularisation mechanisms are inadequate to handle crosscutting concerns. We propose intentional source-code views as an intuitive and lightweight means of modelling such concerns. They increase our ability to understand, modularise and browse the source code by grouping together source-code entities that address the same concern. They facilitate software development and evolution, because alternative descriptions of the same intentional view can be checked for consistency and relations among intentional views can be defined and verified. Finally, they enable us to specify knowledge developers have about source code that is not captured by traditional program documentation mechanisms. Our intentional view model is implemented in a logic metaprogramming language that can reason about and manipulate object-oriented source code directly. The proposed model has been validated on the evolution of a medium-sized object-oriented application in Smalltalk, and a prototype tool has been implemented

Relationship between size, effort, duration and number of contributors in large FLOSS projects

This contribution presents initial results in the study of the relationship between size, effort, duration and number of contributors in eleven evolving Free/Libre Open Source Software (FLOSS) projects, in the range from approx. 650,000 to 5,300,000 lines of code. Our initial motivation was to estimate how much effort is involved in achieving a large FLOSS system. Software cost estimation for proprietary projects has been an active area of study for many years. However, to our knowledge, no previous similar research has been conducted in FLOSS effort estimation. This research can help planning the evolution of future FLOSS projects and in comparing them with proprietary systems. Companies that are actively developing FLOSS may benefit from such estimates. Such estimates may also help to identify the productivity ’baseline’ for evaluating improvements in process, methods and tools for FLOSS evolution

Refactoring of UML models using AGG

Model refactoring is an emerging research topic that is heavily inspired by refactoring of object-oriented programs. Current-day UML modeling environments provide poor support for evolving UML models and applying refactoring techniques at model level. As UML models are intrinsically graph-based in nature we propose to use graph transformations to specify and apply model refactoring. More in particular, we use a specific graph transformation tool, AGG, and provide recommendations of how AGG may be improved to better support model refactoring. These recommendations are based on a small experiment that we have carried out with refactoring of UML class diagrams and state machines