This paper describes Hume: a novel domain-specific language whose purpose is to explore the expressibility/costability spectrum in resource-constrained systems, such as real-time embedded or control systems.

Java is becoming the main software platform for consumer and embedded devices such as mobile phones, PDAs, TV set-top boxes, and in-vehicle systems. Since many of these systems are memory constrained, it is extremely important to keep the memory footprint of Java applications under control.

The capabilities of applications executing on embedded and mobile devices are strongly influenced by memory size limitations. In fact, memory limitations are one of the main reasons that applications run slowly or even crash in embedded/mobile devices. While improvements in technology enable the integration of more memory into embedded devices, the amount memory that can be included is also limited by cost, power consumption, and form factor considerations. Consequently, addressing memory limitations will continue to be of importance. Focusing on embedded Java environments, this paper shows how object compression can improve memory space utilization. The main idea is to make use of the observation that a small set of values tend to appear in some fields of the heapallocated objects much more frequently than other values. Our analysis shows the existence of such frequent field values in the SpecJVM98 benchmark suite. We then propose two object compression schemes that eliminate/reduce the space occupied by the frequent field values. Our extensive experimental evaluation using a set of eight Java benchmarks shows that these schemes can reduce the minimum heap size allowing Java applications to execute without outof-memory exceptions by up to 24 % (14 % on an average).

Currently, there are 23 million Java-enabled handsets with more than 50 different models from 17-plus suppliers. With the growing popularity of such devices, there is a need in the embedded industry for a set of applications for accurate indications of the performance of embedded Java solutions. Towards addressing this problem, we gather a set of 12 Java applications running on PDA and cell phone like devices. We present a machine-independent characterization of the applications, specifically focusing on their memory characteristics. Our focus is motivated by the criticality of memory size constraints and heap footprints on both performance and power budgets.