The Total Correctness of Parallel Programs

1981 ◽  
Vol 10 (2) ◽  
pp. 227-246 ◽  
Author(s):  
Lawrence Flon ◽  
Norihisa Suzuki
Keyword(s):  
Parallel Programs ◽  
Total Correctness

scholarly journals A unified approach of program verification

2017 ◽  
Vol 9 (1) ◽  
pp. 65-82
Author(s):  
Tibor Gregorics ◽  
Zsolt Borsi
Keyword(s):  
Program Verification ◽  
Parallel Programs ◽  
Relational Model ◽  
Unified Approach ◽  
Partial Functions ◽  
Sequential Programs ◽  
Verification Method ◽  
Total Correctness ◽  
The Subject

Abstract The subject of this paper is a program verification method that takes into account abortion caused by partial functions in program statements. In particular, boolean expressions of various statements will be investigated that are not well-defined. For example, a loop aborts if its execution begins in a state for which the loop condition is undefined. This work considers the program constructs of nondeterministic sequential programs and also deals with the synchronization statement of parallel programs introduced by Owicki and Gries [7]. The syntax of program constructs will be reviewed and their semantics will be formally defined in such a way that they suit the relational model of programming developed at Eőtvős Loránd University [3, 4]. This relational model defines the program as a set of its possible executions and also provides definition for other important programming notions like problem and solution. The proof rules of total correctness [2, 5, 8, 9, 7] will be extended by treating abortion caused by partial functions. The use of these rules will be demonstrated by means of a verification case study.

scholarly journals Disentanglement in nested-parallel programs

2020 ◽  
Vol 4 (POPL) ◽  
pp. 1-32 ◽  
Author(s):  
Sam Westrick ◽  
Rohan Yadav ◽  
Matthew Fluet ◽  
Umut A. Acar
Keyword(s):  
Parallel Programs

Test-driven repair of data races in structured parallel programs

2014 ◽  
Vol 49 (6) ◽  
pp. 15-25 ◽  
Author(s):  
Rishi Surendran ◽  
Raghavan Raman ◽  
Swarat Chaudhuri ◽  
John Mellor-Crummey ◽  
Vivek Sarkar
Keyword(s):  
Parallel Programs ◽  
Data Races

scholarly journals Correct program parallelisations

2021 ◽  
Author(s):  
S. Blom ◽  
S. Darabi ◽  
M. Huisman ◽  
M. Safari
Keyword(s):  
Composition Operators ◽  
Parallel Programs ◽  
Parallel Program ◽  
Tool Support ◽  
Intermediate Representation ◽  
Data Race ◽  
Sequential Program ◽  
Functional Correctness ◽  
Correct Program ◽  
Basic Blocks

AbstractA commonly used approach to develop deterministic parallel programs is to augment a sequential program with compiler directives that indicate which program blocks may potentially be executed in parallel. This paper develops a verification technique to reason about such compiler directives, in particular to show that they do not change the behaviour of the program. Moreover, the verification technique is tool-supported and can be combined with proving functional correctness of the program. To develop our verification technique, we propose a simple intermediate representation (syntax and semantics) that captures the main forms of deterministic parallel programs. This language distinguishes three kinds of basic blocks: parallel, vectorised and sequential blocks, which can be composed using three different composition operators: sequential, parallel and fusion composition. We show how a widely used subset of OpenMP can be encoded into this intermediate representation. Our verification technique builds on the notion of iteration contract to specify the behaviour of basic blocks; we show that if iteration contracts are manually specified for single blocks, then that is sufficient to automatically reason about data race freedom of the composed program. Moreover, we also show that it is sufficient to establish functional correctness on a linearised version of the original program to conclude functional correctness of the parallel program. Finally, we exemplify our approach on an example OpenMP program, and we discuss how tool support is provided.

Provably good scheduling for parallel programs that use data structures through implicit batching

2014 ◽  
Vol 49 (8) ◽  
pp. 389-390
Author(s):  
Kunal Agrawal ◽  
Jeremy T. Fineman ◽  
Brendan Sheridan ◽  
Jim Sukha ◽  
Robert Utterback
Keyword(s):  
Data Structures ◽  
Parallel Programs
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