Debugging Database Queries: A Survey of Tools, Techniques, and Users

Gathani, Sneha; Lim, Peter; Battle, Leilani

doi:10.1145/3313831.3376485

Cited by 20 publications

(6 citation statements)

References 93 publications

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“…Just as in other declarative languages, it can be challenging to debug [101], requiring the programmer to hold a potentially unfamiliar execution model held by the DSL in their mind to address possible subtle errors (providing hidden dependency and hard mental operations difficulties). We follow Hoffswell et al's [141] in-situ visualization in that our custom views offer a space for the application designer to surface relevant information into the editor to help end-users debug.…”

Section: Discussionmentioning

confidence: 99%

Understanding and Enhancing JSON-based DSL Interfaces for Visualization

McNutt¹

2023

Preprint

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Domain-specific languages represented in data serialization formats (such as Javascript Object Notation or JSON) are an increasingly common means to control numerous systems.These range from database queries to application configuration, narrative generation, Twitter bots, data visualization, and many other areas.These languages allow potentially unsophisticated human users to concisely specify their intent through logic and notation that is relevant to task domain.Further, they provide a means for computational agents to easily manipulate that form, allowing for powerful recommendation engines and systems of automated analyses.In this thesis, we consider how end-user agency might be enhanced and maintained through the design of tools that support these domain-specific languages, as well as through the study of the design of the languages themselves.In support of this goal, we conducted four interconnected projects which variously study how JSON-based DSLs are designed, how abstraction can be integrated into those languages, how interfaces can be designed to specifically facilitate their manipulation, as well as how those programs might be automatically validated.Through these projects, we demonstrate that giving primacy to these textual interfaces as design elements can be valuable for end users.We find that this style of interventions are useful for helping end users learn, use, and re-use programs written in these languages.We primarily consider languages focused on data visualization tasks, as there has been substantial work in the visualization research community on this form of interface—although the lessons learned could be applied to any relevant domain.

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Section: Discussionmentioning

confidence: 99%

Understanding and Enhancing JSON-based DSL Interfaces for Visualization

McNutt¹

2023

Preprint

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“…Just as in other declarative languages, it can be challenging to debug [70], requiring the programmer to hold a potentially unfamiliar execution model held by the DSL in their mind to address possible subtle errors (providing hidden dependency and hard mental operations difficulties). We follow Hoffswell et al's [21] in-situ visualization in that our custom views offer a space for the application designer to surface relevant information into the editor to help end-users debug.…”

Section: Discussionmentioning

confidence: 99%

No Grammar to Rule Them All: A Survey of JSON-style DSLs for Visualization

McNutt

2022

IEEE Trans. Visual. Comput. Graphics

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Augmenting text-based programming with rich structured interactions has been explored in many ways. Among these, projectional editors offer an enticing combination of structure editing and domain-specific program visualization. Yet such tools are typically bespoke and expensive to produce, leaving them inaccessible to many DSL and application designers.We describe a relatively inexpensive way to build rich projectional editors for a large class of DSLs-namely, those defined using JSON. Given any such JSON-based DSL, we derive a projectional editor through (i) a language-agnostic mapping from JSON Schemas to structure-editor GUIs and (ii) an API for application designers to implement custom views for the domainspecific types described in a schema. We implement these ideas in a prototype, Prong, which we illustrate with several examples including the Vega and Vega-Lite data visualization DSLs.

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“…Data understanding aims to develop algorithms and tools to help comprehensively understand and debug data. One important measure is data visualization [10], which represents data in a more intuitive form, such as graphics, to facilitate communication. A notable example is warehouse systems, where entity-relation diagrams have been exploited to show the relationship between data schema, and graphical representations are developed to visualize logical structure among queries and outputs.…”

Section: Data Maintenancementioning

confidence: 99%

Data-centric AI: Perspectives and Challenges

Zha¹,

Bhat²,

Lai³

et al. 2023

Preprint

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The role of data in building AI systems has recently been significantly magnified by the emerging concept of data-centric AI (DCAI), which advocates a fundamental shift from model advancements to ensuring data quality and reliability. Although our community has continuously invested efforts into enhancing data in different aspects, they are often isolated initiatives on specific tasks. To facilitate the collective initiative in our community and push forward DCAI, we draw a big picture and bring together three general missions: training data development, evaluation data development, and data maintenance. We provide a top-level discussion on representative DCAI tasks and share perspectives. Finally, we list open challenges to motivate future exploration.

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Debugging Database Queries: A Survey of Tools, Techniques, and Users

Cited by 20 publications

References 93 publications

Understanding and Enhancing JSON-based DSL Interfaces for Visualization

Understanding and Enhancing JSON-based DSL Interfaces for Visualization

No Grammar to Rule Them All: A Survey of JSON-style DSLs for Visualization

Data-centric AI: Perspectives and Challenges

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