An official website of the United States government
Once a programmer knows one language, they can leverage concepts and knowledge already learned, and easily pick up another programming language. But is that always the case? To understand if programmers have difficulty learning additional programming languages, we conducted an empirical study of Stack Overflow questions across 18 different programming languages. We hypothesized that previous knowledge could potentially interfere with learning a new programming language. From our inspection of 450 Stack Overflow questions, we found 276 instances of interference that occurred due to faulty assumptions originating from knowledge about a different language. To understand why these difficulties occurred, we conducted semi-structured interviews with 16 professional programmers. The interviews revealed that programmers make failed attempts to relate a new programming language with what they already know. Our findings inform design implications for technical authors, toolsmiths, and language designers, such as designing documentation and automated tools that reduce interference, anticipating uncommon language transitions during language design, and welcoming programmers not just into a language, but its entire ecosystem.
more »
« less
PLIERS: A Process that Integrates User-Centered Methods into Programming Language Design
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.
more »
« less
- Award ID(s):
- 1852260
- PAR ID:
- 10601520
- Publisher / Repository:
- Association for Computing Machinery (ACM)
- Date Published:
- Journal Name:
- ACM Transactions on Computer-Human Interaction
- Volume:
- 28
- Issue:
- 4
- ISSN:
- 1073-0516
- Format(s):
- Medium: X Size: p. 1-53
- Size(s):
- p. 1-53
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
There are many different probabilistic programming languages that are specialized to specific kinds of probabilistic programs. From a usability and scalability perspective, this is undesirable: today, probabilistic programmers are forced up-front to decide which language they want to use and cannot mix-and-match different languages for handling heterogeneous programs. To rectify this, we seek a foundation for sound interoperability for probabilistic programming languages: just as today’s Python programmers can resort to low-level C programming for performance, we argue that probabilistic programmers should be able to freely mix different languages for meeting the demands of heterogeneous probabilistic programming environments. As a first step towards this goal, we introduce MultiPPL, a probabilistic multi-language that enables programmers to interoperate between two different probabilistic programming languages: one that leverages a high-performance exact discrete inference strategy, and one that uses approximate importance sampling. We give a syntax and semantics for MultiPPL, prove soundness of its inference algorithm, and provide empirical evidence that it enables programmers to perform inference on complex heterogeneous probabilistic programs and flexibly exploits the strengths and weaknesses of two languages simultaneously.more » « less
-
The report documents the program and outcomes of Dagstuhl Seminar 18061 "Evidence About Programmers for Programming Language Design". The seminar brought together a diverse group of researchers from the fields of computer science education, programming languages, software engineering, human-computer interaction, and data science. At the seminar, participants discussed methods for designing and evaluating programming languages that take the needs of programmers directly into account. The seminar included foundational talks to introduce the breadth of perspectives that were represented among the participants; then, groups formed to develop research agendas for several subtopics, including novice programmers, cognitive load, language features, and love of programming languages. The seminar concluded with a discussion of the current SIGPLAN artifact evaluation mechanism and the need for evidence standards in empirical studies of programming languages.more » « less
-
Chasins, Sarah; Glassman, Elena; Sunshine, Joshua (Ed.)A domain-specific language (DSL) design space describes a collection of related languages via a series of, often orthogonal, dimensions. While PL and HCI researchers have independently developed methods for working with design spaces, the communities have yet to fully benefit from each others' insights. In pursuit of new approaches informed by both PL and HCI, we first review existing approaches researchers employ to conceptualize, develop, and use design spaces in DSL design across the two disciplines. For example, HCI researchers, when developing interfaces backed by DSLs, often treat the design process as core to their research contributions and theory-building. In PL, researchers have explored formal approaches to design spaces that help automate design space exploration and provide powerful conceptual clarity to language design tradeoffs. We then discuss areas where the two fields share common methods and highlight opportunities for researchers to combine knowledge across PL and HCI.more » « less
-
Programmers are expected to use multiple programming languages frequently. Studies have found that programmers try to reuse existing knowledge from their previous languages. However, this strategy can result in misconceptions from previous languages. Current learning resources that support the strategy are limited because there is no systematic way to produce or validate the material. We designed three instruments that can help identify and validate meaningful behavior differences between two languages to pinpoint potential misconceptions. To validate the instruments, we examined how Python programmers predict behavior in a less familiar language like R, and whether they expect various R semantics. We found that the instruments are effective in validating differences between Python and R which were linked to misconceptions. We discuss design trade-offs between the three instruments and provide guidelines for researchers and educators in systematically validating programming misconceptions when switching to a new language.more » « less
