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Reliability Modeling of OSS Systems based on Innovation-Diffusion Theory and Imperfect Debugging

Gandhi N., Gondwal N., Tandon A.

Annals of Computer Science and Information Systems

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2018

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Vol. 14

53--58

EN

Open Source Software (OSS) has obtained widespread popularity in last few decades due to the exceptional contribution of some well established ones like Apache, Android, MySQL, LibreOffice, Linux etc. not only in the field of information technology but also in other sectors such as research, business and education. These systems are characterized by a huge shift in development pattern they adopt in comparison to proprietary software. Reliability modeling for such systems therefore is a growing area of research now days. Number of users adopting and working on refinement of such systems post-release play an indispensible role in their reliability growth. In this paper, we have proposed a software reliability growth model (SRGM) based on Non-homogeneous Poisson process (NHPP) based on number of users, under the phenomenon of Imperfect Debugging. The renowned Bass Model from Marketing based on the Theory of Diffusion of Innovation is used to depict the user growth phenomenon. Various fault content functions are considered in proposed models to represent imperfect debugging conditions and their performance is evaluated on fault dataset of GNOME 2.0. Four goodness-of-fit criteria namely Coefficient of Determination, Mean Square Error, Predictive Ratio Risk, and Predictive Power are used to calculate the estimation accuracy of all the proposed models and it has been observed that prediction capabilities of models based on imperfect debugging phenomenon is better than model assuming perfect debugging situation.

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A study of Optimal Testing Resource Allocation Problem for Modular Software with Change Point

Kaur G., Aggarwal A. G., Kedia A.

Annals of Computer Science and Information Systems

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2018

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Vol. 14

77--84

EN

For evolving trustworthy software, engrossing on uncovering process of fault in software is central. Nevertheless, during testing, modifications in the testing routine, defect gravity or testing-skill maturity and working environment, there can be notable change in fault detection rate. When this sort of pattern is observed in testing time it is called change point. In this article, we inquire a resource distribution problem that optimally distributes software developing resources among modules such that the total software development cost is minimized. In this problem the effect of chief circumstantial element of change-point is considered in each module. The constraint of pulling off the desired reliability level for every individual module is also incorporated in the formulation of the problem. An algorithm based on Karush Kuhn Tucker (KKT) optimality conditions is presented to solve the resulting non-linear optimization problem. A simulated numerical illustration has been analyzed to reflect the formulation of the case and its solution by the algorithm proposed.

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Modeling of software fault detection and correction processes with fault dependency

Peng R., Zhai Q.

Eksploatacja i Niezawodność

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2017

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Vol. 19, no. 3

467--475

EN

Software reliability modeling has undergone a continuous evolution over the past three decades to adapt to various and everchanging software testing environments. In existing models, immediate fault removal and fault independency are two basic and commonly used assumptions. Recently, models combining fault detection process (FDP) and fault correction process (FCP) were proposed to alleviate the immediate fault removal assumption. In this paper, we extend such a methodology by proposing a modeling framework for the FDP and FCP incorporating fault dependency. Faults are classified as leading faults and dependent faults and the FCPs for both types of faults are explicitly modeled. Several paired models considering different assumptions for debugging lags are proposed for the combined FDP and FCP. The applicability of the proposed models are illustrated using real testing data. In addition, the optimal software release policy under this framework is studied.

PL

Modelowanie niezawodności oprogramowania w ciągu ostatnich trzech dekad ulegało ciągłej ewolucji, pozwalającej dostosować je do różnych, stale zmieniających się środowisk testowych. W przypadku istniejących modeli, dwoma podstawowymi i powszechnie stosowanymi założeniami jest natychmiastowe usunięcie błędu oraz brak zależności między błędami. Ostatnio, badacze zaproponowali modele, które łagodzą pierwsze z tych założeń, łącząc proces wykrywania błędów (FDP) z procesem ich korekcji (FCP). W niniejszym artykule, rozszerzono tę metodologię, proponując paradygmat modelowania dla zintegrowanych procesów FDP i FCP uwzględniający zależności między błędami. W paradygmacie tym, błędy klasyfikuje się jako błędy nadrzędne i błędy zależne, a procesy FCP dla obu typów błędów są modelowane oddzielnie. Zaproponowano kilka połączonych w pary modeli rozważających różne założenia dotyczące opóźnień debugowania w procesach łączących detekcję i korekcję błędów. Możliwość zastosowania proponowanych modeli przedstawiono na przykładzie rzeczywistych danych testowych. Dodatkowo badano optymalną politykę aktualizacji oprogramowania, jaką można prowadzić w ramach proponowanego paradygmatu.