@article {14805,
	title = {A tool to help tune where computation is performed},
	journal = {IEEE Transactions on Software Engineering},
	volume = {27},
	year = {2001},
	month = {2001/07//},
	pages = {618 - 629},
	abstract = {We introduce a new performance metric, called load balancing factor (LBF), to assist programmers when evaluating different tuning alternatives. The LBF metric differs from traditional performance metrics since it is intended to measure the performance implications of a specific tuning alternative rather than quantifying where time is spent in the current version of the program. A second unique aspect of the metric is that it provides guidance about moving work within a distributed or parallel program rather than reducing it. A variation of the LBF metric can also be used to predict the performance impact of changing the underlying network. The LBF metric is computed incrementally and online during the execution of the program to be tuned. We also present a case study that shows that our metric can accurately predict the actual performance gains for a test suite of six programs},
	keywords = {Computational modeling, Current measurement, Distributed computing, distributed program, distributed programming, load balancing factor, Load management, parallel program, parallel programming, Performance analysis, performance evaluation, Performance gain, performance metric, Programming profession, software metrics, software performance evaluation, Testing, Time measurement, tuning},
	isbn = {0098-5589},
	doi = {10.1109/32.935854},
	author = {Eom, Hyeonsang and Hollingsworth, Jeffrey K}
}
@article {16314,
	title = {Comparing detection methods for software requirements inspections: a replicated experiment},
	journal = {IEEE Transactions on Software Engineering},
	volume = {21},
	year = {1995},
	month = {1995/06//},
	pages = {563 - 575},
	abstract = {Software requirements specifications (SRS) are often validated manually. One such process is inspection, in which several reviewers independently analyze all or part of the specification and search for faults. These faults are then collected at a meeting of the reviewers and author(s). Usually, reviewers use Ad Hoc or Checklist methods to uncover faults. These methods force all reviewers to rely on nonsystematic techniques to search for a wide variety of faults. We hypothesize that a Scenario-based method, in which each reviewer uses different, systematic techniques to search for different, specific classes of faults, will have a significantly higher success rate. We evaluated this hypothesis using a 3{\texttimes}24 partial factorial, randomized experimental design. Forty eight graduate students in computer science participated in the experiment. They were assembled into sixteen, three-person teams. Each team inspected two SRS using some combination of Ad Hoc, Checklist or Scenario methods. For each inspection we performed four measurements: (1) individual fault detection rate, (2) team fault detection rate, (3) percentage of faults first identified at the collection meeting (meeting gain rate), and (4) percentage of faults first identified by an individual, but never reported at the collection meeting (meeting loss rate). The experimental results are that (1) the Scenario method had a higher fault detection rate than either Ad Hoc or Checklist methods, (2) Scenario reviewers were more effective at detecting the faults their scenarios are designed to uncover, and were no less effective at detecting other faults than both Ad Hoc or Checklist reviewers, (3) Checklist reviewers were no more effective than Ad Hoc reviewers, and (4) Collection meetings produced no net improvement in the fault detection rate-meeting gains were offset by meeting losses},
	keywords = {Assembly, Computer science, Design for experiments, detection methods, Fault detection, fault detection rate, Fault diagnosis, formal specification, formal verification, Gain measurement, individual fault detection rate, Inspection, Loss measurement, nonsystematic techniques, performance evaluation, Performance gain, replicated experiment, scenario-based method, Software development management, software requirements inspections, software requirements specifications, team fault detection rate},
	isbn = {0098-5589},
	doi = {10.1109/32.391380},
	author = {Porter, Adam and Votta,L. G. and Basili, Victor R.}
}
