Unit Test Generation Research Articles

1600 faults in 100 projects: automatically finding faults while achieving high coverage with EvoSuite

Automated unit test generation techniques traditionally follow one of two goals: Either they try to find violations of automated oracles (e.g., assertions, contracts, undeclared exceptions), or they aim to produce representative test suites (e.g., satisfying branch coverage) such that a developer can manually add test oracles. Search-based testing (SBST) has delivered promising results when it comes to achieving coverage, yet the use in conjunction with automated oracles has hardly been explored, and is generally hampered as SBST does not scale well when there are too many testing targets. In this paper we present a search-based approach to handle both objectives at the same time, implemented in the EvoSuite tool. An empirical study applying EvoSuite on 100 randomly selected open source software projects (the SF100 corpus) reveals that SBST has the unique advantage of being well suited to perform both traditional goals at the same time—efficiently triggering faults, while producing representative test sets for any chosen coverage criterion. In our study, EvoSuite detected twice as many failures in terms of undeclared exceptions as a traditional random testing approach, witnessing thousands of real faults in the 100 open source projects. Two out of every five classes with undeclared exceptions have actual faults, but these are buried within many failures that are caused by implicit preconditions. This “noise” can be interpreted as either a call for further research in improving automated oracles—or to make tools like EvoSuite an integral part of software development to enforce clean program interfaces.

CTGEN - a Unit Test Generator for C

We present a new unit test generator for C code, CTGEN. It generates test data for C1 structural coverage and functional coverage based on pre-/post-condition specifications or internal assertions. The generator supports automated stub generation, and data to be returned by the stub to the unit under test (UUT) may be specified by means of constraints. The typical application field for CTGEN is embedded systems testing; therefore the tool can cope with the typical aliasing problems present in low-level C, including pointer arithmetics, structures and unions. CTGEN creates complete test procedures which are ready to be compiled and run against the UUT. In this paper we describe the main features of CTGEN, their technical realisation, and we elaborate on its performance in comparison to a list of competing test generation tools. Since 2011, CTGEN is used in industrial scale test campaigns for embedded systems code in the automotive domain.

Generating Unit Tests for Floating Point Embedded Software using Compositional Dynamic Symbolic Execution

We present a method that would integrate both: compositional dynamic symbolic execution and search-based test data generation methods to achieve better code coverage for software that largely depends on floating point computations. We have implemented our method as an extension of a well-know symbolic execution engine – PEX. Our extension implements search-based testing as an optimization technique using AVM method. We present coverage comparison for several benchmark functions. Ill. 1, bibl. 17, tabl. 2 (in English; abstracts in English and Lithuanian).DOI: http://dx.doi.org/10.5755/j01.eee.122.6.1814

Mutation-Driven Generation of Unit Tests and Oracles

To assess the quality of test suites, mutation analysis seeds artificial defects (mutations) into programs; a nondetected mutation indicates a weakness in the test suite. We present an automated approach to generate unit tests that detect these mutations for object-oriented classes. This has two advantages: First, the resulting test suite is optimized toward finding defects modeled by mutation operators rather than covering code. Second, the state change caused by mutations induces oracles that precisely detect the mutants. Evaluated on 10 open source libraries, our μtest prototype generates test suites that find significantly more seeded defects than the original manually written test suites.

Comprehensive aspect weaving for Java

Aspect-oriented programming (AOP) has been successfully applied to application code thanks to techniques such as Java bytecode instrumentation. Unfortunately, with existing AOP frameworks for Java such as AspectJ, aspects cannot be woven into the standard Java class library. This restriction is particularly unfortunate for aspects that would benefit from comprehensive aspect weaving with complete method coverage, such as profiling or debugging aspects. In this article we present MAJOR, a new tool for comprehensive aspect weaving, which ensures that aspects are woven into all classes loaded in a Java Virtual Machine, including those in the standard Java class library. MAJOR includes the pluggable module CARAJillo, which supports efficient access to a complete and customizable calling context representation. We validate our approach with three case studies. Firstly, we weave existing profiling aspects with MAJOR which otherwise would generate incomplete profiles. Secondly, we introduce an aspect for memory leak detection that also benefits from comprehensive weaving. Thirdly, we present an aspect subsuming the functionality of ReCrash, an existing tool based on low-level bytecode instrumentation techniques that generates unit tests to reproduce program failures. Our aspect-based tools are concisely implemented in a few lines of code, and leverage MAJOR and CARAJillo for comprehensive aspect weaving and for efficient access to calling context information.

GenUTest: a unit test and mock aspect generation tool

Unit testing plays a major role in the software development process. What started as an ad hoc approach is becoming a common practice among developers. It enables the immediate detection of bugs introduced into a unit whenever code changes occur. Hence, unit tests provide a safety net of regression tests and validation tests which encourage developers to refactor existing code with greater confidence. One of the major corner stones of the agile development approach is unit testing. Agile methods require all software classes to have unit tests that can be executed by an automated unit-testing framework. However, not all software systems have unit tests. When changes to such software are needed, writing unit tests from scratch, which is hard and tedious, might not be cost effective. In this paper we propose a technique which automatically generates unit tests for software that does not have such tests. We have implemented GenUTest, a prototype tool which captures and logs interobject interactions occurring during the execution of Java programs, using the aspect-oriented language AspectJ. These interactions are used to generate JUnit tests. They also serve in generating mock aspects—mock object-like entities, which enable testing units in isolation. The generated JUnit tests and mock aspects are independent of the tool, and can be used by developers to perform unit tests on the software. Comprehensiveness of the unit tests depends on the software execution. We applied GenUTest to several open source projects such as NanoXML and JODE. We present the results, explain the limitations of the tool, and point out direction to future work to improve the code coverage provided by GenUTest and its scalability.

Tool-assisted unit-test generation and selection based on operational abstractions

Unit testing, a common step in software development, presents a challenge. When produced manually, unit test suites are often insufficient to identify defects. The main alternative is to use one of a variety of automatic unit-test generation tools: these are able to produce and execute a large number of test inputs that extensively exercise the unit under test. However, without a priori specifications, programmers need to manually verify the outputs of these test executions, which is generally impractical. To reduce this cost, unit-test selection techniques may be used to help select a subset of automatically generated test inputs. Then programmers can verify their outputs, equip them with test oracles, and put them into the existing test suite. In this paper, we present the operational violation approach for unit-test generation and selection, a black-box approach without requiring a priori specifications. The approach dynamically generates operational abstractions from executions of the existing unit test suite. These operational abstractions guide test generation tools to generate tests to violate them. The approach selects those generated tests violating operational abstractions for inspection. These selected tests exercise some new behavior that has not been exercised by the existing tests. We implemented this approach by integrating the use of Daikon (a dynamic invariant detection tool) and Parasoft Jtest (a commercial Java unit testing tool), and conducted several experiments to assess the approach.

Unit tests reloaded: parameterized unit testing with symbolic execution

Unit tests are becoming popular. Are there ways to automate the generation of good unit tests? Parameterized unit tests are unit tests that depend on inputs. PUTs describe behavior more concisely than traditional unit tests. We use symbolic execution techniques and constraint solving to find inputs for PUTs that achieve high code coverage, to turn existing unit tests into PUTs, and to generate entirely new PUTs that describe an existing implementation's behavior. Traditional testing benefits from these techniques because test inputs - including the behavior of entire classes - can often be generated automatically from compact PUTs