A comparison of system monitoring methods, passive network monitoring and kernel instrumentation

This paper presents the comparison of two methods of system monitoring, passive network monitoring and kernel instrumentation. The comparison is made on the basis of passive network monitoring being used as a replacement for kernel instrumentation in some situations. Despite the fact that the passive network monitoring technique is shown to perform poorly as a direct replacement for kernel instrumentation, this paper indicates the areas where passive network monitoring could be used to the greatest advantage and presents methods by which the discrepancies between results of the two techniques could be minimised

THE EFFECTIVENESS OF ACTIVATING STUDENTS’ PERIPHERAL LEARNING STRATEGY ON TEACHING DESCRIPTIVE TEXT WRITING FOR THE TENTH GRADERS IN SMANEGERI 1 NGANJUK

Abstrak                 Penelitian ini bertujuan untuk mengetahui efektifitas dari pengaktifan peripheral learning strategy pada kemampuan menulis teks deskriptif siswa. Dua kelas telah dipilih dan secara acak dibagi menjadi dua kelompok, yaitu kelompok kontrol dan eksperimental. Mereka berada pada tingkat yang sama yaitu pada kelas sepuluh di SMA Negeri 1 Nganjuk. Sebelum memberikan perlakuan khusus, tes menulis telah diberikan pada kedua kelompok sebagai pre-tes. Lalu, peripheral learning dari kelompok eksperimental diaktifkan sebagai perlakuan khusus, sedangkan kelompok kontrol diajar dengan menggunakan metode tradisional. Setelah pemberian perlakuan khusus, post-tes diberikan pada kedua kelompok. Sebuah analisis t-test pada SPSS 16.00 digunakan untuk menganalisa hasil pre-tes dan post-tes dari kelompok kontrol dan eksperimental. Hasil dari penelitian ini menunjukkan bahwa pengaktifan dari peripheral learning strategy memiliki efek yang signifikan untuk meningkatkan kemampuan menulis teks deskriptif siswa, (P<.05).   Kata Kunci: Menulis, Teks Deskriptif, Peripheral Learning Strategy   Abstract                 This study is an effort to know the effectiveness of activating students’ peripheral learning strategy on students’ descriptive text ability. Two classes were selected and randomly divided into two groups, namely experimental and control groups. They were on the same level that is on the tenth grade of SMA Negeri 1 Nganjuk. Before giving the treatment, a writing test was administered to both groups as pre-test. Then, the peripheral learning of experimental group was activated as a treatment, while the control group was taught by traditional way. After giving treatment, a post-test was administered to both groups. A t-test on SPSS 16.00 was used to analyze the result of pre-test and post-test from experimental and control groups. The results showed that the activation of peripheral learning strategy had a significant effect to improve the students’ descriptive writing ability, (P<.05).   Keywords: Writing, Descriptive Text, Peripheral Learning Strateg

Sampling-based Program Execution Monitoring

For its high overall cost during product development, program debugging is an important aspect of system development. Debugging is a hard and complex activity, especially in time-sensitive systems which have limited resources and demanding timing constraints. System tracing is a frequently used technique for debugging embedded systems. A specific use of system tracing is to monitor and debug control-flow problems in programs. However, it is difficult to implement because of the potentially high overhead it might introduce to the system and the changes which can occur to the system behaviour due to tracing. To solve the above problems, in this work, we present a sampling-based approach to program execution monitoring which specifically helps developers trace the program execution in time-sensitive systems such as real-time applications. We build the system model and propose three theorems which determine the sampling period or the optimal in different scenarios. We also design seven heuristics and an instrumentation framework to extend the sampling period which can reduce the monitoring overhead and achieve an optimal tradeoff between accuracy and overhead introduced by instrumentation. Using this monitoring framework, we can use the information extracted through sampling to reconstruct the system state and execution paths to locate the deviation. Based on the statistically significant data, we also model the trend of the sampling period with the instrumentation steps. Based on the modelling results, we devise a scheme for predicting the number of markers we need to reach a certain sampling period. Last, we build a tool chain to instrument and monitoring the software system and further prove the soundness of our approach

Policy Driven Software Monitoring

Software monitoring and logging is one of the most important tools a software engineer has when faced with the challenge of auditing or analysing a software system. However, the difficulty in effectively monitoring a system, managing its logs and cross referencing them with source code makes software re-engineering a rigorous and complex task. This thesis aims to address this issue by providing a framework that enables pattern matching between a software log and an event pattern expression that is based on a monitoring policy. The framework consists of parsers and annotators that facilitates transformation of a monitoring policy into a Petri Net as well as source code annotation for gathering data through logged events. It further expands upon this work by proposing an adaptive logging framework that will greatly improve the quality of log management by autonomically adjusting the amount of information logged based on the application’s operational environment. Finally, a prototype system of the policy driven monitoring framework is implemented and tested with applications of different scales as a proof of concept for the proposed framework