The DaCapo benchmarks: java benchmarking development and analysis

By S. Blackburn, Robin Garner, Chris Hoffmann, Asjad M. Khan, Kathryn S. McKinley, Rotem Bentzur, Amer Diwan, Daniel Feinberg, Daniel Frampton, Samuel Z. Guyer and 10 more. Conference on Object-Oriented Programming Systems, Languages, and Applications, 2006

1,736 citations recorded by the source corpus.

Subfields: Hardware and Architecture, Information Systems, Software

View Paper: https://www.semanticscholar.org/paper/00a9ba0063d34ec56792849a67ef57b4601becbb

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Citations in the corpus

Mop: an efficient and generic runtime verification framework (2007, methodology): “, the DaCapo benchmark suite [14], the Tracematches benchmark suite [8], and Eclipse [25].”
Uranine: Real-time Privacy Leakage Monitoring without System Modification for Android (2015, background): “The DaCapo benchmarks [6], which are popular Java benchmarks, are not easily ported to Android (due to their use of Java-specific libraries and GUI) and moreover, may also differ from real-world application workloads on Android.”
Evaluating Fuzz Testing (2018, background): “be considered “real” or “general.” 8.3 Toward a Fuzzing Benchmark Suite Our assessment leads us to believe that there is a real need for a solid, independently defined benchmark suite, e.g., a DaCapo [4] or SPEC10 for fuzz testing. This is a big enough task that we do not presume to take it on in th”
The ManyBugs and IntroClass Benchmarks for Automated Repair of C Programs (2015, background): “A well-designed benchmark set simplifies experimental reproduction, helps ensure generality of results, allows direct comparisons between competing methods, and over time enables measurement of a field's technical progress.”
A Systematic Evaluation of Transient Execution Attacks and Defenses (2018, background): “11 benchmarks STIPB [3, 43] 30– 50% [56] Rodinia OpenMP [17], DaCapo [13] IBPB [3, 43] no individual reports Serialization [4, 40] 62%, 74.”
A user-guided approach to program analysis (2015, methodology): “The benchmarks for the ﬁrst study (upper seven rows of Table 2) are 131–198 KLOC in size, and include programs from the DaCapo suite [5] ( antlr , avrora , luindex , lusearch ) and from past works that address our two analysis problems.”
The Qualitas Corpus: A Curated Collection of Java Code for Empirical Studies (2010, background): “[18], which consists of a set of open source, real world Java applications with non-trivial memo ry loads.”
Producing wrong data without doing anything obviously wrong! (2009, methodology): “, the DaCapo group found that the memory behavior of the SPEC JVM98 benchmarks was not representative of typical Java applications [3].”
Statistically rigorous java performance evaluation (2007, methodology): “Following the advice by Blackburn et al. [7], we consider multiple hardware platforms in our performance evaluation methodology: a 2.1GHz AMD Athlon XP, a 2.8GHz Intel Pentium 4, and a 1.42GHz Mac PowerPC G4 machine.”