Automatic Reasoning Techniques for Non-Serializable Data-Intensive Applications

The performance bottlenecks in modern data-intensive applications have induced database implementors to forsake high-level abstractions and trade-off simplicity and ease of reasoning for performance. Among the first casualties of this trade-off are the well-known ACID guarantees, which simplify the reasoning about concurrent database transactions. ACID semantics have become increasingly obsolete in practice due to serializable isolation – an integral aspect of ACID, being exorbitantly expensive. Databases, including the popular commercial offerings, default to weaker levels of isolation where effects of concurrent transactions are visible to each other. Such weak isolation guarantees, however, are extremely hard to reason about, and have led to serious safety violations in real applications. The problem is further complicated in a distributed setting with asynchronous state replications, where high availability and low latency requirements compel large-scale web applications to embrace weaker forms of consistency (e.g., eventual consistency) besides weak isolation. Given the serious practical implications of safety violations in data-intensive applications, there is a pressing need to extend the state-of-the-art in program verification to reach non- serializable data-intensive applications operating in a weakly-consistent distributed setting.

This thesis sets out to do just that. It introduces new language abstractions, program logics, reasoning methods, and automated verification and synthesis techniques that collectively allow programmers to reason about non-serializable data-intensive applications in the same way as their serializable counterparts. The contributions

xi

made are broadly threefold. Firstly, the thesis introduces a uniform formal model to reason about weakly isolated (non-serializable) transactions on a sequentially consistent (SC) relational database machine. A reasoning method that relates the semantics of weak isolation to the semantics of the database program is presented, and an automation technique, implemented in a tool called ACIDifier is also described. The second contribution of this thesis is a relaxation of the machine model from sequential consistency to a specifiable level of weak consistency, and a generalization of the data model from relational to schema-less or key-value. A specification language to express weak consistency semantics at the machine level is described, and a bounded verification technique, implemented in a tool called Q9 is presented that bridges the gap between consistency specifications and program semantics, thus allowing high-level safety properties to be verified under arbitrary consistency levels. The final contribution of the thesis is a programming model inspired by version control systems that guarantees correct-by-construction replicated data types (RDTs) for building complex distributed applications with arbitrarily-structured replicated state. A technique based on decomposing inductively-defined data types into characteristic relations is presented, which is used to reason about the semantics of the data type under state replication, and eventually derive its correct-by-construction replicated variant automatically. An implementation of the programming model, called Quark, on top of a content-addressable storage is described, and the practicality of the programming model is demonstrated with help of various case studies.