… a bloat-aware design paradigm towards the development of efficient and scalable Big Data
applications … lists of two widely-used open-source Big Data applications. Next, we discuss our …

… We have also conducted experiments to verify the nongenerational property of data items
in Big Data applications. Figure 4 depicts the memory footprint and its correlation with epochs …

… data manipulation code by automatically transforming the data path of an existing Big Data
application… the number of runtime heap objects created for data types in each thread is (almost…

… application was relatively well designed with no memory leaks, it required such a big amount
of memory that for large data the application … A bloat-aware design for big data applications,…

… • We summarize the typical memory usage patterns of big data applications, and
empirically evaluate three widely-used garbage collectors on four Spark applications. Our in-depth …

… data of each class in an application or a JRE together to calculate the complexity of that
application … Xu, and MJ Carey, “A bloat-aware design for big data applications,” in Proc. ISMM ’13…

We present a study of bloating across the software stack. We study user-level programs, OS
kernels and Java virtual machine. We employ: (1) static measurements to detect limits to …

Programs are bloated. Our study shows that only 5% of libc is used on average across the
Ubuntu Desktop envi-ronment (2016 programs); the heaviest user, vlc media player, only …

… We evaluate XDebloat with 200 open-source and 1,000 commercial apps. The results
show that XDebloat can successfully remove components from apps or transform apps into on-…

… a well-known and widely used Big Data application, we show negligible overhead in frequent
… Previous works, such as Bu et al. with their bloat-aware design [5] have also alerted to this …