108,767 research outputs found
Ada (trademark) projects at NASA. Runtime environment issues and recommendations
Ada practitioners should use this document to discuss and establish common short term requirements for Ada runtime environments. The major current Ada runtime environment issues are identified through the analysis of some of the Ada efforts at NASA and other research centers. The runtime environment characteristics of major compilers are compared while alternate runtime implementations are reviewed. Modifications and extensions to the Ada Language Reference Manual to address some of these runtime issues are proposed. Three classes of projects focusing on the most critical runtime features of Ada are recommended, including a range of immediately feasible full scale Ada development projects. Also, a list of runtime features and procurement issues is proposed for consideration by the vendors, contractors and the government
ACon: A learning-based approach to deal with uncertainty in contextual requirements at runtime
Context: Runtime uncertainty such as unpredictable operational environment and failure of sensors that gather environmental data is a well-known challenge for adaptive systems.
Objective: To execute requirements that depend on context correctly, the system needs up-to-date knowledge about the context relevant to such requirements. Techniques to cope with uncertainty in contextual requirements are currently underrepresented. In this paper we present ACon (Adaptation of Contextual requirements), a data-mining approach to deal with runtime uncertainty affecting contextual requirements.
Method: ACon uses feedback loops to maintain up-to-date knowledge about contextual requirements based on current context information in which contextual requirements are valid at runtime. Upon detecting that contextual requirements are affected by runtime uncertainty, ACon analyses and mines contextual data, to (re-)operationalize context and therefore update the information about contextual requirements.
Results: We evaluate ACon in an empirical study of an activity scheduling system used by a crew of 4 rowers in a wild and unpredictable environment using a complex monitoring infrastructure. Our study focused on evaluating the data mining part of ACon and analysed the sensor data collected onboard from 46 sensors and 90,748 measurements per sensor.
Conclusion: ACon is an important step in dealing with uncertainty affecting contextual requirements at runtime while considering end-user interaction. ACon supports systems in analysing the environment to adapt contextual requirements and complements existing requirements monitoring approaches by keeping the requirements monitoring specification up-to-date. Consequently, it avoids manual analysis that is usually costly in today’s complex system environments.Peer ReviewedPostprint (author's final draft
Dynamic Choreographies: Theory And Implementation
Programming distributed applications free from communication deadlocks and
race conditions is complex. Preserving these properties when applications are
updated at runtime is even harder. We present a choreographic approach for
programming updatable, distributed applications. We define a choreography
language, called Dynamic Interaction-Oriented Choreography (AIOC), that allows
the programmer to specify, from a global viewpoint, which parts of the
application can be updated. At runtime, these parts may be replaced by new AIOC
fragments from outside the application. AIOC programs are compiled, generating
code for each participant in a process-level language called Dynamic
Process-Oriented Choreographies (APOC). We prove that APOC distributed
applications generated from AIOC specifications are deadlock free and race free
and that these properties hold also after any runtime update. We instantiate
the theoretical model above into a programming framework called Adaptable
Interaction-Oriented Choreographies in Jolie (AIOCJ) that comprises an
integrated development environment, a compiler from an extension of AIOCs to
distributed Jolie programs, and a runtime environment to support their
execution.Comment: arXiv admin note: text overlap with arXiv:1407.097
The Need for a Versioned Data Analysis Software Environment
Scientific results in high-energy physics and in many other fields often rely
on complex software stacks. In order to support reproducibility and scrutiny of
the results, it is good practice to use open source software and to cite
software packages and versions. With ever-growing complexity of scientific
software on one side and with IT life-cycles of only a few years on the other
side, however, it turns out that despite source code availability the setup and
the validation of a minimal usable analysis environment can easily become
prohibitively expensive. We argue that there is a substantial gap between
merely having access to versioned source code and the ability to create a data
analysis runtime environment. In order to preserve all the different variants
of the data analysis runtime environment, we developed a snapshotting file
system optimized for software distribution. We report on our experience in
preserving the analysis environment for high-energy physics such as the
software landscape used to discover the Higgs boson at the Large Hadron
Collider
MERIC and RADAR generator: tools for energy evaluation and runtime tuning of HPC applications
This paper introduces two tools for manual energy evaluation and runtime tuning developed at IT4Innovations in the READEX project. The MERIC library can be used for manual instrumentation and analysis of any application from the energy and time consumption point of view. Besides tracing, MERIC can also change environment and hardware parameters during the application runtime, which leads to energy savings.
MERIC stores large amounts of data, which are difficult to read by a human. The RADAR generator analyses the MERIC output files to find the best settings of evaluated parameters for each instrumented region. It generates a Open image in new window report and a MERIC configuration file for application production runs
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