Raquel Blanco

A tabu search algorithm for structural software testing

This paper presents a tabu search metaheuristic algorithm for the automatic generation of structural software tests. It is a novel work since tabu search is applied to the automation of the test generation task, whereas previous works have used other techniques such as genetic algorithms. The developed test generator has a cost function for intensifying the search and another for diversifying the search that is used when the intensification is not successful. It also combines the use of memory with a backtracking process to avoid getting stuck in local minima. Evaluation of the generator was performed using complex programs under test and large ranges for input variables. Results show that the developed generator is both effective and efficient.

Automated software testing using a metaheuristic technique based on Tabu search

The use of techniques for automating the generation of software test cases is very important as it can reduce the time and cost of this process. The latest methods for automatic generation of tests use metaheuristic search techniques, i.e. genetic algorithms and simulated annealing. There is a great deal of research into the use of genetic algorithms to obtain a specific coverage in software testing but there is none using the metaheuristic Tabu search technique. In this paper, we explain how we have created an efficient testing technique that combines Tabu search with Korel chaining approach. Our technique automatically generates test data in order to obtain branch coverage in software testing.

Automated test data generation using a scatter search approach

The techniques for the automatic generation of test cases try to efficiently find a small set of cases that allow a given adequacy criterion to be fulfilled, thus contributing to a reduction in the cost of software testing. In this paper we present and analyze two versions of an approach based on the scatter search metaheuristic technique for the automatic generation of software test cases using a branch coverage adequacy criterion. The first test case generator, called TCSS, uses a diversity property to extend the search of test cases to all branches of the program under test in order to generate test cases that cover these. The second, called TCSS-LS, is an extension of the previous test case generator which combines the diversity property with a local search method that allows the intensification of the search for test cases that cover the difficult branches. We present the results obtained by our generators and carry out a detailed comparison with many other generators, showing a good performance of our approach.

A First Approach to Test Case Generation for BPEL Compositions of Web Services Using Scatter Search

A challenging part of Software Testing entails the generation of test cases, which cost can be reduced by means of the use of techniques for automating this task. In this paper we present an approach based on the metaheuristic technique Scatter Search for the automatic test case generation of the BPEL business process. A transition coverage criterion is used as adequacy criterion.

Three Techniques for Competitive Lab Activities Based on Project-Oriented Learning in Information and Communication Technologies

Laboratory work is one of the most important activities in technical degrees. In these classes, students learn while carrying out tasks similar to those they could encounter in a professional environment. These activities help to strengthen the theoretical principles while allowing the students to develop useful skills for their careers. In this paper, we present three experiences (Lab Battle, Lab Race, and Lab Triathlon) in the organization of practical activities based on the paradigms of competitiveness and project-oriented learning. The goal of these techniques is to immerse the students in an environment as realistic as possible. In such scenarios, it is often important to be first, to think like the “bad guy” or to keep confidentiality. After three years applying these techniques, we have observed great motivation and excellent competences in the students. Moreover, cheating has been less frequent than in other types of lab assignments.

Test Adequacy Evaluation for the User-database Interaction: A Specification-Based Approach

Testing a database application is a challenging process where both the database and the user interaction have to be considered in the design of test cases. This paper describes a specification-based approach to guide the design of test inputs (both the test database and the user inputs) for a database application and to automatically evaluate the test adequacy. First, the system specification of the application is modelled: (1) the structure of the database and the user interface are represented in a single model, called Integrated Data Model (IDM), (2) the functional requirements are expressed as a set of business rules, written in terms of the IDM. Then, a MCDC-based criterion is applied over the business rules to automatically derive the situations of interest to be tested (test requirements), which guide the design of the test inputs. Finally, the adequacy of these test inputs is automatically evaluated to determine whether the test requirements are covered. The approach has been applied to the TPC-C benchmark. The results show that it allows designing test cases that are able to detect interesting faults which were located in the procedural code of the implementation.

A modular tool for automated coverage in software testing

Software testing is an expensive and difficult process which need much time. For this reason, the existence of tools that allow to decrease this effort is very important. Our tool automatically generates test cases in order to obtain branch coverage in software testing from a source code. All process is automatic (source code instrumentation and test cases generation) and therefore the total time used in software testing is reduced. We describe the modules of the tool and present the result we have obtained compared the needed time to generate the test cases with manual instrumentation and the needed time with an automatic process.

A test model for graph database applications: an MDA-based approach

NoSQL databases have given rise to new testing challenges due to the fact that they use data models and access modes to the data that differ from the relational databases. Testing relational database applications has attracted the interest of many researchers; but this is still not the case with NoSQL database applications. The approach presented in this paper defines a test model for graph database applications that takes into account the data model of this technology and the system specification. To automate the derivation of the test cases and the evaluation of their adequacy we propose a framework that places model-based testing into the model-driven architecture context.

Coverage-Aware Test Database Reduction

Functional testing of applications that process the information stored in databases often requires a careful design of the test database. The larger the test database, the more difficult it is to develop and maintain tests as well as to load and reset the test data. This paper presents an approach to reduce a database with respect to a set of SQL queries and a coverage criterion. The reduction procedures search the rows in the initial database that contribute to the coverage in order to find a representative subset that satisfies the same coverage as the initial database. The approach is automated and efficiently executed against large databases and complex queries. The evaluation is carried out over two real life applications and a well-known database benchmark. The results show a very large degree of reduction as well as scalability in relation to the size of the initial database and the time needed to perform the reduction.

Incremental test data generation for database queries

Testing database applications is a complex task since it involves designing test databases with meaningful test data in order to reveal faults and, at the same time, with a small size in order to carry out the testing process in an efficient way. This paper presents an automated approach to generating test data (test relational databases and test inputs for query parameters) for a set of SQL queries, with the aim of covering test requirements as obtained from said queries. The test data generation follows an incremental approach where, in each increment, test data are generated to cover a test requirement by re-using test data previously generated for other test requirements. The test data generation for each test requirement is formulated as a constraint satisfaction problem, where constraints are derived from the test requirement, initial database states and previously generated test data. The generation process is fully automated and supports the execution on complex queries and databases. Evaluation is carried out on a real life application, and the results show that small-size generated test relational databases achieve high coverage scores for the queries under test in a short generating time.