GPU Accelerated Parallel Algorithm of Sliding-Window Belief Propagation for LDPC Codes

Shan, Bowei; Fang, Yong

doi:10.1007/s10766-019-00632-3

Cited by 9 publications

(4 citation statements)

References 8 publications

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“…In optimization aspect, investigators primarily focus on implementation and convergence condition. Furthermore, LDPC along computational process assists in parallelization and merging memory access [36]. Beside this, convergence problem of BP and numerical polynomialhomotopy-continuation method revealed influence of structures.…”

Section: Belief Propagationmentioning

confidence: 99%

CIPC: A Change Impact Propagation Computing Based Technique for Microservice Regression Testing Prioritization

Chen

et al. 2021

Mobile Information Systems

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Regression testing is the optimal technique that can be used in each iteration of microservice systems. However, regression testing prioritization is the only main method that gives better results. These techniques directly involve the processes of artifacts, data acquisition, analysis, and maintenance. The microservice systems have input data, which are difficult to obtain and control, while such processes are of high costs with impractical design. This paper gives a detailed study on testing prioritization technique, which is referred to as CIPC. As there are dependencies between services from API gateway logs, a novel CIPC algorithm is proposed, which is based on belief propagation. There are some rules that are directly affected by service changes. Therefore, the higher execution order of test case prioritizes CIPC, which is based on impact changes. Multiobjective prioritization algorithm is based on heuristic searching, in which sequence test cases are done by coverage. By evaluating the effectiveness of CIPC, the empirical study presents five microservice systems and four different techniques. The results describe that CIPC has improved fault detection rate with acceptable time and cost. The technique is more practical than typical artifacts, which are based on increments of system scales.

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Section: Belief Propagationmentioning

confidence: 99%

CIPC: A Change Impact Propagation Computing Based Technique for Microservice Regression Testing Prioritization

Chen

et al. 2021

Mobile Information Systems

View full text Add to dashboard Cite

show abstract

“…In optimization aspect, investigators primarily focus on implementation and convergence condition. Furthermore, LDPC along computational process assists in parallelization and merging memory access [37]. Beside this, convergence problem of BP algorithm and numerical polynomial-homotopy-continuation method revealed influence of structures.…”

Section: Belief Propagationmentioning

confidence: 99%

A microservice regression testing selection approach based on belief propagation

Chen

Wu²,

Yang³

et al. 2023

J Cloud Comp

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Regression testing is required to assure the quality of each iteration of microservice systems. Test case selection is one of main techniques to optimize regression testing. Existing techniques mainly involve artifacts acquisition, processing and maintenance, thus hard to apply in microservice regression testing since it is difficult to obtain and process required artifacts from multiple development teams, which is normal in cases of microservice systems. This paper proposes a novel approach, namely MRTS-BP, which takes API gateway logs instead of artifacts as inputs. By mining service dependencies from API gateway logs, MRTS-BP analyzes service change impacts based on a propagation calculation, and selects test cases affected by changes based on impact degree values. To evaluate the effectiveness of MRTS-BP, empirical studies based on four real deployed systems are presented. Retest-all strategy and a regression testing selection approach based on control flow graphs called RTS-CFG are compared with MRTS-BP. The results show that, MRTS-BP can significantly reduce both the number of test cases and overall time cost while maintaining the fault detection capability of selected test suite, and that MRTS-BP can save more time cost than RTS-CFG with the similar safety and precision.

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“…Zhang et al proved that the Gaussian BP algorithm is exponentially convergent under the condition of walk summability, and gave a boundary of convergence rate [36]. Shan et al proposed sliding window belief propagation decoding algorithm of LDPC, and optimized the computational efficiency of propagation process with parallelization and merging memory access [37]. Knoll et al studied the convergence problem of BP algorithm and proposed the numerical polynomial-homotopy-continuation method, which revealed the influence of the structures and parameters of graph models on the convergence by solving the fixed points [38].…”

Section: Belief Propagationmentioning

confidence: 99%

A Microservice Regression Testing Selection Approach Based on Belief Propagation

Chen¹,

Wu²,

Yang³

et al. 2021

Preprint

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Regression testing is required in each iteration of microservice systems. Regression testing selection, which reduces testing costs by selecting a subset from the original test cases, is one of the main techniques to optimize regression testing. Existing techniques mainly rely on the information retrieved from artifacts such as code files and system models. For microservice systems with service autonomy, development method diversity and a large amount of services, such artifacts are too difficultly obtained and costly processed to apply those approaches. This paper presents a regression testing selection approach called MRTS-BP, which needs the API gateway layer logs instead of code files and system models as inputs. By parsing the API gateway layer logs, our approach establishes the service dependency matrix, which in further is transformed into a directed graph with the services as nodes. Then, to find out which test cases are affected by service changes, an algorithm based on belief propagation is presented to compute the quantitative results of service-change propagation from the directed graph. Finally, the relationships between original test cases and service-change propagation results are established to select test cases with three strategies. To evaluate the efficiency of MRTS-BP, the empirical study based on four microservice systems is presented. A typical technique RTS-CFG is compared with MRTS-CFG and four experiments are setup to investigate four research questions. The results show that MRTS-BP can not only reduce the number of test cases by half compared with the retest-all strategy while ensuring the safety, but also save at least 20% testing time costs more than that of RTS-CFG. MRTS-BP is more practical than the techniques relying on the artifacts when the latter cannot be implemented due to the artifacts are difficult to obtain and process.

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GPU Accelerated Parallel Algorithm of Sliding-Window Belief Propagation for LDPC Codes

Cited by 9 publications

References 8 publications

CIPC: A Change Impact Propagation Computing Based Technique for Microservice Regression Testing Prioritization

CIPC: A Change Impact Propagation Computing Based Technique for Microservice Regression Testing Prioritization

A microservice regression testing selection approach based on belief propagation

A Microservice Regression Testing Selection Approach Based on Belief Propagation

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