Programming guidelines for improving software resiliency against soft-errors without performance overhead

Arasteh, Bahman; Najafi, Jalal

doi:10.1007/s00607-018-0592-y

Cited by 14 publications

(4 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, the dynamic nature of the current method is expected to be a topic for future research, as the migration of initial and replica data in a dynamic setting presents unique challenges. Various heuristic/metaheuristics [35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50] and machine learning methods have been developed and utilized in computer engineering to address a variety of optimization problems [51][52][53][54][55][56][57]; therefore, assessing these methods' effectiveness in the problem of replica placement would be worthwhile.…”

Section: Discussionmentioning

confidence: 99%

Data Replication in Distributed Systems Using Olympiad Optimization Algorithm

Arasteh,

Bouyer,

Ghanbarzadeh

et al. 2023

FU Mech Eng

View full text Add to dashboard Cite

Achieving timely access to data objects is a major challenge in big distributed systems like the Internet of Things (IoT) platforms. Therefore, minimizing the data read and write operation time in distributed systems has elevated to a higher priority for system designers and mechanical engineers. Replication and the appropriate placement of the replicas on the most accessible data servers is a problem of NP-complete optimization. The key objectives of the current study are minimizing the data access time, reducing the quantity of replicas, and improving the data availability. The current paper employs the Olympiad Optimization Algorithm (OOA) as a novel population-based and discrete heuristic algorithm to solve the replica placement problem which is also applicable to other fields such as mechanical and computer engineering design problems. This discrete algorithm was inspired by the learning process of student groups who are preparing for the Olympiad exams. The proposed algorithm, which is divide-and-conquer-based with local and global search strategies, was used in solving the replica placement problem in a standard simulated distributed system. The 'European Union Database' (EUData) was employed to evaluate the proposed algorithm, which contains 28 nodes as servers and a network architecture in the format of a complete graph. It was revealed that the proposed technique reduces data access time by 39% with around six replicas, which is vastly superior to the earlier methods. Moreover, the standard deviation of the results of the algorithm's different executions is approximately 0.0062, which is lower than the other techniques' standard deviation within the same experiments.

show abstract

Section: Discussionmentioning

confidence: 99%

Data Replication in Distributed Systems Using Olympiad Optimization Algorithm

Arasteh,

Bouyer,

Ghanbarzadeh

et al. 2023

FU Mech Eng

View full text Add to dashboard Cite

show abstract

“…Now, it's time to further improve and optimize it. [1] Digital image [2][3] and signal processing [4][5] as well as knowledge graphs [6] [7] are all related to each other via software programming [8] [9].…”

Section: Introductionmentioning

confidence: 99%

Green Tourism Courses Customized with Digital Maps

Yang¹,

Jian²,

Zou³

2020

Proceedings of the International Academic Conference on Frontiers in Social Sciences and Management Innovation (IAFSM 2019)

View full text Add to dashboard Cite

This paper aims to introduce map knowledge management combined with personalization and standardization by taking the green tourism course as an example. The method is as follows: Firstly, the digital map knowledge management methods of the map of green tourism course are divided into several categories, namely: the first type is pure natural landscape, the second type is artificial landscape, and the third type is mixed landscape. Then, on the digital map customized by the green tourism course, these three types of landscapes are treated differently. Finally, the application of knowledge graphs and mind maps and other visualization techniques to enrich the personalized digital maps customized by the green tourism curriculum, and then find a series of events that can be standardized batch processing, and establish a smart query system. Its characteristics are: distinguish learning mode between large and small probability and very special exception. The result: not only the three types of landscapes are clearly visible in the digital map smart system customized by the green tourism course, but also the digital map knowledge management combined with personalized and standardized in the case of green tourism courses. The significance is that such a purpose, method and result not only help the teachers and students to better experience the innovative ideas of the green tourism curriculum, but more importantly, reserve enough opportunities for teachers and students to participate, for example, The selection and scoring of the three types of landscapes is a simple participation, and the effect will produce big data; for another example, not only can the standardized query be used, but also the personalized query can be conveniently established with examples in our paper.

show abstract

“…The propagation rate of injected faults in a code or data is expressed by the errorpropagation rate (Arasteh et al, 2014;Grun et al, 2009;Arasteh and Najafi, 2018). Given the role and impact of data in a program, the error-propagation rate of different data and codes of a program will be different.…”

Section: Introductionmentioning

confidence: 99%

An error-propagation aware method to reduce the software mutation cost using genetic algorithm

Hosseini

Arasteh

Isazadeh

et al. 2020

DTA

Self Cite

View full text Add to dashboard Cite

PurposeThe purpose of this study is to reduce the number of mutations and, consequently, reduce the cost of mutation test. The results of related studies indicate that about 40% of injected faults (mutants) in the source code are effect-less (equivalent). Equivalent mutants are one of the major costs of mutation testing and the identification of equivalent and effect-less mutants has been known as an undecidable problem.Design/methodology/approachIn a program with n branch instructions (if instruction) there are 2n execution paths (test paths) that the data and codes into each of these paths can be considered as a target of mutation. Given the role and impact of data in a program, some of data and codes propagates the injected mutants more likely to the output of the program. In this study, firstly the error-propagation rate of the program data is quantified using static analysis of the program control-flow graph. Then, the most error-propagating test paths are identified by the proposed heuristic algorithm (Genetic Algorithm [GA]). Data and codes with higher error-propagation rate are only considered as the strategic locations for the mutation testing.FindingsIn order to evaluate the proposed method, an extensive series of mutation testing experiments have been conducted on a set of traditional benchmark programs using MuJava tool set. The results depict that the proposed method reduces the number of mutants about 24%. Also, in the corresponding experiments, the mutation score is increased about 5.6%. The success rate of the GA in finding the most error-propagating paths of the input programs is 99%. On average, only 7.46% of generated mutants by the proposed method are equivalent. Indeed, 92.54% of generated mutants are non-equivalent.Originality/valueThe main contribution of this study is as follows: Proposing a set of equations to measure the error-propagation rate of each data, basic-block and execution path of a program. Proposing a genetic algorithm to identify a most error-propagating path of program as locations of mutations. Developing an efficient mutation-testing framework that mutates only the strategic locations of a program identified by the proposed genetic algorithms. Reducing the time and cost of mutation testing by reducing the equivalent mutants.

show abstract

Programming guidelines for improving software resiliency against soft-errors without performance overhead

Cited by 14 publications

References 36 publications

Data Replication in Distributed Systems Using Olympiad Optimization Algorithm

Data Replication in Distributed Systems Using Olympiad Optimization Algorithm

Green Tourism Courses Customized with Digital Maps

An error-propagation aware method to reduce the software mutation cost using genetic algorithm

Contact Info

Product

Resources

About