Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
184 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Spencer: Interactive Heap Analysis for the Masses (1703.05615v2)

Published 16 Mar 2017 in cs.PL

Abstract: Programming language-design and run-time-implementation require detailed knowledge about the programs that users want to implement. Acquiring this knowledge is hard, and there is little tool support to effectively estimate whether a proposed tradeoff actually makes sense in the context of real world applications. Ideally, knowledge about behaviour of "typical" programs is 1) easily obtainable, 2) easily reproducible, and 3) easily sharable. We present Spencer, a web service and API framework for dynamic analysis of a continuously growing set of traces of standard program corpora. Users do not obtain traces on their own, but can instead send queries to the web service that will be executed on a set of program traces. Queries are built in terms of a set of query combinators that present a high level interface for working with trace data. Since the framework is high level, and there is a hosted collection of recorded traces, queries are easy to implement. Since the data sets are shared by the research community, results are reproducible. Since the actual queries run on one (or many) servers that provide analysis as a service, obtaining results is possible on commodity hardware. Data in Spencer is meant to be obtained once, and analysed often, making the overhead of data collection mostly irrelevant. This allows Spencer to collect more data than traditional tracing tools can afford within their performance budget. Results in Spencer are cached, making complicated analyses that build on cached primitive queries speedy.

Citations (4)

Summary

We haven't generated a summary for this paper yet.