Faster Mutation Analysis via Equivalence Modulo States

Mutation analysis has many applications, such as asserting the quality of test suites and localizing faults. One important bottleneck of mutation analysis is scalability. The latest work explores the possibility of reducing the redundant execution via split-stream execution. However, split-stream execution is only able to remove redundant execution before the first mutated statement. In this paper we try to also reduce some of the redundant execution after the execution of the first mutated statement. We observe that, although many mutated statements are not equivalent, the execution result of those mutated statements may still be equivalent to the result of the original statement. In other words, the statements are equivalent modulo the current state. In this paper we propose a fast mutation analysis approach, AccMut. AccMut automatically detects the equivalence modulo states among a statement and its mutations, then groups the statements into equivalence classes modulo states, and uses only one process to represent each class. In this way, we can significantly reduce the number of split processes. Our experiments show that our approach can further accelerate mutation analysis on top of split-stream execution with a speedup of 2.56x on average.Comment: Submitted to conferenc

О задаче минимизации последовательных программ

First-order program schemata is one of the simplest models of sequential imperative programs intended for solving verification and optimization problems. We consider the decidable relation of logical-thermal equivalence of these schemata and the problem of their size minimization while preserving logical-thermal equivalence. We prove that this problem is decidable. Further we show that the first-order program schemata supplied with logical-thermal equivalence and finite state deterministic transducers operating over substitutions are mutually translated into each other. This relationship implies that the equivalence checking problem and the minimization problem for these transducers are also decidable. In addition, on the basis of the discovered relationship, we have found a subclass of firstorder program schemata such that their minimization can be performed in polynomial time by means of known techniques for minimization of finite state transducers operating over semigroups. Finally, we demonstrate that in general case the minimization problem for finite state transducers over semigroups may have several non-isomorphic solutions.Стандартные схемы программ — это одна из наиболее простых моделей последовательных императивных программ, предназначенная для решения задач оптимизации и верификации программ. Мы рассматриваем разрешимое отношение логико-термальной эквивалентности стандартных схем программ и задачу минимизации их размера при условии сохранения отношения логико-термальной эквивалентности. Нами доказано, что эта задача является алгоритмически разрешимой. Далее показано, что стандартные схемы программ с отношением логико-термальной эквивалентности и конечные детерминированные автоматы-преобразователи, работающие над полугруппами подстановок, взаимно транслируются друг в друга. Отсюда следует, что также разрешимы задачи проверки эквивалентности и минимизации для преобразователей указанного вида. Кроме того, на основе обнаруженной взаимосвязи выделен подкласс стандартных схем программ, минимизация которых осуществима за полиномиальное время при помощи ранее известных методов минимизации автоматов-преобразователей, работающих над полугруппами. В заключении приведен пример, свидетельствующий о том, что в общем случае задача минимизации автоматов- преобразователей над полугруппой подстановок может иметь несколько неизоморфных решений.

CHREST+: A simulation of how humans learn to solve problems using diagrams.

This paper describes the underlying principles of a computer model, CHREST+, which learns to solve problems using diagrammatic representations. Although earlier work has determined that experts store domain-specific information within schemata, no substantive model has been proposed for learning such representations. We describe the different strategies used by subjects in constructing a diagrammatic representation of an electric circuit known as an AVOW diagram, and explain how these strategies fit a theory for the learnt representations. Then we describe CHREST+, an extended version of an established model of human perceptual memory. The extension enables the model to relate information learnt about circuits with that about their associated AVOW diagrams, and use this information as a schema to improve its efficiency at problem solving

Elements of latent learning in a maze environment

A general purpose learning program is described which demonstrates a latent learning ability by operating at two separate goal pursuit levels. At one level are the constant, implicit goals associated with the system's memory management mechanisms. At the higher level are the dynamic, explicit behavioral goals which the implicit goals enable by manipulating memory representations to conform to the external surroundings. The program is shown to negotiate a simulated maze environment by the step-wise refinement of its latently learned experiences

An Abstract Machine for Unification Grammars

This work describes the design and implementation of an abstract machine, Amalia, for the linguistic formalism ALE, which is based on typed feature structures. This formalism is one of the most widely accepted in computational linguistics and has been used for designing grammars in various linguistic theories, most notably HPSG. Amalia is composed of data structures and a set of instructions, augmented by a compiler from the grammatical formalism to the abstract instructions, and a (portable) interpreter of the abstract instructions. The effect of each instruction is defined using a low-level language that can be executed on ordinary hardware. The advantages of the abstract machine approach are twofold. From a theoretical point of view, the abstract machine gives a well-defined operational semantics to the grammatical formalism. This ensures that grammars specified using our system are endowed with well defined meaning. It enables, for example, to formally verify the correctness of a compiler for HPSG, given an independent definition. From a practical point of view, Amalia is the first system that employs a direct compilation scheme for unification grammars that are based on typed feature structures. The use of amalia results in a much improved performance over existing systems. In order to test the machine on a realistic application, we have developed a small-scale, HPSG-based grammar for a fragment of the Hebrew language, using Amalia as the development platform. This is the first application of HPSG to a Semitic language.Comment: Doctoral Thesis, 96 pages, many postscript figures, uses pstricks, pst-node, psfig, fullname and a macros fil