66,173 research outputs found
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Accelerating Electromigration Aging: Fast Failure Detection for Nanometer ICs
For practical testing and detection of electromigration (EM) induced failures in dual damascene copper interconnects, one critical issue is creating stressing conditions to induce the chip to fail exclusively under EM in a very short period of time so that EM sign-off and validation can be carried out efficiently. Existing acceleration techniques, which rely on increasing temperature and current densities beyond the known limits, also accelerate other reliability effects making it very difficult, if not impossible, to test EM in isolation. In this article, we propose novel EM wear-out acceleration techniques to address the aforementioned issue. First we show that multi-segment interconnects with reservoir and sink structures can be exploited to significantly speedup the EM wear-out process. Based on this observation, we propose three strategies to accelerate EM induced failure: reservoir-enhanced acceleration, sink-enhanced acceleration, and a hybrid method that combines both reservoir and sink structures. We then propose several configurable interconnect structures that exploit atomic reservoirs and sinks for accelerated EM testing. Such configurable interconnect structures are very flexible and can be used to achieve significant lifetime reductions at the cost of some routing resources. Using the proposed technique, EM testing can be carried out at nominal current densities, and at a much lower temperature compared to traditional testing methods. This is the most significant contribution of this work since, to our knowledge, this is the only method that allows EM testing to be performed in a controlled environment without the risk of invoking other reliability effects that are also accelerated by elevated temperature and current density. Simulation results show that, using the proposed method, we can reduce the EM lifetime of a chip from 10 years down to a few hours 10^5X acceleration under the 150C temperature limit, which is sufficient for practical EM testing of typical nanometer CMOS ICs
Enablers and Impediments for Collaborative Research in Software Testing: An Empirical Exploration
When it comes to industrial organizations, current collaboration efforts in
software engineering research are very often kept in-house, depriving these
organizations off the skills necessary to build independent collaborative
research. The current trend, towards empirical software engineering research,
requires certain standards to be established which would guide these
collaborative efforts in creating a strong partnership that promotes
independent, evidence-based, software engineering research. This paper examines
key enabling factors for an efficient and effective industry-academia
collaboration in the software testing domain. A major finding of the research
was that while technology is a strong enabler to better collaboration, it must
be complemented with industrial openness to disclose research results and the
use of a dedicated tooling platform. We use as an example an automated test
generation approach that has been developed in the last two years
collaboratively with Bombardier Transportation AB in Sweden
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.Comment: In Proceedings SSV 2012, arXiv:1211.587
Functional Requirements-Based Automated Testing for Avionics
We propose and demonstrate a method for the reduction of testing effort in
safety-critical software development using DO-178 guidance. We achieve this
through the application of Bounded Model Checking (BMC) to formal low-level
requirements, in order to generate tests automatically that are good enough to
replace existing labor-intensive test writing procedures while maintaining
independence from implementation artefacts. Given that existing manual
processes are often empirical and subjective, we begin by formally defining a
metric, which extends recognized best practice from code coverage analysis
strategies to generate tests that adequately cover the requirements. We then
formulate the automated test generation procedure and apply its prototype in
case studies with industrial partners. In review, the method developed here is
demonstrated to significantly reduce the human effort for the qualification of
software products under DO-178 guidance
FORTEST: Formal methods and testing
Formal methods have traditionally been used for specification and development of software. However there are potential benefits for the testing stage as well. The panel session associated with this paper explores the usefulness
or otherwise of formal methods in various contexts for improving software testing. A number of different possibilities for the use of formal methods are explored and questions raised. The contributors are all members of the UK FORTEST Network on formal methods and testing. Although
the authors generally believe that formal methods
are useful in aiding the testing process, this paper is intended to provoke discussion. Dissenters are encouraged to put their views to the panel or individually to the authors
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Automatic generation of test sequences form EFSM models using evolutionary algorithms
Automated test data generation through evolutionary testing (ET) is a topic of interest to the software engineering community. While there are many ET-based techniques for automatically generating test data from code, the problem of generating test data from an extended finite state machine (EFSMs) is more complex and has received little attention. In this paper, we introduce a novel approach that addresses the problem of generating input test sequences that trigger given feasible paths in an EFSM model by employing an ET-based technique. The proposed approach expresses the problem as a search for input parameters to be applied to a set of functions to be called sequentially. In order to apply ET-based technique, a new fitness function is introduced to cope with the case when a test target involves calls to a set of transitions sequentially. We evaluate our approach empirically using five sets of randomly generated paths through two EFSM case studies: INRES and class 2 transport protocols. In the experiments, we apply two search techniques: a random and an ET-based which utilizes our new fitness function. Experimental results show that the proposed approach produces input test sequences that trigger all the feasible paths used with a success rate of 100%, however, the random technique failed in most cases with a success rate of 20.8%
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