Memoized zipper-based attribute grammars

Attribute Grammars are a powerfull, well-known formalism to implement and reason about programs which, by design, are conveniently modular.In this work we focus on a state of the art Zipper-based embedding of Attribute Grammars and further improve its performance through controlling attribute (re)evaluation by using memoization techniques. We present the results of our optimization by comparing their impact in various implementations of different, well-studied Attribute Grammars.- (undefined

Semantic Fuzzing with Zest

Programs expecting structured inputs often consist of both a syntactic analysis stage, which parses raw input, and a semantic analysis stage, which conducts checks on the parsed input and executes the core logic of the program. Generator-based testing tools in the lineage of QuickCheck are a promising way to generate random syntactically valid test inputs for these programs. We present Zest, a technique which automatically guides QuickCheck-like randominput generators to better explore the semantic analysis stage of test programs. Zest converts random-input generators into deterministic parametric generators. We present the key insight that mutations in the untyped parameter domain map to structural mutations in the input domain. Zest leverages program feedback in the form of code coverage and input validity to perform feedback-directed parameter search. We evaluate Zest against AFL and QuickCheck on five Java programs: Maven, Ant, BCEL, Closure, and Rhino. Zest covers 1.03x-2.81x as many branches within the benchmarks semantic analysis stages as baseline techniques. Further, we find 10 new bugs in the semantic analysis stages of these benchmarks. Zest is the most effective technique in finding these bugs reliably and quickly, requiring at most 10 minutes on average to find each bug.Comment: To appear in Proceedings of 28th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA'19

A PC-based data acquisition system for sub-atomic physics measurements

Modern particle physics measurements are heavily dependent upon automated data acquisition systems (DAQ) to collect and process experiment-generated information. One research group from the University of Saskatchewan utilizes a DAQ known as the Lucid data acquisition and analysis system. This thesis examines the project undertaken to upgrade the hardware and software components of Lucid. To establish the effectiveness of the system upgrades, several performance metrics were obtained including the system's dead time and input/output bandwidth.Hardware upgrades to Lucid consisted of replacing its aging digitization equipment with modern, faster-converting Versa-Module Eurobus (VME) technology and replacing the instrumentation processing platform with common, PC hardware. The new processor platform is coupled to the instrumentation modules via a fiber-optic bridging-device, the sis1100/3100 from Struck Innovative Systems.The software systems of Lucid were also modified to follow suit with the new hardware. Originally constructed to utilize a proprietary real-time operating system, the data acquisition application was ported to run under the freely available Real-Time Executive for Multiprocessor Systems (RTEMS). The device driver software provided with sis1100/3100 interface also had to be ported for use under the RTEMS-based system. Performance measurements of the upgraded DAQ indicate that the dead time has been reduced from being on the order of milliseconds to being on the order of several tens of microseconds. This increased capability means that Lucid's users may acquire significantly more data in a shorter period of time, thereby decreasing both the statistical uncertainties and data collection duration associated with a given experiment