Detecting inefficiently-used containers to avoid bloat
PLDI '10 Proceedings of the 2010 ACM SIGPLAN conference on Programming language design and implementation
Finding low-utility data structures
PLDI '10 Proceedings of the 2010 ACM SIGPLAN conference on Programming language design and implementation
Proceedings of the FSE/SDP workshop on Future of software engineering research
Brainy: effective selection of data structures
Proceedings of the 32nd ACM SIGPLAN conference on Programming language design and implementation
LeakChaser: helping programmers narrow down causes of memory leaks
Proceedings of the 32nd ACM SIGPLAN conference on Programming language design and implementation
The beauty and the beast: separating design from algorithm
Proceedings of the 25th European conference on Object-oriented programming
Patterns of memory inefficiency
Proceedings of the 25th European conference on Object-oriented programming
Reuse, recycle to de-bloat software
Proceedings of the 25th European conference on Object-oriented programming
The interplay of software bloat, hardware energy proportionality and system bottlenecks
HotPower '11 Proceedings of the 4th Workshop on Power-Aware Computing and Systems
Smaller footprint for Java collections
Proceedings of the ACM international conference companion on Object oriented programming systems languages and applications companion
Does lean imply green?: a study of the power performance implications of Java runtime bloat
Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
Dynamic analysis of inefficiently-used containers
Proceedings of the 2012 Workshop on Dynamic Analysis
Uncovering performance problems in Java applications with reference propagation profiling
Proceedings of the 34th International Conference on Software Engineering
Smaller footprint for java collections
ECOOP'12 Proceedings of the 26th European conference on Object-Oriented Programming
Static detection of loop-invariant data structures
ECOOP'12 Proceedings of the 26th European conference on Object-Oriented Programming
Finding reusable data structures
Proceedings of the ACM international conference on Object oriented programming systems languages and applications
A bloat-aware design for big data applications
Proceedings of the 2013 international symposium on memory management
Precise memory leak detection for java software using container profiling
ACM Transactions on Software Engineering and Methodology (TOSEM) - In memoriam, fault detection and localization, formal methods, modeling and design
Resurrector: a tunable object lifetime profiling technique for optimizing real-world programs
Proceedings of the 2013 ACM SIGPLAN international conference on Object oriented programming systems languages & applications
Combining concern input with program analysis for bloat detection
Proceedings of the 2013 ACM SIGPLAN international conference on Object oriented programming systems languages & applications
CoCo: sound and adaptive replacement of java collections
ECOOP'13 Proceedings of the 27th European conference on Object-Oriented Programming
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The drive to rapidly develop layered, interconnected, and flexible systems has eclipsed consideration of resource costs. Consequently, large Java applications suffer from runtime bloat: a large and pervasive infrastructure tax, where simple transactions require a few hundred thousand method calls, and a server with 1 Gbyte of memory sometimes can only support a few hundred users. Current Java optimizers and garbage collectors are of little help for these systemic problems. Enterprises face greatly reduced scalability, increased power consumption, and missed deliveries. In this article, the authors detail four global software development trends, along with some widely held myths, that lead to bloat in Java applications. They illustrate their consequences with anecdotes drawn from real applications suffering severe performance and memory issues. While these trends are inevitable, runtime bloat is not. Understanding the sources of bloat can help programmers craft appropriate solutions for the future.