Many internal software metrics and external quality attributes of Java programs correlate strongly with program size. This knowledge has been used pervasively in quantitative studies of software through practices such as normalization on size metrics. This paper reports size-related super- and sublinear effects that have not been known before. Findings obtained on a very large collection of Java programs – 30,911 projects hosted at Google Code as of Summer 2011 – unveils how certain characteristics of programs vary disproportionately with program size, sometimes even non-monotonically. Many of the specific parameters of nonlinear relations are reported. This result gives further insights for the differences of programming in the small vs.
programming in the large.'' The reported findings carry important consequences for OO software metrics, and software research in general: metrics that have been known to correlate with size can now be properly normalized so that all the information that is left in them is size-independent.
Slides (How Scale Affects Structure (OOPSLA15).pdf) | 889KiB |
Fri 30 OctDisplayed time zone: Eastern Time (US & Canada) change
10:30 - 12:00 | |||
10:30 22mTalk | Using C Language Extensions for Developing Embedded Software: A Case Study OOPSLA Markus Völter itemis, Germany, Arie van Deursen Delft University of Technology, Netherlands, Bernd Kolb itemis AG, Stephan Eberle itemis AG DOI Pre-print Media Attached | ||
10:52 22mTalk | How Scale Affects Structure in Java Programs OOPSLA DOI Pre-print Media Attached File Attached | ||
11:15 22mTalk | Use at Your Own Risk: The Java Unsafe API in the Wild OOPSLA Luis Mastrangelo University of Lugano, Switzerland, Luca Ponzanelli University of Lugano, Switzerland, Andrea Mocci University of Lugano, Switzerland, Michele Lanza University of Lugano, Switzerland, Matthias Hauswirth University of Lugano, Switzerland, Nate Nystrom University of Lugano, Switzerland DOI Media Attached | ||
11:37 22mTalk | Approximate Computation with Outlier Detection in Topaz OOPSLA Sara Achour Massachusetts Institute of Technology, USA, Martin C. Rinard Massachusetts Institute of Technology, USA DOI Media Attached |