Cassio L. Rodrigues

An elitist evolutionary algorithm for automatically generating test data

The development of an effective and efficient method for generating test data is an extremely challenging process which directly impacts the time that could be spent on activities relevant to software testing. Therefore, various researches related to this area have been carried out. Among the techniques for automatically generating test data, we highlight the use of metaheuristics, a promising area called Search-Based Software Testing (SBST). Thus, this article proposes the use of an Elitist Genetic Algorithm (GA) as a tool for generation and selection of test data applied in Mutation Testing for different benchmarks. The results indicate a good performance of the algorithm used in the benchmarks.

Shrinking a database to perform SQL mutation tests using an evolutionary algorithm

This paper tries to combine SQL mutation testing techniques with evolutionary computation aiming to improve the test data to SQL instructions. Based on a heuristic perspective it presents an approach that uses Genetic Algorithms (GA) to select tuples from an original database trying to reduce this one in an effective data set. The goal is to find a reduced data set which is able to detect a large number of faults in the SQL instructions of a given application. During the evolutionary process, the analysis of mutants is used to assess each set of data test selected by GA. The results obtained from experiments reveal a good performance using GA metaheuristic.

Applying genetic algorithms to data selection for SQL mutation analysis

This paper presents an approach to Structured Query Language (SQL) instruction tests via Mutation Analysis that uses Evolutionary Algorithms (GA) to select data to be used in the assessment of mutants. Based on a heuristic perspective, our aim is to select an effective data set which may help detect faults in the SQL instructions of a given application. The results obtained from experiments reveal a good performance using GA metaheuristic.

Refactoring VeriSc testbenches to improve the functional verification during the integration phase

This work proposes a refactoring for VeriSc testbenches in order to reduce the efforts that are required during the integration phase. This refactoring improves the reuse of testbench components that were developed during the verification of stand-alone blocks and preserves the other desirable features of VeriSC, such as tool support for the testbench construction, reuse of testbench components during the decomposition phase, synthesis of new coverage criteria during the composition phase.

An Evolutionary Approach to Test SELECT SQL Statements using Mutation Analysis

This paper proposes combining the mutation testing technique with evolutionary computing to improve the test data applied to SELECT instructions. From a heuristic perspective, this approach uses Genetic Algorithms to optimize tuples selection from an original database. In other words, generating a smaller amount of tuples able to detect faults in the instructions. Mutants are analyzed to evaluate each set of data tests selected during the evolutionary process. Once the appropriate reduced database was found, it can be used whenever the SQL statement test is necessary. The experimental results indicate that the metaheuristics outperform random methods and reach, in average, 80.3% of the optimal value.

Functional verification methodology using Hierarchical Coloured Petri Nets-based testbenches

We present a functional verification methodology that employs hierarchical coloured petri nets (HCPN) to describe the testbench. By this way, we are avoiding the absence of formal techniques concerning the testbench description and keeping a high-level of abstraction that is required in this phase of the project. The hierarchical (de)composition is the solution to deal with large designs. The methodology prescribes a way to (de)compose the testbench that promotes incremental development and reuse of testbench elements. Furthermore, our methodology provides tool support for the testbench creation. Experimental results concerning the functional verification of the MPEG 4 video decoder are presented.

Model checking in object-oriented Petri nets

We present model checking techniques for verifying an object oriented Petri net modeling language (RPOO). Our intention is turn the application of model checking on model-based software development more feasible. In order that we provide means of specifying objects properties regardless Petri nets details. We use Petri nets semantics just to construct the models state space. We present our algorithms to evaluate properties expressed in branching-time temporal logic CTL. We deal with explicit representation of state space emphasizing its OO features. Besides, we remark the results of some applications of our model checker.