A Characteristic Study of Parameterized Unit Tests in .NET Open Source Projects

In the past decade, parameterized unit testing has emerged as a promising method to specify program behaviors under test in the form of unit tests. Developers can write parameterized unit tests (PUTs), unit-test methods with parameters, in contrast to conventional unit tests, without parameters. The use of PUTs can enable powerful test generation tools such as Pex to have strong test oracles to check against, beyond just uncaught runtime exceptions. In addition, PUTs have been popularly supported by various unit testing frameworks for .NET and the JUnit framework for Java. However, there exists no study to offer insights on how PUTs are written by developers in either proprietary or open source development practices, posing barriers for various stakeholders to bring PUTs to widely adopted practices in software industry. To fill this gap, we first present categorization results of the Microsoft MSDN Pex Forum posts (contributed primarily by industrial practitioners) related to PUTs. We then use the categorization results to guide the design of the first characteristic study of PUTs in .NET open source projects. We study hundreds of PUTs that open source developers wrote for these open source projects. Our study findings provide valuable insights for various stakeholders such as current or prospective PUT writers (e.g., developers), PUT framework designers, test-generation tool vendors, testing researchers, and testing educators

Automatic Refactoring for Renamed Clones in Test Code

Unit testing plays an essential role in software development and maintenance, especially in Test-Driven Development. Conventional unit tests, which have no input parameters, often exercise similar scenarios with small variations to achieve acceptable coverage, which often results in duplicated code in test suites. Test code duplication hinders comprehension of test cases and maintenance of test suites. Test refactoring is a potential tool for developers to use to control technical debt arising due to test cloning. In this thesis, we present a novel tool, JTestParametrizer, for automatically refactoring method-scope renamed clones in test suites. We propose three levels of refactoring to parameterize type, data, and behaviour differences in clone pairs. Our technique works at the Abstract Syntax Tree level by extracting a parameterized template utility method and instantiating it with appropriate parameter values. We applied our technique to 5 open-source Java benchmark projects and conducted an empirical study on our results. Our technique examined 14,431 test methods in our benchmark projects and identified 415 renamed clone pairs as effective candidates for refactoring. On average, 65% of the effective candidates (268 clone pairs) in our test suites are refactorable using our technique. All of the refactored test methods are compilable, and 94% of them pass when executed as tests. We believe that our proposed refactorings generally improve code conciseness, reduce the amount of duplication, and make test suites easier to maintain and extend

Detecting Test Clones with Static Analysis

Large-scale software systems often have correspondingly complicated test suites, which are diffi cult for developers to construct and maintain. As systems evolve, engineers must update their test suite along with changes in the source code. Tests created by duplicating and modifying previously existing tests (clones) can complicate this task. Several testing technologies have been proposed to mitigate cloning in tests, including parametrized unit tests and test theories. However, detecting opportunities to improve existing test suites is labour intensive. This thesis presents a novel technique for etecting similar tests based on type hierarchies and method calls in test code. Using this technique, we can track variable history and detect test clones based on test assertion similarity. The thesis further includes results from our empirical study of 10 benchmark systems using this technique which suggest that test clone detection by our technique will aid test de-duplication eff orts in industrial systems

Detecting Test Clones with Static Analysis

Large-scale software systems often have correspondingly complicated test suites, which are diffi cult for developers to construct and maintain. As systems evolve, engineers must update their test suite along with changes in the source code. Tests created by duplicating and modifying previously existing tests (clones) can complicate this task. Several testing technologies have been proposed to mitigate cloning in tests, including parametrized unit tests and test theories. However, detecting opportunities to improve existing test suites is labour intensive. This thesis presents a novel technique for etecting similar tests based on type hierarchies and method calls in test code. Using this technique, we can track variable history and detect test clones based on test assertion similarity. The thesis further includes results from our empirical study of 10 benchmark systems using this technique which suggest that test clone detection by our technique will aid test de-duplication eff orts in industrial systems

PEER Testbed Study on a Laboratory Building: Exercising Seismic Performance Assessment

From 2002 to 2004 (years five and six of a ten-year funding cycle), the PEER Center organized the majority of its research around six testbeds. Two buildings and two bridges, a campus, and a transportation network were selected as case studies to “exercise” the PEER performance-based earthquake engineering methodology. All projects involved interdisciplinary teams of researchers, each producing data to be used by other colleagues in their research. The testbeds demonstrated that it is possible to create the data necessary to populate the PEER performancebased framing equation, linking the hazard analysis, the structural analysis, the development of damage measures, loss analysis, and decision variables. This report describes one of the building testbeds—the UC Science Building. The project was chosen to focus attention on the consequences of losses of laboratory contents, particularly downtime. The UC Science testbed evaluated the earthquake hazard and the structural performance of a well-designed recently built reinforced concrete laboratory building using the OpenSees platform. Researchers conducted shake table tests on samples of critical laboratory contents in order to develop fragility curves used to analyze the probability of losses based on equipment failure. The UC Science testbed undertook an extreme case in performance assessment—linking performance of contents to operational failure. The research shows the interdependence of building structure, systems, and contents in performance assessment, and highlights where further research is needed. The Executive Summary provides a short description of the overall testbed research program, while the main body of the report includes summary chapters from individual researchers. More extensive research reports are cited in the reference section of each chapter

Cyclic behavior of masonry shear walls retrofitted with engineered cementitious composite and pseudoelastic shape memory alloy

The behavior of masonry shear walls reinforced with pseudoelastic Ni–Ti shape memory alloy (SMA) strips and engineered cementitious composite (ECC) sheets is the main focus of this paper. The walls were subjected to quasi-static cyclic in-plane loads and evaluated by using Abaqus. Eight cases of strengthening of masonry walls were investigated. Three masonry walls were strengthened with different thicknesses of ECC sheets using epoxy as adhesion, three walls were reinforced with different thicknesses of Ni–Ti strips in a cross form bonded to both the surfaces of the wall, and one was utilized as a reference wall without any reinforcing element. The final concept was a hybrid of strengthening methods in which the Ni–Ti strips were embedded in ECC sheets. The effect of mesh density on analytical outcomes is also discussed. A parameterized analysis was conducted to examine the influence of various variables such as the thickness of the Ni–Ti strips and that of ECC sheets. The results show that using the ECC sheet in combination with pseudoelastic Ni–Ti SMA strips enhances the energy absorption capacity and stiffness of masonry walls, demonstrating its efficacy as a reinforcing method

Test Clone Detection via Assertion Fingerprints

Large software systems require large test suites to achieve high coverage. Test suites often employ closed unit tests that are self-contained and have no input parameters. To achieve acceptable coverage with self-contained unit tests, developers often clone existing tests and reproduce both boilerplate and essential environment setup code as well as assertions. Existing technologies such as parametrized unit tests and theories could mitigate cloning in test suites. These technologies give developers new ways to express refactorings. However, they do not help detect refactorable clones in the first place, which requires tedious manual effort. This thesis proposes a novel technique, assertion fingerprints, for detecting clones based on the set of assertion/fail calls in test methods. Assertion fingerprints encode the control flow around the ordered set of assertions in methods. We have implemented clone set detection using assertion fingerprints and applied it to 10 test suites for open-source Java programs. We provide an empirical study and a qualitative analysis of our results. Assertion fingerprints enable the discovery of test clones that exhibit strong structural similarities and are amenable to refactoring. Our technique delivers an overall 75% true positive rate on our benchmarks and identifies 44% of the benchmark test methods as clones