SEDGE : symbolic example data generation for dataflow programs
- Exhaustive, automatic testing of dataflow (esp. mapreduce) programs has emerged as an important challenge. Past work demonstrated effective ways to generate small example data sets that exercise operators in the Pig platform, used to generate Hadoop map-reduce programs. Although such prior techniques attempt to cover all cases of operator use, in practice they often fail. Our SEDGE system addresses these completeness problems: for every dataflow operator, we produce data aiming to cover all cases that arise in the dataflow program (e.g., both passing and failing a filter). SEDGE relies on transforming the program into symbolic constraints, and solving the constraints using a symbolic reasoning engine (a powerful SMT solver), while using input data as concrete aids in the solution process. The approach resembles dynamic-symbolic (a.k.a. "concolic") execution in a conventional programming language, adapted to the unique features of the dataflow domain. In third-party benchmarks, SEDGE achieves higher coverage than past techniques for 5 out of 20 PigMix benchmarks and 7 out of 11 SDSS benchmarks and (with equal coverage for the rest of the benchmarks). We also show that our targeting of the high-level dataflow language pays off: for complex programs, state-of-the-art dynamic-symbolic execution at the level of the generated map-reduce code (instead of the original dataflow program) requires many more test cases or achieves much lower coverage than our approach.
Author: | Kaituo Li, Christoph Reichenbach, Yannis Smaragdakis, Yanlei Diao, Christoph Csallner |
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URN: | urn:nbn:de:hebis:30:3-438959 |
URL: | https://zenodo.org/record/7730/files/sedge-ase13.pdf |
ISBN: | 978-1-4799-0215-6 |
ISBN: | 978-1-4799-0216-3 |
Editor: | Ewen Denney, Tevfik Bultan, Andreas Zeller |
Document Type: | Conference Proceeding |
Language: | English |
Date of Publication (online): | 2017/10/19 |
Year of first Publication: | 2013 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Contributing Corporation: | 2013 28th IEEE/ACM international conference on automated software engineering (ASE), November 11-15, 2013, Palo Alto, USA |
Release Date: | 2017/10/19 |
Tag: | Benchmark testing; Cognition; Concrete; Data processing; Educational institutions; Extraterrestrial measurements; Programming |
Page Number: | 11 |
Note: | Auch in: Ewen Denney ; Tevfik Bultan ; Andreas Zeller (Hrsg.): 2013 28th IEEE/ACM international conference on automated software engineering (ASE) : proceedings, Conference Publishing Consulting : Passau, 2013, S. 235-245, ISBN: 978-1-4799-0215-6, ISBN: 978-1-4799-0216-3, doi:10.1109/ASE.2013.6693083 |
HeBIS-PPN: | 41972284X |
Institutes: | Informatik und Mathematik / Informatik |
Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
Sammlungen: | Universitätspublikationen |
Licence (German): | Deutsches Urheberrecht |