A graph based process model measurement framework using scheduling theory

Software development processes, as a means of ensuring software quality and productivity, have been widely accepted within the software development community; software process modeling, on the other hand, continues to be a subject of interest in the research community. Even with organizations that have achieved higher SEI maturity levels, processes are by and large described in documents and reinforced as guidelines or laws governing software development activities. The lack of industry-wide adaptation of software process modeling as part of development activities can be attributed to two major reasons: lack of forecast power in the (software) process modeling and lack of integration mechanism for the described process to seamlessly interact with daily development activities. This dissertation describes a research through which a framework has been established where processes can be manipulated, measured, and dynamically modified by interacting with project management techniques and activities in an integrated process modeling environment, thus closing the gap between process modeling and software development. In this research, processes are described using directed graphs, similar to the techniques with CPM. This way, the graphs can be manipulated visually while the properties of the graphs-can be used to check their validity. The partial ordering and the precedence relationship of the tasks in the graphs are similar to the one studied in other researches [Delcambre94] [Mills96]. Measurements of the effectiveness of the processes are added in this research. These measurements provide bases for the judgment when manipulating the graphs to produce or modify a process. Software development can be considered as activities related to three sets: a set of tasks (τ), a set of resources (ρ), and a set of constraints (y). The process, P, is then a function of all the sets interacting with each other: P = {τ, ρ, y). The interactions of these sets can be described in terms of different machine models using scheduling theory. While trying to produce an optimal solution satisfying a set of prescribed conditions using the analytical method would lead to a practically non-feasible formulation, many heuristic algorithms in scheduling theory combined with manual manipulation of the tasks can help to produce a reasonable good process, the effectiveness of which is reflected through a set of measurement criteria, in particular, the make-span, the float, and the bottlenecks. Through an integrated process modeling environment, these measurements can be obtained in real time, thus providing a feedback loop during the process execution. This feedback loop is essential for risk management and control

Performance Prediction of Cloud-Based Big Data Applications

Big data analytics have become widespread as a means to extract knowledge from large datasets. Yet, the heterogeneity and irregular- ity usually associated with big data applications often overwhelm the existing software and hardware infrastructures. In such con- text, the exibility and elasticity provided by the cloud computing paradigm o er a natural approach to cost-e ectively adapting the allocated resources to the application’s current needs. However, these same characteristics impose extra challenges to predicting the performance of cloud-based big data applications, a key step to proper management and planning. This paper explores three modeling approaches for performance prediction of cloud-based big data applications. We evaluate two queuing-based analytical models and a novel fast ad hoc simulator in various scenarios based on di erent applications and infrastructure setups. The three ap- proaches are compared in terms of prediction accuracy, nding that our best approaches can predict average application execution times with 26% relative error in the very worst case and about 7% on average

Scheduling of a Cyber-Physical System Simulation

The work carried out in this Ph.D. thesis is part of a broader effort to automate industrial simulation systems. In the aeronautics industry, and more especially within Airbus, the historical application of simulation is pilot training. There are also more recent uses in the design of systems, as well as in the integration of these systems. These latter applications require a very high degree of representativeness, where historically the most important factor has been the pilot’s feeling. Systems are now divided into several subsystems that are designed, implemented and validated independently, in order to maintain their control despite the increase in their complexity, and the reduction in time-to-market. Airbus already has expertise in the simulation of these subsystems, as well as their integration into a simulation. This expertise is empirical; simulation specialists use the previous integrations schedulings and adapt it to a new integration. This is a process that can sometimes be time-consuming and can introduce errors. The current trends in the industry are towards flexible production methods, integration of logistics tools for tracking, use of simulation tools in production, as well as resources optimization. Products are increasingly iterations of older, improved products, and tests and simulations are increasingly integrated into their life cycles. Working empirically in an industry that requires flexibility is a constraint, and nowadays it is essential to facilitate the modification of simulations. The problem is, therefore, to set up methods and tools allowing a priori to generate representative simulation schedules. In order to solve this problem, we have developed a method to describe the elements of a simulation, as well as how this simulation can be executed, and functions to generate schedules. Subsequently, we implemented a tool to automate the scheduling search, based on heuristics. Finally, we tested and verified our method and tools in academic and industrial case studies

Formal methods and tools for the development of distributed and real time systems : Esprit Project 3096 (SPEC)

The Basic Research Action No. 3096, Formal Methods snd Tools for the Development of Distributed and Real Time Systems, is funded in the Area of Computer Science, under the ESPRIT Programme of the European Community. The coordinating institution is the Department of Computing Science, Eindhoven University of Technology, and the participating Institutions are the Institute of Computer Science of Crete. the Swedish Institute of Computer Science, the Programmimg Research Group of the University of Oxford, and the Computer Science Departments of the University of Manchester, Imperial College. Weizmann Institute of Science, Eindhoven University of Technology, IMAG Grenoble. Catholic University of Nijmegen, and the University of Liege. This document contains the synopsis. and part of the sections on objectives and area of advance, on baseline and rationale, on research goals, and on organisation of the action, as contained in the original proposal, submitted June, 198S. The section on the state of the art (18 pages) and the full list of references (21 pages) of the original proposal have been deleted because of limitation of available space

Real-time and Probabilistic Temporal Logics: An Overview

Over the last two decades, there has been an extensive study on logical formalisms for specifying and verifying real-time systems. Temporal logics have been an important research subject within this direction. Although numerous logics have been introduced for the formal specification of real-time and complex systems, an up to date comprehensive analysis of these logics does not exist in the literature. In this paper we analyse real-time and probabilistic temporal logics which have been widely used in this field. We extrapolate the notions of decidability, axiomatizability, expressiveness, model checking, etc. for each logic analysed. We also provide a comparison of features of the temporal logics discussed

Challenging the Computational Metaphor: Implications for How We Think

This paper explores the role of the traditional computational metaphor in our thinking as computer scientists, its influence on epistemological styles, and its implications for our understanding of cognition. It proposes to replace the conventional metaphor--a sequence of steps--with the notion of a community of interacting entities, and examines the ramifications of such a shift on these various ways in which we think

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.