Quantitative dynamic-memory analysis for Java

DIEGO GARBERVETSKY; SERGIO YOVINE; VÍCTOR BRABERMAN; ALEJANDRO TABOADA; MARTIN ROAUX

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE

JOHN WILEY & SONS LTD

Año: 2011 p. 1 - 18

1532-0626

Space- and time-predictability are hard to achieve for object-oriented languages with automated dynamic-memory management. Although there has been significant work to design APIs, such as the Real-Time Specication for Java (RTSJ), and to implement arbage collectors to enable real-time performance, quantitative space analysis is still in its infancy. This work presents the integration of a series of compile-time analysis techniques to help predicting quantitative memory usage. In particular, we focus on providing tool-assistance for identifying RTSJ scoped-memory regions, their sizes, and overall memory usage. First, the tool-suite synthesizes a memory organization where regions are associated with methods. Second, it infers their sizes in parametric closed-form in terms of relevant program variables. Third, it exhibits a parametric upper-bound on the amount of available free memory required to execute a method. The experiments carried out with a RTSJ benchmark, a real-time aircraft collision detector, show that semi-automatic, tool-assisted generation of scoped-based code is both helpful and doable form in terms of relevant program variables.