In this talk, we will discuss three popular static analysis tools for identifying information flows in mobile applications: FlowDroid combined with IccTA, AmanDroid, and DroidSafe. These tools are often compared with each other, yet, our experience shows that they are compared under different setup, rendering the comparisons largely inaccurate. To mitigate this problem, we performed a large, controlled, and independent comparison of the the tools, using common configuration setup and on the same set of benchmark applications. We observed that we cannot reproduce most of the results reported in earlier studies. We discuss reasons for such discrepancy, identify main causes of inaccuracy in existing tools, and provide suggestions for future research.

Julia Rubin

University of British Columbia

Canada

Project Auger (Automated Unittest Generator) watches your Python code while you write it and automatically generates all unit tests for your code, including all the mocks. Little or no work is required by the developer. Auger works like a smart Python debugger that sets breakpoints for each component you are interested in

Chris Laffra

Uber Technologies

Nowadays, a large amount of software is based on multi-tasked or asynchronous execution. This poses a substantial difficulty for automated testing: Assertions may only fail sporadically due to the non-deterministic scheduling, impeding reliable regression testing. This talk discusses this challenge and general solution approaches. We also focus on a specific idea that is to employ a static analysis inside the unit test execution, to get reproducible results for concurrent test cases.

Luc Bläser

Hochschule für Technik Rapperswil

Switzerland

Parasoft Jtest’s Unit Test Assistant is an IDE plug-in that helps guide users through the process of unit testing with easy one-click actions for creating, scaling, and maintaining unit tests. Parasoft Jtest’s UTA goes beyond ordinary unit testing tools by helping users create not only unit tests, but also mocks and assertions, and execute Java unit tests while collecting the coverage information. UTA helps uncover and test hidden coverage gaps with Jtest’s unique code coverage recommendations and quick-fix actions. It is pluggable into Eclipse or IntelliJ and is leveraging open source frameworks such as JUnit, Mockito, and PowerMock.

Leonid Borodaev

Unit tests are labor-intensive to write and maintain. In this talk we look into how well unit tests for a target software package can be extracted from the execution traces of client code. Our objective is to reduce the effort involved in creating test suites while minimizing the number and size of individual tests, and maximizing coverage. To evaluate the viability of our approach, we have chosen R, a programming language that is popular for data science applications. The challenges presented by R are its extreme dynamism, coerciveness, and lack of types. This combination decrease the efficacy of traditional test extraction techniques. We present Genthat, a tool developed over the last couple of years to non-invasively record execution traces of R programs and extract unit tests from those traces. We have carried out an evaluation on 1,545 packages comprising 1.7M lines of code. The tests extracted by Genthat improved code coverage from original 19% to 53%. The running time of the generated tests is 1.9 times faster than the code they came from.

Filip Křikava

Czech Technical University