The XDa-TA system for automated grading of SQL query assignments

Bhangdiya, Amol; Chandra, Bikash; Kar, Biplab; Radhakrishnan, Bharath; Reddy, K. Vishal; Shah, Sejal; Sudarshan, S.

doi:10.1109/icde.2015.7113403

Cited by 16 publications

(11 citation statements)

References 5 publications

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“…Several systems have been developed to assist instructors in grading SQL queries. In [26], the authors describe XDaTa, a system that compares the results of a student's query to the results of the solution query. The system can also generate test set data for SQL queries.…”

Section: Literature Reviewmentioning

confidence: 99%

ScaffoldSQL: Using Parson’s Problems to Support Database Pedagogy

Borchert¹,

Walia²

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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This paper examines ScaffoldSQL, an interactive tool for helping students learn SQL through a system of interactive scaffolded exercises using Parson's problems. In the system, students are posed with a problem to solve using SQL. They start by attempting to answer the question using free-form text. If they get the problem wrong, they can use a Parson's problem interface to simplify the problem. After completing the problem, students are given one of two "secret words," which allows instructors to track student progress without the need to install anything beyond their typical LMS. The system is designed to help instructors of flipped classrooms identify students who are struggling early, while simultaneously providing immediate feedback for students as they are learning. The system also provides tools for content creation and data gathering for research and development purposes.

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Section: Literature Reviewmentioning

confidence: 99%

ScaffoldSQL: Using Parson’s Problems to Support Database Pedagogy

Borchert¹,

Walia²

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…XData is a mutation testing tool for SQL: given an input query, XData generates mutations of the query and then asks the underlying SMT solver to construct a distinguishing input to kill the mutant. It then adds the generated distinguishing input to the test suite for database testing or grading [Bhangdiya et al 2015]. Tesma is a concolic test engine that allows testing database applications under the concolic test framework.…”

Section: Related Workmentioning

confidence: 99%

Speeding up symbolic reasoning for relational queries

Wang

Cheung

Bodík

2018

Proc. ACM Program. Lang.

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The ability to reason about relational queries plays an important role across many types of database applications, such as test data generation, query equivalence checking, and computer-assisted query authoring. Unfortunately, symbolic reasoning about relational queries can be challenging because relational tables are multisets (bags) of tuples, and the underlying languages, such as SQL, can introduce complex computation among tuples. We propose a space refinement algorithm that soundly reduces the space of tables such applications need to consider. The refinement procedure, independent of the specific dataset application, uses the abstract semantics of the query language to exploit the provenance of tuples in the query output to prune the search space. We implemented the refinement algorithm and evaluated it on SQL using three reasoning tasks: bounded query equivalence checking, test generation for applications that manipulate relational data, and concolic testing of database applications. Using real world benchmarks, we show that our refinement algorithm significantly speeds up (up to 100×) the SQL solver when reasoning about a large class of challenging SQL queries, such as those with aggregations. CCS Concepts: • Theory of computation → Logic and verification; Database query languages (principles);

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“…In [6] we describe the XDa-TA grading tool which uses datasets generated by the techniques presented in this paper for checking the correctness of student SQL queries. Here we describe how to efficiently check student queries against given correct queries.…”

Section: Grading Student Sql Queriesmentioning

confidence: 99%

Data generation for testing and grading SQL queries

et al. 2015

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Correctness of SQL queries is usually tested by executing the queries on one or more datasets. Erroneous queries are often the results of small changes or mutations of the correct query. A mutation Q' of a query Q is killed by a dataset D if Q(D) = Q'(D). Earlier work on the XData system showed how to generate datasets that kill all mutations in a class of mutations that included join type and comparison operation mutations.In this paper, we extend the XData data generation techniques to handle a wider variety of SQL queries and a much larger class of mutations. We have also built a system for grading SQL queries using the datasets generated by XData. We present a study of the effectiveness of the datasets generated by the extended XData approach, using a variety of queries including queries submitted by students as part of a database course. We show that the XData datasets outperform predefined datasets as well as manual grading done earlier by teaching assistants, while also avoiding the drudgery of manual correction. Thus, we believe that our techniques will be of great value to database course instructors and TAs, particularly to those of MOOCs. It will also be valuable to database application developers and testers for testing SQL queries.

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The XDa-TA system for automated grading of SQL query assignments

Cited by 16 publications

References 5 publications

ScaffoldSQL: Using Parson’s Problems to Support Database Pedagogy

ScaffoldSQL: Using Parson’s Problems to Support Database Pedagogy

Speeding up symbolic reasoning for relational queries

Data generation for testing and grading SQL queries

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