با سلام خدمت کاربران عزیز، به اطلاع می رساند ترجمه مقالاتی که سال انتشار آن ها زیر 2008 می باشد رایگان بوده و میتوانید با وارد شدن در صفحه جزییات مقاله به رایگان ترجمه را دانلود نمایید.
Evaluation of EPL mutation operators with the MuEPL mutation system
ارزیابی اپراتورهای جهش EPL با سیستم جهش MuEPL-2019
The expert systems (ESs) have been developed to facilitate the users their tasks, to enhance the produc- tivity and reduce losses. In order to replicate the behaviour of a human expert, they generate output using their stored knowledge base. In a ES, the accumulation of knowledge from different sources is a very important factor. Nowadays, we are living in a world where two crucial processes need to be per- form quickly: decision-making and problem solving. The complexity of the decisions and problems lays on the different factors, situations and data that are involved. The Internet of Things (IoT) has been cre- ated to address these situations and helps the users to make correct decisions in real time according to the received data. In the concept of IoT, daily life objects are connected to each other so they can transfer data over the internet without a human to human interaction. The combination of IoT and ESs is a step further for the decision making problem, the received data from the IoT system will be sent to the ES, then the ES will process the information and send the results or decisions to the user. Given that correct decisions-making and problem solving are critical processed, these complex systems need to be tested. Mutation testing, which is a technique used in fault testing, has been examined in a range of studies where different programming languages have been used as well as in IoT expert systems evaluations. However, this technique has not been applied to an IoT programming language, which is noteworthy in the case of event processing languages (EPLs), that have been designed to address the main problems of IoT systems. Among the existing EPLs, the EPL of EsperTech is used the most often. In this paper, we ap- ply mutation testing using MuEPL to EPL of EsperTech programs in order to simulate the common errors of the developers and to avoid the wrong decisions before moving out to ES in the IoT network.
Keywords: Mutation testing | EPL | Mutation system |EPL Mutation operators | Complex event processing | Internet of things
An expert system for checking the correctness of memory systems using simulation and metamorphic testing
یک سیستم خبره برای بررسی صحت سیستم های حافظه با استفاده از شبیه سازی و تست های metamorphic-2019
During the last few years, computer performance has reached a turning point where computing power is no longer the only important concern. This way, the emphasis is shifting from an exclusive focus on the optimisation of the computing system to optimising other systems, like the memory system. Broadly speaking, testing memory systems entails two main challenges: the oracle problem and the reliable test set problem. The former consists in deciding if the outputs of a test suite are correct. The latter refers to providing an appropriate test suite for determining the correctness of the system under test. In this paper we propose an expert system for checking the correctness of memory systems. In order to face these challenges, our proposed system combines two orthogonal techniques –simulation and metamorphic testing –enabling the automatic generation of appropriate test cases and deciding if their outputs are correct. In contrast to conventional expert systems, our system includes a factual database containing the results of previous simulations, and a simulation platform for computing the behaviour of memory systems. The knowledge of the expert is represented in the form of metamorphic relations, which are properties of the analysed system involving multiple inputs and their outputs. Thus, the main contribution of this work is two-fold: a method to automatise the testing process of memory systems, and a novel expert system design focusing on increasing the overall performance of the testing process. To show the applicability of our system, we have performed a thorough evaluation using 500 memory configurations and 4 different memory management algorithms, which entailed the execution of more than one million of simulations. The evaluation used mutation testing, injecting faults in the memory management algorithms. The developed expert system was able to detect over 99% of the critical injected faults, hence obtaining very promising results, and outperforming other standard techniques like random testing.
Keywords: Memory systems | Metamorphic testing | Simulation | Mutation testing | Expert systems | Memory scheduling