664 research outputs found
A Test Vector Minimization Algorithm Based On Delta Debugging For Post-Silicon Validation Of Pcie Rootport
In silicon hardware design, such as designing PCIe devices, design verification is an essential part of the design process, whereby the devices are subjected to a series of tests that verify the functionality. However, manual debugging is still widely used in post-silicon validation and is a major bottleneck in the validation process. The reason is a large number of tests vectors have to be analyzed, and this slows process down. To solve the problem, a test vector minimizer algorithm is proposed to eliminate redundant test vectors that do not contribute to reproduction of a test failure, hence, improving the debug throughput. The proposed methodology is inspired by the Delta Debugging algorithm which is has been used in automated software debugging but not in post-silicon hardware debugging. The minimizer operates on the principle of binary partitioning of the test vectors, and iteratively testing each subset (or complement of set) on a post-silicon System-Under-Test (SUT), to identify and eliminate redundant test vectors. Test results using test vector sets containing deliberately introduced erroneous test vectors show that the minimizer is able to isolate the erroneous test vectors. In test cases containing up to 10,000 test vectors, the minimizer requires about 16ns per test vector in the test case when only one erroneous test vector is present. In a test case with 1000 vectors including erroneous vectors, the same minimizer requires about 140μs per erroneous test vector that is injected. Thus, the minimizer’s CPU consumption is significantly smaller than the typical amount of time of a test running on SUT. The factors that significantly impact the performance of the algorithm are number of erroneous test vectors and distribution (spacing) of the erroneous vectors. The effect of total number of test vectors and position of the erroneous vectors are relatively minor compared to the other two. The minimization algorithm therefore was most effective for cases where there are only a few erroneous test vectors, with large number of test vectors in the set
A debugging engine for parallel and distributed programs
Dissertação apresentada para a obtenção
do Grau de Doutor em Informática pela
Universidade Nova de Lisboa, Faculdade
de Ciências e Tecnologia.In the last decade a considerable amount of research work has focused on distributed
debugging, one of the crucial fields in the parallel software development cycle. The
productivity of the software development process strongly depends on the adequate
definition of what debugging tools should be provided, and what debugging methodologies
and functionalities should these tools support.
The work described in this dissertation was initiated in 1995, in the context of two
research projects, the SEPP (Software Engineering for Parallel Processing) and HPCTI
(High-Performance Computing Tools for Industry), both sponsored by the European
Union in the Copernicus programme, which aimed at the design and implementation
of an integrated parallel software development environment. In the context of these
projects, two independent toolsets have been developed, the GRADE and EDPEPPS
parallel software development environments.
Our contribution to these projects was in the debugging support. We have designed
a debugging engine and developed a prototype, which was integrated the both
toolsets (it was the only tool developed in the context of the SEPP and HPCTI projects
which achieved such a result). Even after the closing of those research projects, further
research work on distributed debugger has been carried on, which conducted to the
re-design and re-implementation of the debugging engine.
This dissertation describes the debugging engine according to its most up-to-date
design and implementation stages. It also reposts some of the experimentalworkmade
with both the initial and the current implementations, and how it contributed to validate
the design and implementations of the debugging engine
Reversible Computation: Extending Horizons of Computing
This open access State-of-the-Art Survey presents the main recent scientific outcomes in the area of reversible computation, focusing on those that have emerged during COST Action IC1405 "Reversible Computation - Extending Horizons of Computing", a European research network that operated from May 2015 to April 2019. Reversible computation is a new paradigm that extends the traditional forwards-only mode of computation with the ability to execute in reverse, so that computation can run backwards as easily and naturally as forwards. It aims to deliver novel computing devices and software, and to enhance existing systems by equipping them with reversibility. There are many potential applications of reversible computation, including languages and software tools for reliable and recovery-oriented distributed systems and revolutionary reversible logic gates and circuits, but they can only be realized and have lasting effect if conceptual and firm theoretical foundations are established first
Reversible Computation: Extending Horizons of Computing
This open access State-of-the-Art Survey presents the main recent scientific outcomes in the area of reversible computation, focusing on those that have emerged during COST Action IC1405 "Reversible Computation - Extending Horizons of Computing", a European research network that operated from May 2015 to April 2019. Reversible computation is a new paradigm that extends the traditional forwards-only mode of computation with the ability to execute in reverse, so that computation can run backwards as easily and naturally as forwards. It aims to deliver novel computing devices and software, and to enhance existing systems by equipping them with reversibility. There are many potential applications of reversible computation, including languages and software tools for reliable and recovery-oriented distributed systems and revolutionary reversible logic gates and circuits, but they can only be realized and have lasting effect if conceptual and firm theoretical foundations are established first
Automatically Repairing Programs Using Both Tests and Bug Reports
The success of automated program repair (APR) depends significantly on its
ability to localize the defects it is repairing. For fault localization (FL),
APR tools typically use either spectrum-based (SBFL) techniques that use test
executions or information-retrieval-based (IRFL) techniques that use bug
reports. These two approaches often complement each other, patching different
defects. No existing repair tool uses both SBFL and IRFL. We develop RAFL
(Rank-Aggregation-Based Fault Localization), a novel FL approach that combines
multiple FL techniques. We also develop Blues, a new IRFL technique that uses
bug reports, and an unsupervised approach to localize defects. On a dataset of
818 real-world defects, SBIR (combined SBFL and Blues) consistently localizes
more bugs and ranks buggy statements higher than the two underlying techniques.
For example, SBIR correctly identifies a buggy statement as the most suspicious
for 18.1% of the defects, while SBFL does so for 10.9% and Blues for 3.1%. We
extend SimFix, a state-of-the-art APR tool, to use SBIR, SBFL, and Blues.
SimFix using SBIR patches 112 out of the 818 defects; 110 when using SBFL, and
55 when using Blues. The 112 patched defects include 55 defects patched
exclusively using SBFL, 7 patched exclusively using IRFL, 47 patched using both
SBFL and IRFL and 3 new defects. SimFix using Blues significantly outperforms
iFixR, the state-of-the-art IRFL-based APR tool. Overall, SimFix using our FL
techniques patches ten defects no prior tools could patch. By evaluating on a
benchmark of 818 defects, 442 previously unused in APR evaluations, we find
that prior evaluations on the overused Defects4J benchmark have led to overly
generous findings. Our paper is the first to (1) use combined FL for APR, (2)
apply a more rigorous methodology for measuring patch correctness, and (3)
evaluate on the new, substantially larger version of Defects4J.Comment: working pape
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Sandboxed, Online Debugging of Production Bugs for SOA Systems
Short time-to-bug localization is extremely important for any 24x7 service-oriented application. To this end, we introduce a new debugging paradigm called live debugging. There are two goals that any live debugging infrastructure must meet: Firstly, it must offer real-time insight for bug diagnosis and localization, which is paramount when errors happen in user-facing applications. Secondly, live debugging should not impact user-facing performance for normal events. In large distributed applications, bugs which impact only a small percentage of users are common. In such scenarios, debugging a small part of the application should not impact the entire system.
With the above-stated goals in mind, this thesis presents a framework called Parikshan, which leverages user-space containers (OpenVZ) to launch application instances for the express purpose of live debugging. Parikshan is driven by a live-cloning process, which generates a replica (called debug container) of production services, cloned from a production container which continues to provide the real output to the user. The debug container provides a sandbox environment, for safe execution of monitoring/debugging done by the users without any perturbation to the execution environment. As a part of this framework, we have designed customized-network proxies, which replicate inputs from clients to both the production and test-container, as well safely discard all outputs. Together the network duplicator, and the debug container ensure both compute and network isolation of the debugging environment. We believe that this piece of work provides the first of its kind practical real-time debugging of large multi-tier and cloud applications, without requiring any application downtime, and minimal performance impact
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