This tutorial covers the basics of how to use statistical tests to evaluate and compare search-algorithms, in particular when applied on software engineering problems. Search-algorithms like Hill Climbing and Genetic Algorithms are randomised. Running ...

This keynote discusses the use of Predictive Analytics for Software Engineering, and in particular for Software Defect Prediction and Software Testing, by presenting the latest results achieved in these fields leveraging Artificial Intelligence, Search-...

EvoSuite is a search-based tool that automatically generates executable unit tests for Java code (JUnit tests). This paper summarises the results and experiences of EvoSuite's participation at the sixth unit testing competition at SBST 2018, where EvoS...

We report on the advances in this sixth edition of the JUnit tool competitions. This year the contest introduces new benchmarks to assess the performance of JUnit testing tools on different types of real-world software projects. Following on the ...

This paper discusses the performance of the automated testing tool for Java called T3 and compares it with few other tools and human written tests in a benchmark set by the Java Unit Testing Tool Contest 2018. Since all the compared tools rely on ...

A self-adaptive system (SAS) can reconfigure at run time in response to uncertainty and/or adversity to continually deliver an acceptable level of service. An SAS can experience uncertainty during execution in terms of environmental conditions for which ...

In specification-based test generation, sometimes having a formal specification is not sufficient, since the specification may be in a different formalism from that required by the generation approach being used. In this paper, we deal with this problem ...

In this paper, we analyze the effect of reducing object redundancy in random testing, by comparing the Randoop random testing tool with a version of the tool that disregards tests that only produce objects that have been previously generated by other ...

Dozens of criteria have been proposed to judge testing adequacy. Such criteria are important, as they guide automated generation efforts. Yet, the current use of such criteria in automated generation contrasts how such criteria are used by humans. For a ...

This paper explores the usage of search-based techniques for the Testing Resource Allocation Problem (TRAP). We focus on the analysis of the literature, surveying the research proposals where search-based techniques are exploited for different ...

Test data generation is a tedious and laborious process. Search-based Software Testing (SBST) automatically generates test data optimising structural test criteria using metaheuristic algorithms. In essence, metaheuristic algorithms are systematic trial-...

While adequacy criteria offer an end-point for testing, they do not mandate how targets are covered. Branch Coverage may be attained through direct calls to methods, or through indirect calls between methods. Automated generation is biased towards the ...

There is a growing realization that optimization can be applied to many aspects of the software development process: a research area known as Search Based Software Engineering (SBSE). Search Based Software Testing - one of the largest research areas ...