67,692 research outputs found
Constraint-based generation of database states for testing database applications
Testing is essential for quality assurance of database applications. To test the quality of database applications, it usually requires test inputs consisting of both program input values and corresponding database states. However, producing these tests could be very tedious and labor-intensive in a non-automated way. It is thus imperative to conduct automatic test generation helping reduce human efforts.
The research focuses on automatic test generation of both program input values and corresponding database states for testing database applications. We develop our approaches based on the Dynamic Symbolic Execution (DSE) technique to achieve various testing requirements. We formalize a problem for program-input-generation given an existing database state to achieve high program code coverage and propose an approach that conducts program-input-generation through auxiliary query construction based on the intermediate information accumulated during DSE's exploration. We develop a technique to generate database states to achieve advanced code coverage criteria such as Boundary Value Coverage and Logical Coverage. We develop an approach that constructs synthesized database interactions to guide the DSE's exploration to collect constraints for both program inputs and associated database states. In this way, we bridge various constraints within a database application: query-construction constraints, query constraints, database schema constraints, and query-result-manipulation constraints. We develop an approach that generates tests for mutation testing on database applications. We use a state-of-the-art white-box testing tool called Pex for .NET from Microsoft Research as the DSE engine. Empirical evaluation results show that our approaches are able to generate effective program input values and sufficient database states to achieve various testing requirements
SmartUnit: Empirical Evaluations for Automated Unit Testing of Embedded Software in Industry
In this paper, we aim at the automated unit coverage-based testing for
embedded software. To achieve the goal, by analyzing the industrial
requirements and our previous work on automated unit testing tool CAUT, we
rebuild a new tool, SmartUnit, to solve the engineering requirements that take
place in our partner companies. SmartUnit is a dynamic symbolic execution
implementation, which supports statement, branch, boundary value and MC/DC
coverage. SmartUnit has been used to test more than one million lines of code
in real projects. For confidentiality motives, we select three in-house real
projects for the empirical evaluations. We also carry out our evaluations on
two open source database projects, SQLite and PostgreSQL, to test the
scalability of our tool since the scale of the embedded software project is
mostly not large, 5K-50K lines of code on average. From our experimental
results, in general, more than 90% of functions in commercial embedded software
achieve 100% statement, branch, MC/DC coverage, more than 80% of functions in
SQLite achieve 100% MC/DC coverage, and more than 60% of functions in
PostgreSQL achieve 100% MC/DC coverage. Moreover, SmartUnit is able to find the
runtime exceptions at the unit testing level. We also have reported exceptions
like array index out of bounds and divided-by-zero in SQLite. Furthermore, we
analyze the reasons of low coverage in automated unit testing in our setting
and give a survey on the situation of manual unit testing with respect to
automated unit testing in industry.Comment: In Proceedings of 40th International Conference on Software
Engineering: Software Engineering in Practice Track, Gothenburg, Sweden, May
27-June 3, 2018 (ICSE-SEIP '18), 10 page
A Symbolic Execution Algorithm for Constraint-Based Testing of Database Programs
In so-called constraint-based testing, symbolic execution is a common
technique used as a part of the process to generate test data for imperative
programs. Databases are ubiquitous in software and testing of programs
manipulating databases is thus essential to enhance the reliability of
software. This work proposes and evaluates experimentally a symbolic ex-
ecution algorithm for constraint-based testing of database programs. First, we
describe SimpleDB, a formal language which offers a minimal and well-defined
syntax and seman- tics, to model common interaction scenarios between pro-
grams and databases. Secondly, we detail the proposed al- gorithm for symbolic
execution of SimpleDB models. This algorithm considers a SimpleDB program as a
sequence of operations over a set of relational variables, modeling both the
database tables and the program variables. By inte- grating this relational
model of the program with classical static symbolic execution, the algorithm
can generate a set of path constraints for any finite path to test in the
control- flow graph of the program. Solutions of these constraints are test
inputs for the program, including an initial content for the database. When the
program is executed with respect to these inputs, it is guaranteed to follow
the path with re- spect to which the constraints were generated. Finally, the
algorithm is evaluated experimentally using representative SimpleDB models.Comment: 12 pages - preliminary wor
Relational Constraint Driven Test Case Synthesis for Web Applications
This paper proposes a relational constraint driven technique that synthesizes
test cases automatically for web applications. Using a static analysis,
servlets can be modeled as relational transducers, which manipulate backend
databases. We present a synthesis algorithm that generates a sequence of HTTP
requests for simulating a user session. The algorithm relies on backward
symbolic image computation for reaching a certain database state, given a code
coverage objective. With a slight adaptation, the technique can be used for
discovering workflow attacks on web applications.Comment: In Proceedings TAV-WEB 2010, arXiv:1009.330
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