Relational symbolic execution of SQL code for unit testing of database programs

Symbolic execution is a technique enabling the automatic generation of test inputs that exercise a set of execution paths within a code unit to be tested. If the paths cover a sufficient part of the code under test, the test data offer a representative view of the actual behaviour of this code. This notably enables detecting errors and correcting faults. Relational databases are ubiquitous in software, but symbolic execution of code units that manipulate them remains a non-trivial problem, particularly because of the complex structure of such databases and the complex behaviour of SQL statements. Finding errors in such code units is yet critical, as it can avoid corrupting important data. In this work, we define a symbolic execution translating database manipulation code directly into constraints and integrate it with a more traditional symbolic execution of normal program code. The database tables are represented by relational symbols and the SQL statements by relational constraints over these symbols. An algorithm based on these principles is presented for the symbolic execution of simple Java methods that implement transactional use cases by reading and writing in a relational database, the latter subject to data integrity constraints. The algorithm is integrated in a test generation tool and experimented over sample code. The target language for the constraints produced by the tool is the SMT-Lib standard and the used solver is Microsoft Z3. The results show that the proposed approach enables generating meaningful test data, including valid database content, in reasonable time. In particular, the Z3 solver is shown to be more scalable than the Alloy solver, used in our previous work, for solving relational constraints

CRUD-DOM: a model for bridging the gap between the object-oriented and the relational paradigms : an enhanced performance assessment based on a case study

The development of database applications comprises three different tiers: application tier, database tier and finally the middle tier also known as the data access layer. The development of each tier per-se entails many challenges. Very often the most difficult challenges to be addressed derive from non-functional requirements, as productivity, usability, performance, reliability, high-availability and transparency. This paper is focused on defining and presenting a model for the data access layer aimed to integrate object-oriented application tiers and relational database tiers. The model addresses situations on which users need to explicitly write down complex static CRUD expressions and simultaneously get advantages regarding some non-functional requirements. The model, known as CRUD Data Object Model (CRUD-DOM), tackles the following non-functional requirements: performance, usability and productivity. The main contributions of this paper are threefold: 1) to present an extended model of CRUD-DOM; 2) to carry out an extended performance assessment based on a case study; 3) to present a tool, called CRUD Manager (CRUD-M), which provides automatic code generation with complementary support for software test and maintenance. The main outcome from this paper is the evidences that the pair CRUD-DOM and CRUD-M effectively addresses productivity, performance and usability requirements in the aforementioned context

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

The generation of e-learning exercise problems from subject ontologies

The teaching/ learning of cognitive skills, such as problem-solving, is an important goal in most forms of education. In well-structured subject areas certain exercise problem types may be precisely described by means of machine-processable knowledge structures or ontologies. These ontologies can readily be used to generate individual problem examples for the student, where each problem consists of a question and its solution. An example is given from the subject domain of computer databases

Heterogeneous data source integration for smart grid ecosystems based on metadata mining

The arrival of new technologies related to smart grids and the resulting ecosystem of applications andmanagement systems pose many new problems. The databases of the traditional grid and the variousinitiatives related to new technologies have given rise to many different management systems with several formats and different architectures. A heterogeneous data source integration system is necessary toupdate these systems for the new smart grid reality. Additionally, it is necessary to take advantage of theinformation smart grids provide. In this paper, the authors propose a heterogeneous data source integration based on IEC standards and metadata mining. Additionally, an automatic data mining framework isapplied to model the integrated information.Ministerio de Economía y Competitividad TEC2013-40767-