Lucas Nussbaum

The Ultimate Debian Database: Consolidating bazaar metadata for Quality Assurance and data mining

FLOSS distributions like RedHat and Ubuntu require a lot more complex infrastructures than most other FLOSS projects. In the case of community-driven distributions like Debian, the development of such an infrastructure is often not very organized, leading to new data sources being added in an impromptu manner while hackers set up new services that gain acceptance in the community. Mixing and matching data is then harder than should be, albeit being badly needed for Quality Assurance and data mining. Massive refactoring and integration is not a viable solution either, due to the constraints imposed by the bazaar development model. This paper presents the Ultimate Debian Database (UDD),1 which is the countermeasure adopted by the Debian project to the above “data hell”. UDD gathers data from various data sources into a single, central SQL database, turning Quality Assurance needs that could not be easily implemented before into simple SQL queries. The paper also discusses the customs that have contributed to the data hell, the lessons learnt while designing UDD, and its applications and potentialities for data mining on FLOSS distributions.

Perspectives on bugs in the Debian bug tracking system

Bugs in Debian differ from regular software bugs. They are usually associated with packages, instead of software modules. They are caused and fixed by source package uploads instead of code commits. The majority are reported by individuals who appear in the bug database once, and only once. There also exists a small group of bug reporters with over 1,000 bug reports each to their name. We also explore our idea that a high bug-frequency for an individual package might be an indicator of popularity instead of poor quality.

Accurate emulation of CPU performance

This paper addresses the question of CPU performance emulation, which allows experimenters to evaluate applications under a wide range of reproducible experimental conditions. Specifically, we propose Fracas, a CPU emulator that leverages the Linux Completely Fair Scheduler to achieve performance emulation of homogeneous or heterogeneous multi-core systems. Several benchmarks reproducing different types of workload (CPU-bound, IO-bound) are then used to thoroughly compare Fracas with another CPU emulator and hardware frequency scaling. We show that the design of Fracas results in a more accurate and a less intrusive CPU emulation solution.

Abstract: Using Business Workflows to Improve Quality of Experiments in Distributed Systems Research

Distributed systems pose many difficult problems to researchers. Due to their large-scale complexity, their numerous constituents (e.g., computing nodes, network links) tend to fail in unpredictable ways. This particular fragility of experiment execution threatens reproducibility, often considered to be a foundation of experimental science. Our poster presents a new approach to description and execution of experiments involving large-scale computer installations. The main idea consists in describing the experiment as workflow and using achievements of Business Workflow Management to reliably and efficiently execute it. Moreover, to facilitate the design process, the framework provides abstractions that hide unnecessary complexity from the user.