Owolabi Legunsen

Yuanliang Zhang, Haochen He, Owolabi Legunsen et al.

Many techniques were proposed for detecting software misconfigurations in cloud systems and for diagnosing unintended behavior caused by such misconfigurations. Detection and diagnosis are steps in the right direction: misconfigurations cause many costly failures and severe performance issues. But, we argue that continued focus on detection and diagnosis is symptomatic of a more serious problem: configuration design and implementation are not yet first-class software engineering endeavors in cloud systems. Little is known about how and why developers evolve configuration design and implementation, and the challenges that they face in doing so. This paper presents a source-code level study of the evolution of configuration design and implementation in cloud systems. Our goal is to understand the rationale and developer practices for revising initial configuration design/implementation decisions, especially in response to consequences of misconfigurations. To this end, we studied 1178 configuration-related commits from a 2.5 year version-control history of four large-scale, actively-maintained open-source cloud systems (HDFS, HBase, Spark, and Cassandra). We derive new insights into the software configuration engineering process. Our results motivate new techniques for proactively reducing misconfigurations by improving the configuration design and implementation process in cloud systems. We highlight a number of future research directions.

Tianyin Xu, Owolabi Legunsen

This paper proposes configuration testing--evaluating configuration values (to be deployed) by exercising the code that uses the values and assessing the corresponding program behavior. We advocate that configuration values should be systematically tested like software code and that configuration testing should be a key reliability engineering practice for preventing misconfigurations from production deployment. The essential advantage of configuration testing is to put the configuration values (to be deployed) in the context of the target software program under test. In this way, the dynamic effects of configuration values and the impact of configuration changes can be observed during testing. Configuration testing overcomes the fundamental limitations of de facto approaches to combatting misconfigurations, namely configuration validation and software testing--the former is disconnected from code logic and semantics, while the latter can hardly cover all possible configuration values and their combinations. Our preliminary results show the effectiveness of configuration testing in capturing real-world misconfigurations. We present the principles of writing new configuration tests and the promises of retrofitting existing software tests to be configuration tests. We discuss new adequacy and quality metrics for configuration testing. We also explore regression testing techniques to enable incremental configuration testing during continuous integration and deployment in modern software systems.