scholarly journals Data Flow Testing in Concurrent Programs with Message Passing and Shared Memory Paradigms

2013 ◽  
Vol 18 ◽  
pp. 149-158 ◽  
Author(s):  
Paulo S.L. Souza ◽  
Simone S. Souza ◽  
Murilo G. Rocha ◽  
Rafael R. Prado ◽  
Raphael N. Batista
Keyword(s):  
Shared Memory ◽  
Message Passing ◽  
Data Flow ◽  
Concurrent Programs ◽  
Data Flow Testing

Analyzing Concurrent Programs Title for Potential Programming Errors

2011 ◽  
pp. 380-415
Author(s):  
Qichang Chen ◽  
Liqiang Wang ◽  
Ping Guo ◽  
He Huang
Keyword(s):  
Shared Memory ◽  
Message Passing ◽  
Programming Models ◽  
Concurrent Programs ◽  
Sequential Programs ◽  
Multithreaded Programming ◽  
Testing And Debugging ◽  
Race Condition ◽  
Art Research ◽  
Concurrency Errors

Today, multi-core/multi-processor hardware has become ubiquitous, leading to a fundamental turning point on software development. However, developing concurrent programs is difficult. Concurrency introduces the possibility of errors that do not exist in sequential programs. This chapter introduces the major concurrent programming models including multithreaded programming on shared memory and message passing programming on distributed memory. Then, the state-of-the-art research achievements on detecting concurrency errors such as deadlock, race condition, and atomicity violation are reviewed. Finally, the chapter surveys the widely used tools for testing and debugging concurrent programs.

scholarly journals Trace Generation and Deterministic Execution for Concurrent Programs

2016 ◽  
Author(s):  
Paulo Souza ◽  
Raphael Batista ◽  
Simone Souza ◽  
Rafael Prado ◽  
George Dourado ◽  
...  
Keyword(s):  
Shared Memory ◽  
Message Passing ◽  
Source Code ◽  
Concurrent Programs ◽  
Code Coverage ◽  
Coverage Testing ◽  
Point To Point ◽  
New Algorithms

This paper proposes new algorithms for generation of trace files and deterministic execution of concurrent programs under test. The proposed algorithms are essential to automate the coverage testing of concurrent programs and allow to execute new synchronizations automatically, increasing the source code coverage with focus on non-determinism, and edges of communication and synchronization. Our algorithms consider programs with multiple paradigms of communication and synchronization (collective, blocking and non-blocking point-to-point message passing, and shared memory). We validate our algorithms by means of experiments based on nine representative benchmarks, which exercise non-trivial aspects of synchronization found in real applications. Our algorithms have a robust behaviour and meet their objectives. We also highlight the overhead generated with the algorithms.

Causal-Consistent Replay Reversible Semantics for Message Passing Concurrent Programs

2021 ◽  
Vol 178 (3) ◽  
pp. 229-266
Author(s):  
Ivan Lanese ◽  
Adrián Palacios ◽  
Germán Vidal
Keyword(s):  
Programming Language ◽  
Message Passing ◽  
Concurrent Programming ◽  
Concurrent Systems ◽  
Concurrent Programs ◽  
Unified Framework ◽  
Innovative Technique ◽  
Dual Notion

Causal-consistent reversible debugging is an innovative technique for debugging concurrent systems. It allows one to go back in the execution focusing on the actions that most likely caused a visible misbehavior. When such an action is selected, the debugger undoes it, including all and only its consequences. This operation is called a causal-consistent rollback. In this way, the user can avoid being distracted by the actions of other, unrelated processes. In this work, we introduce its dual notion: causal-consistent replay. We allow the user to record an execution of a running program and, in contrast to traditional replay debuggers, to reproduce a visible misbehavior inside the debugger including all and only its causes. Furthermore, we present a unified framework that combines both causal-consistent replay and causal-consistent rollback. Although most of the ideas that we present are rather general, we focus on a popular functional and concurrent programming language based on message passing: Erlang.

Parallel Nonnegative Matrix Factorization via Newton Iteration

2016 ◽  
Vol 26 (03) ◽  
pp. 1650014 ◽  
Author(s):  
Markus Flatz ◽  
Marián Vajteršic
Keyword(s):  
Shared Memory ◽  
Matrix Factorization ◽  
Message Passing ◽  
Nonnegative Matrix Factorization ◽  
Nonnegative Matrix ◽  
Newton Iteration ◽  
Parallel Execution ◽  
Kkt Conditions ◽  
Nonnegative Matrices ◽  
First Order

The goal of Nonnegative Matrix Factorization (NMF) is to represent a large nonnegative matrix in an approximate way as a product of two significantly smaller nonnegative matrices. This paper shows in detail how an NMF algorithm based on Newton iteration can be derived using the general Karush-Kuhn-Tucker (KKT) conditions for first-order optimality. This algorithm is suited for parallel execution on systems with shared memory and also with message passing. Both versions were implemented and tested, delivering satisfactory speedup results.

An Efficient Parallel Algorithm for Extreme Eigenvalues of Sparse Nonsymmetric Matrices

1992 ◽  
Vol 6 (1) ◽  
pp. 98-111 ◽  
Author(s):  
S. K. Kim ◽  
A. T. Chrortopoulos
Keyword(s):  
Shared Memory ◽  
Message Passing ◽  
Sparse Matrices ◽  
Data Locality ◽  
Main Memory ◽  
Global Memory ◽  
Global Communication ◽  
Step Method ◽  
Arnoldi Algorithm ◽  
Large Sparse Matrices

Main memory accesses for shared-memory systems or global communications (synchronizations) in message passing systems decrease the computation speed. In this paper, the standard Arnoldi algorithm for approximating a small number of eigenvalues, with largest (or smallest) real parts for nonsymmetric large sparse matrices, is restructured so that only one synchronization point is required; that is, one global communication in a message passing distributed-memory machine or one global memory sweep in a shared-memory machine per each iteration is required. We also introduce an s-step Arnoldi method for finding a few eigenvalues of nonsymmetric large sparse matrices. This method generates reduction matrices that are similar to those generated by the standard method. One iteration of the s-step Arnoldi algorithm corresponds to s iterations of the standard Arnoldi algorithm. The s-step method has improved data locality, minimized global communication, and superior parallel properties. These algorithms are implemented on a 64-node NCUBE/7 Hypercube and a CRAY-2, and performance results are presented.

scholarly journals Teaching tools for parallel processing

2005 ◽  
Vol 18 (2) ◽  
pp. 219-224
Author(s):  
Emina Milovanovic ◽  
Natalija Stojanovic
Keyword(s):  
Parallel Computing ◽  
Parallel Processing ◽  
Shared Memory ◽  
Message Passing ◽  
Distributed Memory ◽  
Cost Effective ◽  
Parallel Computers ◽  
Free Software ◽  
Teaching Tools ◽  
Network Of Workstations

Because many universities lack the funds to purchase expensive parallel computers, cost effective alternatives are needed to teach students about parallel processing. Free software is available to support the three major paradigms of parallel computing. Parallaxis is a sophisticated SIMD simulator which runs on a variety of platforms.jBACI shared memory simulator supports the MIMD model of computing with a common shared memory. PVM and MPI allow students to treat a network of workstations as a message passing MIMD multicomputer with distributed memory. Each of this software tools can be used in a variety of courses to give students experience with parallel algorithms.

scholarly journals Test Case Generation for Data Flow Testing using Cuckoo Search Algorithm

2019 ◽  
Vol 8 (2S11) ◽  
pp. 2953-2964
Keyword(s):  
Data Flow ◽  
Search Algorithm ◽  
Fitness Function ◽  
Cuckoo Search ◽  
Automatic Generation ◽  
Cuckoo Search Algorithm ◽  
Test Case ◽  
Stochastic Algorithm ◽  
Data Flow Testing ◽  
Work Done

Software testing consumes the major portion of the total efforts required for software development. This activity is very time consuming and labor intensive. It is very hard to do testing in optimal manner. In this paper a new approach is proposed, which uses the nature inspired stochastic algorithm called Cuckoo Search Algorithm (CSA) for the automatic generation of test data for data flow testing. This approach considers all def-use as test adequacy criteria. For assistance to CSA in the state space a new fitness function is also proposed by using the concept of dominator tree and branch distance in a CFG. To validate the proposed approach experiments are carried out on 10 benchmarked programs and findings are contrasted with earlier work done in this domain. Further in order to prove that proposed approach performs better than the above mentioned approaches a statistical difference test (T-test) is also performed.

Efficient composite data flow analysis applied to concurrent programs

1998 ◽  
Vol 33 (7) ◽  
pp. 51-58
Author(s):  
Gleb Naumovich ◽  
Lori A. Clarke ◽  
Leon J. Osterweil
Keyword(s):  
Data Flow ◽  
Flow Analysis ◽  
Concurrent Programs ◽  
Data Flow Analysis ◽  
Composite Data
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