Towards Complexity Metrics for Ada Tasking
IEEE Transactions on Software Engineering
Concurrent programming: principles and practice
Concurrent programming: principles and practice
Complexity measures for concurrent programs based on information-theoretic metrics
Information Processing Letters
ACM Computing Surveys (CSUR)
Model checking
An alternative to event queues for synchronization in monitors
Communications of the ACM
Monitors: an operating system structuring concept
Communications of the ACM
Elements of Software Science (Operating and programming systems series)
Elements of Software Science (Operating and programming systems series)
Task decomposition testing and metrics for concurrent programs
ISSRE '96 Proceedings of the The Seventh International Symposium on Software Reliability Engineering
Verifying linear time temporal logic properties of concurrent Ada programs with quasar
Proceedings of the 2003 annual ACM SIGAda international conference on Ada: the engineering of correct and reliable software for real-time & distributed systems using ada and related technologies
A brief survey of program slicing
ACM SIGSOFT Software Engineering Notes
RaceTrack: efficient detection of data race conditions via adaptive tracking
Proceedings of the twentieth ACM symposium on Operating systems principles
Comparing Java, C# and Ada monitors queuing policies: a case study and its Ada refinement
ACM SIGAda Ada Letters
IEEE Transactions on Software Engineering
Quasar: a new tool for concurrent Ada programs analysis
Ada-Europe'03 Proceedings of the 8th Ada-Europe international conference on Reliable software technologies
Modelling remote concurrency with Ada: case study of symmetric non-deterministic rendezvous
Ada-Europe'07 Proceedings of the 12th international conference on Reliable software technologies
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Aiming at developing reliable concurrent software, the engineering practice uses appropriate metrics. Our tool Quasar analyses automatically the concurrent part of programs and produces data reporting its analysis process. We attempt to use the data as metrics for concurrent programming. The first aim of Quasar is the validation of concurrent code; in addition, the reported data may be relevant to mark the quality of code, to evaluate different concurrency semantics, to compare the execution indeterminism of different implementations of a concurrency pattern and to estimate the scalability of a solution. As a case study we analyse with Quasar several implementations of a distributed symmetric non-deterministic rendezvous algorithm. We consider two possible uses of the collected data for indeterminism estimation and for concurrent software quality.