Optimal software release policy based on a two-person game of timing

1995 ◽  
Vol 32 (02) ◽  
pp. 470-481 ◽  
Author(s):  
P. Zeephongsekul ◽  
C. Chiera
Keyword(s):  
Growth Models ◽  
Homogeneous Poisson Process ◽  
Nash Equilibrium Point ◽  
Release Policy ◽  
Software Release ◽  
Software Reliability Growth ◽  
Person Game ◽  
Non Homogeneous Poisson Process ◽  
Cost Factors ◽  
Optimal Release Policy

This paper presents a software release policy based on a two-person game of timing. Existing release policies depend solely on cost factors and ignore the element of competition between rival producers, whereas in our policy both of these factors are taken into consideration. Through a series of preliminary results, it is shown that an optimal release policy exists as a Nash equilibrium point in the space of mixed strategies. We also present numerical examples of this optimal policy applied to software reliability growth models which are based on the non-homogeneous Poisson process.

Optimal software release policy based on a two-person game of timing

1995 ◽  
Vol 32 (2) ◽  
pp. 470-481 ◽  
Author(s):  
P. Zeephongsekul ◽  
C. Chiera
Keyword(s):  
Growth Models ◽  
Homogeneous Poisson Process ◽  
Nash Equilibrium Point ◽  
Release Policy ◽  
Software Release ◽  
Software Reliability Growth ◽  
Person Game ◽  
Non Homogeneous Poisson Process ◽  
Cost Factors ◽  
Optimal Release Policy

This paper presents a software release policy based on a two-person game of timing. Existing release policies depend solely on cost factors and ignore the element of competition between rival producers, whereas in our policy both of these factors are taken into consideration. Through a series of preliminary results, it is shown that an optimal release policy exists as a Nash equilibrium point in the space of mixed strategies. We also present numerical examples of this optimal policy applied to software reliability growth models which are based on the non-homogeneous Poisson process.

Optimal Software Release Policies with Debugging Time Lag

1997 ◽  
Vol 04 (03) ◽  
pp. 241-255 ◽  
Author(s):  
Tadashi Dohi ◽  
Naoto Kaio ◽  
Shunji Osaki
Keyword(s):  
Error Detection ◽  
Software Maintenance ◽  
Growth Models ◽  
Time Lag ◽  
Computer Software ◽  
Release Time ◽  
Software Release ◽  
Software Reliability Growth ◽  
Operation Phase ◽  
Non Homogeneous Poisson Process

This paper presents a new stochastic model for determining the optimal release time for a computer software in testing phase, taking account of the debugging time lag. In the earlier works, most of software release models were considered, but it was assumed that an error detected can be removed instantaneously. In other words, none discussed quantitatively the effect of the software maintenance action in the optimal software release time. Main purpose of this work is to relate the optimal software release policy with the arrival-service process on the software operation phase by users. We use the Non-Homogeneous Poisson Process (NHPP) type of software reliability growth models as the software error detection phenomena and obtain the optimal software release policies minimizing the expected total software costs. As a result, the usage circumstance of a software in operation phase gives a monotone effect to the software release planning.

scholarly journals Software Reliability-Combination of Models

2019 ◽  
Vol 9 (2) ◽  
pp. 2121-2128
Keyword(s):  
Comparative Study ◽  
Software Reliability ◽  
Growth Models ◽  
Data Sets ◽  
Reliability Growth ◽  
Suggested Model ◽  
Homogeneous Poisson Process ◽  
Software Reliability Growth ◽  
To Come ◽  
Non Homogeneous Poisson Process

Three software reliability growth models (SRGMs) - one proposed by the authors and two existing in literature based on non homogeneous Poisson Process (NHPP) are considered. Combinations of the three models are suggested as super models to measure software reliability. A comparative study of the suggested models is made with reference to three criteria as applied to eight different data sets and is noticed that the suggested model has a good contribution in the combination to come out as a better SRGM model

An Adaptive EM Algorithm for the Maximum Likelihood Estimation of Non-Homogeneous Poisson Process Software Reliability Growth Models

2017 ◽  
Vol 24 (04) ◽  
pp. 1750020 ◽  
Author(s):  
Vidhyashree Nagaraju ◽  
Lance Fiondella ◽  
Panlop Zeephongsekul ◽  
Thierry Wandji
Keyword(s):  
Maximum Likelihood ◽  
Em Algorithm ◽  
Software Reliability ◽  
Growth Models ◽  
Reliability Growth ◽  
Homogeneous Poisson Process ◽  
Em Algorithms ◽  
Failure Data ◽  
Software Reliability Growth ◽  
Non Homogeneous Poisson Process

Non-homogeneous Poisson process (NHPP) software reliability growth models (SRGM a ) enable quantitative metrics to guide decisions during the software engineering life cycle, including test resource allocation and release planning. However, many SRGM possess complex mathematical forms that make them difficult to apply. Specifically, traditional procedures solve a system of nonlinear equations to identify the numerical parameters that best characterize failure data. Recently, researchers have developed expectation-maximization (EM) algorithms for NHPP SRGM that exhibit better convergence properties and can therefore find maximum likelihood estimates with greater ease. This paper presents an adaptive EM (AEM) algorithm, which combines an earlier EM algorithm for NHPP SRGM with unconstrained search of the model parameter space. Our performance analysis shows that the AEM outperforms state-of-the-art EM algorithms for NHPP SRGM with very strong statistical significance, which is as much as hundreds of times faster on some data sets. Thus, the approach can fit SRGM very quickly. We also incorporate this high performance adaptive EM algorithm into a heuristic nested model selection procedure to objectively select a model of least complexity that best characterizes the failure data. Results indicate this heuristic approach often identifies the model possessing the best model selection criteria. a Acronyms are not pluralized.

NASH EQUILIBRIUM STRATEGIES REVISITED IN SOFTWARE RELEASE GAMES

2020 ◽  
pp. 1-21
Author(s):  
Yasuhiro Saito ◽  
Tadashi Dohi
Keyword(s):  
Nash Equilibrium ◽  
Optimization Theory ◽  
Applied Probability ◽  
Equilibrium Strategies ◽  
Release Policy ◽  
Software Release ◽  
Nash Equilibrium Strategies ◽  
Person Game

A software release game was formulated by Zeephongsekul and Chiera [Zeephongsekul, P. & Chiera, C. (1995). Optimal software release policy based on a two-person game of timing. Journal of Applied Probability 32: 470–481] and was reconsidered by Dohi et al. [Dohi, T., Teraoka, Y., & Osaki, S. (2000). Software release games. Journal of Optimization Theory and Applications 105(2): 325–346] in a framework of two-person nonzero-sum games. In this paper, we further point out the faults in the above literature and revisit the Nash equilibrium strategies in the software release games from the viewpoints of both silent and noisy type of games. It is shown that the Nash equilibrium strategies in the silent and noisy of software release games exist under some parametric conditions.

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