Aspect-oriented implementation of software health indicators

Thai, James; Pekilis, B.R.; Lau, Alexander; Seviora, R.E.

doi:10.1109/apsec.2001.991464

Cited by 9 publications

(4 citation statements)

References 9 publications

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“…Clearly, an important limitation of this study involves the small sample size (18), relatively homogeneous population (University of Hawaii seniors in Computer Science), short duration (four weeks), and small project size (around 3,000 LOC). This severely limits the external validity of this study; we would not expect a replication of this study in a different site and/or with different size teams or projects to generate the same results.…”

Section: Limitationsmentioning

confidence: 99%

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We need more coverage, stat! classroom experience with the software ICU

Johnson

Zhang

2009

2009 3rd International Symposium on Empirical Software Engineering and Measurement

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For empirical software engineering to reach its fullest potential, we must develop effective, experiential approaches to learning about it in a classroom setting. In this paper, we report on a case study involving a new approach to classroom-based empirical software engineering called the "Software ICU". In this approach, students learn about nine empirical project "vital signs" and use the Hackystat Framework to put their projects into a virtual "intensive care unit" where these vital signs can be assessed and monitored. We used both questionnaire and log data to gain insight into the strengths and weaknesses of this approach. Our evaluation provides both quantitative and qualitative evidence concerning the overhead of the system; the relative utility of different vital signs; the frequency of use; and the perceived appropriateness outside of the classroom setting. In addition to benefits, we found evidence of measurement dysfunction induced directly by the presence of the Software ICU. We compare these results to case studies we performed in 2003 and 2006 using the Hackystat Framework but not the Software ICU. We use these findings to orient future research on empirical software engineering both inside and outside of the classroom.

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Section: Limitationsmentioning

confidence: 99%

“…Organizations concerned with expensive, lifecritical hardware-software systems have long been concerned with assessing their health at run-time and potentially recovering from unhealthy states [6,18]. Our approach focuses on the health of the system during development, not execution.…”

Section: Related Workmentioning

confidence: 99%

We need more coverage, stat! classroom experience with the software ICU

Johnson

Zhang

2009

2009 3rd International Symposium on Empirical Software Engineering and Measurement

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“…In this situation, a project leader should rely not only on human-based reports and project artifacts, but also supplement these sources of information with tool-supported process event data monitoring. Tool-driven health monitoring system has been successfully adopted by industries, reaching from hybrid system to business activity process monitoring (Thai, Pekilis, Lau and Seviora, 2001), which in principle can be adopted in software project management domain. Other study (Schatten, Tjoa, Andjomshoa, and Shafazand, 2001) suggested a web-based OSS tools for project monitoring, particularly for dislocated or distributed development such as OSS projects.…”

Section: B Software Project Monitoringmentioning

confidence: 99%

Monitoring the “health” status of open source web‐engineering projects

Wahyudin

Mustofa

Strobel

et al. 2007

International Journal of Web Information Systems

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In response to the increasing number of open source software (OSS) project initiatives and the increasing demand of OSS products as alternative solutions by industries, it is important for particular stakeholders such as the project host/supporter (e.g., Apache Foundation, Sourceforge), project leading teams, and prospective customers to determine whether a (new) project initiative is likely to sustain and worthwhile to support. From a software project management point of view, a typical web-based OSS project can be viewed as a web engineering process, since most OSS projects exploit the benefits of a web platform and enable the project community to collaborate using web-based project tools and repositories such as mailing lists, bug trackers, and versioning systems (CVS/SVN) to deliver web systems and applications. These repositories can provide rich collections of process data, and artifacts which can be analyzed to better understand the project status. This paper proposes a concept of "health" indicators and an evaluation process that can help to get a status overview of OSS projects in a timely fashion and predict project survivability based on the project data available on web repositories. For initial empirical evaluation of the concept, we apply the indicators to well known web-based OSS projects (Apache Tomcat and Apache HTTP Server) and compare the results with challenged projects (Apache Xindice and Apache Slide). We discuss the results with OSS experts to investigate the external validity of the indicators.

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“…A Computer-Aided Dispatch (CAD) system [7], a soft real-time mobile workforce management system, was chosen as the target application for the evaluation. The system supports management and dispatch of emergency vehicles to the incidents reported.…”

Section: Experimental Evaluationmentioning

confidence: 99%

A signal processing approach to global predicate monitoring

Ghafari

Seviora

2004

Proceedings of the 23rd IEEE International Symposium on Reliable Distributed Systems, 2004.

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Global predicate evaluation is a fundamental problem in distributed systems. This paper views it from a different perspective, namely that of the Signals and Systems area of Electrical Engineering. It adapts a signal processing approach to address this problem in the context of monitoring of 'health' of a software system. The global state of the system is viewed as a 'state' signal which evolves over time. The distributed processes are assumed to possess roughly synchronized clocks. The states of individual processes are periodically sampled and reported to a global monitor. The observed system state constructed by the global monitor is viewed as being composed of two components -the consistent global states and an error signal due to the messages in transit and differences in the local clocks. The global monitor removes the error signal by processing the observed global signal through a low-pass filter. It evaluates the predicates on the filtered signal. The approach presented is applicable to distributed systems which are semi-stationary, i.e. whose internal states of interest remain stable over comparatively long intervals of time.The paper presents the relevant signal processing concepts (p-spectrum and p-filtering), outlines an architecture for global predicate monitoring and describes the signal processing done in the global monitor. The paper then summarizes an evaluation of the approach presented on a small computer aided vehicle dispatch system. The evaluation experiments are described and the results are presented and analyzed.

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Aspect-oriented implementation of software health indicators

Cited by 9 publications

References 9 publications

We need more coverage, stat! classroom experience with the software ICU

We need more coverage, stat! classroom experience with the software ICU

Monitoring the “health” status of open source web‐engineering projects

A signal processing approach to global predicate monitoring

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