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Spencer: Interactive Heap Analysis for the Masses
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
2017 (English)In: 2017 IEEE/ACM 14th International Conference on Mining Software Repositories (MSR 2017), IEEE, 2017, no 14, p. 113-123Conference paper, Published paper (Refereed)
Abstract [en]

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, an open source 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.

Place, publisher, year, edition, pages
IEEE, 2017. no 14, p. 113-123
Series
IEEE International Working Conference on Mining Software Repositories, E-ISSN 2160-1852
Keywords [en]
tracing, dynamic analysis, heap analysis, tracing
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:uu:diva-334818DOI: 10.1109/MSR.2017.35ISI: 000425917100013ISBN: 978-1-5386-1544-7 (electronic)OAI: oai:DiVA.org:uu-334818DiVA, id: diva2:1160795
Conference
IEEE/ACM 14th International Conference on Mining Software Repositories (MSR), Buenos Aires, Argentina, May 20-21, 2017
Available from: 2017-11-28 Created: 2017-11-28 Last updated: 2018-11-27Bibliographically approved
In thesis
1. Structured Data
Open this publication in new window or tab >>Structured Data
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

References are a programming language construct that lets a programmer access a datum invariant of its location.

References permit aliasing -- several references to the same object, effectively making a single object accessible through different names (or paths). Aliasing, especially of mutable data, is both a blessing and a curse: when used correctly, it can make a programmer's life easier; when used incorrectly, for example through accidental aliases that the programmer is unaware of, aliasing can lead to hard to find bugs, and hard to verify programs.

Aliases allow us to build efficient data structures by connecting objects together, making them immediately reachable. Aliases are at the heart of many useful programming idioms. But with great power comes great responsibility: unless a programmer carefully manages aliases in a program, aliases propagate changes and make parts of a program's memory change seemingly for no reason. Additionally, such bugs are very easy to make but very hard to track down.

This thesis presents an overview of techniques for controlling how, when and if data can be aliased, as well as how and if data can be mutated. Additionally, it presents three different projects aimed at conserving the blessings, but reducing the curses. The first project is disjointness domains, a type system for expressing intended aliasing in a fine-grained manner so that aliasing will not be unexpected; the second project is Spencer, a tool to flexibly and precisely analyse the use of aliasing in programs to improve our understanding of how aliasing of mutable data is used in practise; and the third project is c flat, an approach for implementing high-level collection data structures using a richer reference construct that reduces aliasing problems but still retains many of aliasing's benefits.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2018. p. 85
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1749
Keywords
Aliasing, mutable state, imperative, programming, programming languages.
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:uu:diva-366932 (URN)978-91-513-0515-8 (ISBN)
Public defence
2019-01-23, Room 2446, Institutionen för informationsteknologi, Polacksbacken, Lägerhyddsvägen 2, Uppsala, 13:15 (English)
Opponent
Supervisors
Projects
UPMARC
Available from: 2018-12-20 Created: 2018-11-27 Last updated: 2019-02-25

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Publisher's full texthttps://arxiv.org/abs/1703.05615

Authority records BETA

Brandauer, StephanWrigstad, Tobias

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