Biblio

Programming languages exist to enable people to create and maintain software as effectively as possible. They are subject to two very different sets of requirements: first, the need to provide strong safety guarantees to protect against bugs; and second, the need for users to effectively and efficiently write software that meets their functional and quality requirements. This thesis argues that fusing formal methods for reasoning about programming languages with user-centered design methods is a practical approach to designing languages that make programmers more effective. By doing so, designers can create safer languages that are more effective for programmers than existing languages. The thesis is substantiated by the introduction of PLIERS: Programming Language Iterative Evaluation and Refinement System. PLIERS is a process for designing programming languages that integrates formal methods with user-centered design. The hypothesis that PLIERS is beneficial is supported by two language design projects. In these projects, I show how PLIERS benefits the programming language design process. Glacier is an extension to Java that enforces transitive class immutability, which is a much stronger property than that provided by languages that are in use today. Although there are hundreds of possible ways of restricting changes to state in programming languages, Glacier occupies a point in the design space that was justified by interview studies with professional software engineers. I evaluated Glacier in case studies, showing that it is expressive enough for some real-world applications. I also evaluated Glacier in lab studies and compared it to Java’s final keyword, finding both that Glacier is more effective at expressing immutability than final and that Glacier detects bugs that users are likely to insert in code. Blockchains are a distributed computing platform that aim to enable safe computation among users who do not necessarily trust each other. To improve safety relative to existing languages, in which programmers have repeatedly deployed software with serious bugs, I designed Obsidian, a new programming language for blockchain application development. From observations about typical blockchain applications, I derived two features that motivated the design of Obsidian. First, blockchain applications typically implement state machines, which support different operations in different states. Obsidian uses typestate, which lifts dynamic state into static types, to provide static guarantees regarding object state. Second, blockchain applications frequently manipulate resources, such as virtual currency. Obsidian provides a notion of ownership, which distinguishes one reference from all others. Obsidian supports resources via linear types, which ensure that owning references to resources are not accidentally lost. The combination of resources and typestate results in a novel set of design problems for the type system; although each idea has been explored individually, combining them requires unifying different perspectives on linearity. Furthermore, no language with either one of these features has been designed in a user-centered way or evaluated with users. Typical typestate systems have a complex set of permissions that provides safety properties, but these systems focused on expressiveness rather than on usability. Obsidian integrates typestate and resources in a novel way, resulting in a new type system design with a focus on simplicity and usability while retaining the desired safety properties. Obsidian is based on a core calculus I designed, Silica, for which I proved type soundness. In order to make Obsidian as usable as possible, I based its design on the results of formative studies with programmers. I evaluated Obsidian with two case studies, showing that Obsidian can be used to implement relevant programs. I also conducted a randomized controlled trial comparing Obsidian to Solidity, a popular language for writing smart contracts. I found that most of the Obsidian participants learned Obsidian and completed programming tasks after only a short training period; further, in one task, 70% of the participants who used Solidity accidentally inserted bugs that Obsidian’s compiler would have detected. Finally, Obsidian participants completed significantly more tasks correctly than did Solidity participants.

Though immutability has been long-proposed as a way to prevent bugs in software, little is known about how to make immutability support in programming languages effective for software engineers. We designed a new formalism that extends Java to support transitive class immutability, the form of immutability for which there is the strongest empirical support, and implemented that formalism in a tool called Glacier. We applied Glacier successfully to two real-world systems. We also compared Glacier to Java’s final in a user study of twenty participants. We found that even after being given instructions on how to express immutability with final, participants who used final were unable to express immutability correctly, whereas almost all participants who used Glacier succeeded. We also asked participants to make specific changes to immutable classes and found that participants who used final all incorrectly mutated immutable state, whereas almost all of the participants who used Glacier succeeded. Glacier represents a promising approach to enforcing immutability in Java and provides a model for enforcement in other languages.

Programming languages can restrict state change by preventing it entirely (immutability) or by restricting which clients may modify state (read-only restrictions). The benefits of immutability and read-only restrictions in software structures have been long-argued by practicing software engineers, researchers, and programming language designers. However, there are many proposals for language mechanisms for restricting state change, with a remarkable diversity of techniques and goals, and there is little empirical data regarding what practicing software engineers want in their tools and what would benefit them. We systematized the large collection of techniques used by programming languages to help programmers prevent undesired changes in state. We interviewed expert software engineers to discover their expectations and requirements, and found that important requirements, such as expressing immutability constraints, were not reflected in features available in the languages participants used. The interview results informed our design of a new language extension for specifying immutability in Java. Through an iterative, participatory design process, we created a tool that reflects requirements from both our interviews and the research literature.