Biblio
Programming language design requires making many usability-related design decisions. However, existing HCI methods can be impractical to apply to programming languages: languages have high iteration costs, programmers require significant learning time, and user performance has high variance. To address these problems, we adapted both formative and summative HCI methods to make them more suitable for programming language design. We integrated these methods into a new process, PLIERS, for designing programming languages in a user-centered way. We assessed PLIERS by using it to design two new programming languages. Glacier extends Java to enable programmers to express immutability properties effectively and easily. Obsidian is a language for blockchains that includes verification of critical safety properties. Empirical studies showed that the PLIERS process resulted in languages that could be used effectively by many programmers and revealed additional opportunities for language improvement.
Some blockchain programs (smart contracts) have included serious security vulnerabilities. Obsidian is a new typestate-oriented programming language that uses a strong type system to rule out some of these vulnerabilities. Although Obsidian was designed to promote usability to make it as easy as possible to write programs, strong type systems can cause a language to be difficult to use. In particular, ownership, typestate, and assets, which Obsidian uses to provide safety guarantees, have not seen broad adoption together in popular languages and result in significant usability challenges. We performed an empirical study with 20 participants comparing Obsidian to Solidity, which is the language most commonly used for writing smart contracts today. We observed that Obsidian participants were able to successfully complete more of the programming tasks than the Solidity participants. We also found that the Solidity participants commonly inserted asset-related bugs, which Obsidian detects at compile time.
Blockchain platforms are coming into use for processing critical transactions among participants who have not established mutual trust. Many blockchains are programmable, supporting smart contracts, which maintain persistent state and support transactions that transform the state. Unfortunately, bugs in many smart contracts have been exploited by hackers. Obsidian is a novel programming language with a type system that enables static detection of bugs that are common in smart contracts today. Obsidian is based on a core calculus, Silica, for which we proved type soundness. Obsidian uses typestate to detect improper state manipulation and uses linear types to detect abuse of assets. We integrated a permissions system that encodes a notion of ownership to allow for safe, flexible aliasing. We describe two case studies that evaluate Obsidian’s applicability to the domains of parametric insurance and supply chain management, finding that Obsidian’s type system facilitates reasoning about high-level states and ownership of resources. We compared our Obsidian implementation to a Solidity implementation, observing that the Solidity implementation requires much boilerplate checking and tracking of state, whereas Obsidian does this work statically.
Much recent work focuses on finding bugs and security vulnerabilities in smart contracts written in existing languages. Although this approach may be helpful, it does not address flaws in the underlying programming language, which can facilitate writing buggy code in the first place. We advocate a re-thinking of the blockchain software engineering tool set, starting with the programming language in which smart contracts are written. In this paper, we propose and justify requirements for a new generation of blockchain software development tools. New tools should (1) consider users' needs as a primary concern; (2) seek to facilitate safe development by detecting relevant classes of serious bugs at compile time; (3) as much as possible, be blockchain-agnostic, given the wide variety of different blockchain platforms available, and leverage the properties that are common among blockchain environments to improve safety and developer effectiveness.
Static types may be used both by the language implementation and directly by the user as documentation. Though much existing work focuses primarily on the implications of static types on the semantics of programs, relatively little work considers the impact on usability that static types pro- vide. Though the omission of static type information may decrease program length and thereby improve readability, it may also decrease readability because users must then frequently derive type information manually while reading programs. As type inference becomes more popular in languages that are in widespread use, it is important to consider whether the adoption of type inference may impact productivity of developers.
Application Programming Interfaces (APIs) often define object
protocols. Objects with protocols have a finite number of states and
in each state a different set of method calls is valid. Many researchers
have developed protocol verification tools because protocols are notoriously
difficult to follow correctly. However, recent research suggests that
a major challenge for API protocol programmers is effectively searching
the state space. Verification is an ineffective guide for this kind of
search. In this paper we instead propose Plaiddoc, which is like Javadoc
except it organizes methods by state instead of by class and it includes
explicit state transitions, state-based type specifications, and rich state
relationships. We compare Plaiddoc to a Javadoc control in a betweensubjects
laboratory experiment. We find that Plaiddoc participants complete
state search tasks in significantly less time and with significantly
fewer errors than Javadoc participants.