Synthesizing Mutable Configurations: Setting up Systems for Success Numerous devices, from network switches and servers to industrial control systems, can be unreliable if they are not configured properly. Even if a deviceu0027s implementation has been proven correct, it must still be configured to meet the specific functional and security requirements of its stakeholders. However, manual configuration remains labor intensive and errorprone even for experts. Automated configuration synthesis presents a promising way forward. Unfortunately, as we show, existing counterexampleguided algorithms can perform poorly if the system model allows configuration changes during execution. Yet disallowing such changes can hide significant problems, such as privilege escalation. We present a new synthesis algorithm that exploits structure inherent in statemachine models where the system configuration changes. We implement it using the Kodkod relational model finder, and show that it favorably solves a number of configurationsynthesis tasks.

What should your runtime configuration framework do to help developers? The users or deployment engineers of a software system can adapt such a system to a wide range of deployment and usage scenarios by changing the value of configuration options, for example by disabling unnecessary features, tweaking performancerelated parameters or specifying GUI preferences. However, the literature agrees that the flexibility of such options comes at a price: misconfigured options can lead a software system to crash in the production environment, while even in the absence of such configuration errors, a large number of configuration options makes a software system more complicated to deploy and use. In earlier work, we also found that developers who intend to make their application configurable face 22 challenges that impact their configuration engineering activities, ranging from technical to managementrelated or even inherent to the domain of configuration engineering. In this paper, we use a prototyping approach to derive and empirically evaluate requirements for tool support able to deal with 13 (primarily technical) configuration engineering challenges. In particular, via a set of interviews with domain experts, we identify four requirements by soliciting feedback on an incrementally evolving prototype. The resulting xe2x80x9cConfig2Codexe2x80x9d prototype, which implements the four requirements, is then empirically evaluated via a user study involving 55 participants that comprises 10 typical configuration engineering tasks, ranging from the creation, comprehension, refactoring, and reviewing of configuration options to the quality assurance of options and debugging of configuration failures. A configuration framework satisfying the four requirements enables developers to perform more accurately and more swiftly in 70% and 60% (respectively) of the configuration engineering tasks than a stateofthepractice framework not satisfying the requirements. Furthermore, such a framework allows to reduce the time taken for these tasks by up to 94.62%, being slower for only one task.