{"id":162941,"date":"2012-09-01T00:00:00","date_gmt":"2012-09-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/finding-non-terminating-executions-in-distributed-asynchronous-programs\/"},"modified":"2018-10-16T21:13:45","modified_gmt":"2018-10-17T04:13:45","slug":"finding-non-terminating-executions-in-distributed-asynchronous-programs","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/finding-non-terminating-executions-in-distributed-asynchronous-programs\/","title":{"rendered":"Finding Non-Terminating Executions in Distributed Asynchronous Programs"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Programming distributed and reactive asynchronous systems is complex due to the lack of synchronization between concurrently executing tasks, and arbitrary delay of message-based communication. As even simple programming mistakes have the capability to introduce divergent behavior, a key liveness property is eventual quiescence: for any finite number of external stimuli (e.g., client-generated events), only a finite number of internal messages are ever created.<br \/>\nIn this work we propose a practical three-step reduction-based approach for detecting divergent executions in asynchronous programs. As a first step, we give a code-to-code translation reducing divergence of an asynchronous program P to completed state-reachability, i.e., reachability to a given state with no pending synchronous tasks, of a polynomially-sized asynchronous program P&#8217;. In the second step, we give a code-to-code translation under-approximating completed state-reachability of P&#8217; by state-reachability of a polynomially-sized recursive sequential program P\u201d(K), for the given analysis parameter K. Following Emmi et al. [8]&#8217;s delay-bounding approach, P\u201d(K) encodes a subset of P&#8217;, and thus of P, by limiting scheduling nondeterminism. As K is increased, more possibly divergent behaviors of P are considered, and in the limit as K approaches infinity, our reduction is complete for programs with finite data domains. As the final step we give the resulting state-reachability query to an of-the-shelf SMT-based sequential program verification tool.<br \/>\nWe demonstrate the feasibility of our approach by implementing a prototype analysis tool called Alive, which detects divergent executions in several hand-coded variations of textbook distributed algorithms. As far as we are aware, our easy-to-implement prototype is the first tool which automatically detects divergence for distributed and reactive synchronous programs.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Programming distributed and reactive asynchronous systems is complex due to the lack of synchronization between concurrently executing tasks, and arbitrary delay of message-based communication. As even simple programming mistakes have the capability to introduce divergent behavior, a key liveness property is eventual quiescence: for any finite number of external stimuli (e.g., client-generated events), only a [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13560],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-162941","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-programming-languages-software-engineering","msr-locale-en_us"],"msr_publishername":"","msr_edition":"Static Analysis Symposium 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