INES – National Institute of Science and Technology for Software Engineering

INES researchers at CSMR 2012

INES researchers, working in the context of the project “Models, Techniques and Tools for Software Evolution” had 2 papers accepted at CSMR 2012:

(1) “Understanding Structural Complexity Evolution: a Quantitative Analysis”,
Antonio Terceiro, Manoel Mendonça, Christina Chavez (UFBA) and Daniela Cruzes (NTNU)

Abstract—Background: An increase in structural complexity
makes the source code of software projects more difficult to
understand, and consequently more difficult and expensive to
maintain and evolve. Knowing the factors that influence structural
complexity may help developers to avoid the effects of
higher levels of structural complexity on the maintainability of
their projects.
Aims: This paper investigates factors that might influence the
evolution of structural complexity.
Method: We analyzed the source code repositories of 5 free/open
source software projects, with commits as experimental units. For
each commit we measured the structural complexity variation it
caused, the experience of the developer who made the commit,
the size variation caused by the commit, and the change diffusion
of the commit.
Results: Change diffusion was the most influential among the factors
studied, followed by size variation and developer experience;
system growth was not necessarily associated with complexity
increase; all the factors we studied influenced at least two
projects; different projects were affected by different factors; and
the factors that influenced the increase in structural complexity
were usually not the same that influenced the decrease.
Conclusions: All the factors explored in this study should be
taken into consideration when analysing structural complexity
evolution. However, they do not fully explain the structural
complexity evolution in the studied projects: this suggests that
qualitative studies are needed in order to better understand
structural complexity evolution and identify other factors that
must be included in future quantitative analysis.

(Activity: http://amigos.ines.org.br/ines/viewTask.do?method=viewTask&code=572&project=8)

(2) “On the Relevance of Code Anomalies for Identifying Architecture Degradation Symptoms”, Isela Macia(PUC-Rio), Roberta Arcoverde(PUC-Rio), Alessandro Garcia(PUC-Rio), Christina Chavez (UFBA) and Arndt von Staa(PUC-Rio).

This work has been developed by PUC-Rio researchers,  and Christina Chavez (UFBA) co-authored it during her pos-doc at PUC-Rio.