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We investigate the maximum increase in number of phrases that results from changing k consecutive symbols in a string x having length n parsed using an LZ'77-like algorithm. We consider a class of compression algorithms that partition a sequence into a collection y of nonoverlapping, variable-length phrases and encode them. Each phrase either is a singleton or matches a substring that starts to its left. We show that changing a single symbol of x in position i can yield an expansion that is of order O(n - i)2/3 as (n - i) → ∞. Our lower bound requires an alphabet size of O(n - i)1/3. We also show that changing k consecutive symbols starting from position i can yield an expansion having a similar but somewhat more involved form. The paper contains both analytically derived upper and lower bounds, and algorithms for numerically computing tighter bounds. While deriving the bounds, we provide a detailed analysis of how expansion can arise when changing consecutive symbols. This problem is motivated by management policies for computer systems, such as the IBM Memory eXpansion Technology (MXT) or the IBM iSeries compressed disks, that use LZ'77-like coding on small compression units, such as 1-4 kbyte, and store the compressed data in memory or on disk tracks. Here, when a change of a portion of the compression unit occurs, for example, an L2 cache line, or a 512-byte disk sector, the data is recompressed and potentially stored in a different location. Knowing the maximum expansion, rather than the average expansion, is an important factor for designing policies for allocation and management of memory or disk space. [ABSTRACT FROM AUTHOR]

An understanding of how software is employed in the field can yield many opportunities for quality improvements. Profiling released software can provide such an understanding. However, profiling released software is difficult due to the potentially large number of deployed sites that must be profiled, the transparency requirements at a user's site, and the remote data collection and deployment management process. Researchers have recently proposed various approaches to tap into the opportunities offered by profiling deployed systems and overcome those challenges. Initial studies have illustrated the application of these approaches and have shown their feasibility. Still, the proposed approaches, and the tradeoffs between overhead, accuracy, and potential benefits for the testing activity have been barely quantified. This paper aims to overcome those limitations. Our analysis of 1,200 user sessions on a 155 KLOC deployed system substantiates the ability of field data to support test suite improvements, assesses the efficiency of profiling techniques for released software, and the effectiveness of testing efforts that leverage profiled field data. [ABSTRACT FROM AUTHOR]

Advance knowledge of which files in the next release of a large software system are most likely to contain the largest numbers of faults can be a very valuable asset. To accomplish this, a negative binomial regression model has been developed and used to predict the expected number of faults in each file of the next release of a system. The predictions are based on the code of the file in the current release, and fault and modification history of the file from previous releases. The model has been applied to two large industrial systems, one with a history of 17 consecutive quarterly releases over 4 years, and the other with nine releases over 2 years. The predictions were quite accurate: For each release of the two systems, the 20 percent of the files with the highest predicted number of faults contained between 71 percent and 92 percent of the faults that were actually detected, with the overall average being 83 percent. The same model was also used to predict which files of the first system were likely to have the highest fault densities (faults per KLOC). In this case, the 20 percent of the files with the highest predicted fault densities contained an average of 62 percent of the system's detected faults. However, the identified files contained a much smaller percentage of the code mass than the files selected to maximize the numbers of faults. The model was also used to make predictions from a much smaller input set that only contained fault data from integration testing and later. The prediction was again very accurate, identifying files that contained from 71 percent to 93 percent of the faults, with the average being 84 percent. Finally, a highly simplified version of the predictor selected files containing, on average, 73 percent and 74 percent of the faults for the two systems. [ABSTRACT FROM AUTHOR]

Large and complex real-time systems can benefit significantly from a component-based development approach where new systems are constructed by composing reusable, documented and previously tested concurrent objects. However, reusing objects which execute under real-time constraints is problematic because application specific time and synchronization constraints are often embedded in the internals of these objects. The tight coupling of functionality and real-time constraints makes objects interdependent, and as a result difficult to reuse in another system. We propose a model which facilitates separate and modular specification of real-time constraints, and show how separation of real-time constraints and functional behavior is possible. We present our ideas using the Actor model to represent untimed objects, and the Real-time Synchronizers language to express real-time and synchronization constraints. We discuss specific mechanisms by which Real-time Synchronizers can govern the interaction and execution of untimed objects. We treat our model formally, and succinctly define what effect real-time constraints have on a set of concurrent objects. We briefly discuss how a middleware scheduling and event-dispatching service can use the synchronizers to execute the system. [ABSTRACT FROM AUTHOR]

An object based formal method for the development of real-time systems, called ATOM, is presented. The method is an integration of the real-time formal technique TAM (Temporal Agent Model) with an industry-strength structured methodology known as HRT-HOOD. ATOM is a systematic formal approach based on the refinement calculus. Within ATOM, a formal specification (or abstract description statement) contains Interval Temporal Logic (ITL) description of the timing, functional, and communication behavior of the proposed real-time system. This formal specification can be analyzed and then refined into concrete statements through successive applications of sound refinement laws. Both abstract and concrete statements are allowed to freely intermix. The semantics of the concrete statements in ATOM are defined denotationally in specification-oriented style using ITL. [ABSTRACT FROM AUTHOR]