Oscar Luis Vera-Pérez

Benjamin Danglot, Oscar Luis Vera-Pérez, Benoit Baudry et al.

In the literature, there is a rather clear segregation between manually written tests by developers and automatically generated ones. In this paper, we explore a third solution: to automatically improve existing test cases written by developers. We present the concept, design, and implementation of a system called \dspot, that takes developer-written test cases as input (junit tests in Java) and synthesizes improved versions of them as output. Those test improvements are given back to developers as patches or pull requests, that can be directly integrated in the main branch of the test code base. We have evaluated DSpot in a deep, systematic manner over 40 real-world unit test classes from 10 notable and open-source software projects. We have amplified all test methods from those 40 unit test classes. In 26/40 cases, DSpot is able to automatically improve the test under study, by triggering new behaviors and adding new valuable assertions. Next, for ten projects under consideration, we have proposed a test improvement automatically synthesized by \dspot to the lead developers. In total, 13/19 proposed test improvements were accepted by the developers and merged into the main code base. This shows that DSpot is capable of automatically improving unit-tests in real-world, large-scale Java software.

Oscar Luis Vera-Pérez, Martin Monperrus, Benoit Baudry

Descartes is a tool that implements extreme mutation operators and aims at finding pseudo-tested methods in Java projects. It leverages the efficient transformation and runtime features of PIT. The demonstration compares Descartes with Gregor, the default mutation engine provided by PIT, in a set of real open source projects. It considers the execution time, number of mutants created and the relationship between the mutation scores produced by both engines. It provides some insights on the main features exposed by Descartes.

Oscar Luis Vera-Pérez, Benjamin Danglot, Martin Monperrus et al.

An extreme transformation removes the body of a method that is reached by one test case at least. If the test suite passes on the original program and still passes after the extreme transformation, the transformation is said to be undetected, and the test suite needs to be improved. In this work we propose a technique to automatically determine which of the following three reasons prevent the detection of the extreme transformation is : the test inputs are not sufficient to infect the state of the program; the infection does not propagate to the test cases; the test cases have a weak oracle that does not observe the infection. We have developed Reneri, a tool that observes the program under test and the test suite in order to determine runtime differences between test runs on the original and the transformed method. The observations gathered during the analysis are processed by Reneri to suggest possible improvements to the developers. We evaluate Reneri on 15 projects and a total of 312 undetected extreme transformations. The tool is able to generate a suggestion for each each undetected transformation. For 63% of the cases, the existing test cases can infect the program state, meaning that undetected transformations are mostly due to observability and weak oracle issues. Interviews with developers confirm the relevance of the suggested improvements and experiments with state of the art automatic test generation tools indicate that no tool can improve the existing test suites to fix all undetected transformations.