Multi-Attribute Utility Theory for Estimation of Optimal Release Time and Change-Point

2015 ◽  
Vol 22 (04) ◽  
pp. 1550019 ◽  
Author(s):  
Yuka Minamino ◽  
Shinji Inoue ◽  
Shigeru Yamada
Keyword(s):  
Change Point ◽  
Utility Theory ◽  
Evaluation Criteria ◽  
Evaluation Criterion ◽  
Release Time ◽  
Data Sets ◽  
Software Cost ◽  
Multi Attribute Utility Theory ◽  
Software Release ◽  
Point Total

Existing optimal software release problems have been discussed by using an evaluation criterion such as cost, reliability, delivery. When we use the methods by those evaluation criteria, the optimal release time is determined by an evaluation criterion. However, it is more realistic that we determine the optimal release time with multiple attributes. Therefore, in this study, we estimate the optimal release time by using multi-attribute utility theory (MAUT). Since MAUT is one of utility theories, we can estimate an optimal release time and change-point from the perspective of utility by maximizing the multi-attribute utility function. Especially, we consider the both of two attributes: cost and reliability. Then, we apply a software reliability growth model (SRGM) with change-point to represent the cost and reliability attributes. Concretely, we use an exponential SRGM with change-point. That is, we can estimate not only the optimal release time but also change-point. Finally, we show numerical examples by using actual data sets. Especially, we check the behavior of the optimal release time, change-point, total software cost and utility.

scholarly journals Optimal Release Time Estimation of Software System using Box-Cox Transformation and Neural Network

2018 ◽  
Vol 3 (2) ◽  
pp. 177-194 ◽  
Author(s):  
Momotaz Begum ◽  
Tadashi Dohi
Keyword(s):  
Neural Network ◽  
Count Data ◽  
Growth Models ◽  
Time Estimation ◽  
Critical Issue ◽  
Release Time ◽  
Data Sets ◽  
Software Cost ◽  
Software Release ◽  
Software Fault

The determination of the software release time for a new software product is the most critical issue for designing and controlling software development processes. This paper presents an innovative technique to predict the optimal software release time using a neural network. In our approach, a three-layer perceptron neural network with multiple outputs is used, where the underlying software fault count data are transformed into the Gaussian data by means of the well-known Box-Cox power transformation. Then the prediction of the optimal software release time, which minimizes the expected software cost, is carried out using the neural network. Numerical examples with four actual software fault count data sets are presented, where we compare our approach with conventional Non-Homogeneous Poisson Process (NHPP) -based Software Reliability Growth Models (SRGMs).

scholarly journals Optimal decisions on software release and post-release testing: A unified approach

2021 ◽  
pp. 1-1
Author(s):  
Vivek Kumar ◽  
Saurabh Panwar ◽  
P.K. Kapur ◽  
Ompal Singh
Keyword(s):  
Change Point ◽  
Reliability Estimation ◽  
Release Time ◽  
Unified Approach ◽  
Additional Time ◽  
Novel Approach ◽  
Decision Variables ◽  
Multi Attribute Utility Theory ◽  
Software Release ◽  
Termination Time

In this research, a novel approach is developed where a testing team delivers the software product first and extends the testing process for additional time in the user environment. During the operational phase, users also participate in the fault detection process and notify the defects to the software. In this study, a reliability growth model is proposed using a unified approach based on the expenditure of efforts during the testing process. Besides, debugging process is considered imperfect as new faults may enter the software during each fault removal. The developed model further considers that the developer's rate of defect identification changes with a software release. Thus, the software time-to-market acts as a change-point for the failure observation phenomenon. It is asserted that the accuracy of a software reliability estimation improves by implementing the concept of change-point. The main aim of the paper is to evaluate the optimal release time and testing termination time based on two attributes, particularly, reliability, and cost. A multi-attribute utility theory (MAUT) is applied to find a trade-off between the two conflicting attributes. Finally, a numerical example is presented by using the historical fault count data. The behavior of two decision variables is measured and compared with the existing release time strategy.

SOFTWARE RELEASE TIME BASED ON DIFFERENT MULTI-ATTRIBUTE UTILITY FUNCTIONS

2013 ◽  
Vol 20 (04) ◽  
pp. 1350012 ◽  
Author(s):  
P. K. KAPUR ◽  
V. B. SINGH ◽  
OMPAL SINGH ◽  
JYOTISH N. P. SINGH
Keyword(s):  
Utility Theory ◽  
Practical Method ◽  
Release Time ◽  
Strategic Value ◽  
Software Product ◽  
Multi Attribute Utility Theory ◽  
Two Factors ◽  
Software Release ◽  
Financial Losses ◽  
Weighted Combination

The decision to release a software product will become an even more complex and important decision. A decision has strategic value when it has the potential for large prospective financial losses to a software manufacturer or its customers or end-users. A software release decision is a tradeoff between early release to capture the benefits of an earlier market introduction and the deferral of product release to the reliability. If a software product is released too early, the software manufacturer incurs post-release costs of later fixing failures. If a software product is released too late, the additional development cost and the opportunity cost of missing a market window could be substantial. These two attribute reliability and cost need to be combined to determine the optimal release time of software. This paper proposes a new practical method for determining when to stop software testing considering reliability and cost as two factors simultaneously. The proposed new decision model is based on three different weighted combination of utility function in Multi-attribute utility theory.

scholarly journals Determining Software Time-to-Market and Testing Stop Time when Release Time is a Change-Point

2020 ◽  
Vol 5 (2) ◽  
pp. 208-224 ◽  
Author(s):  
Ompal Singh ◽  
Saurabh Panwar ◽  
P. K. Kapur
Keyword(s):  
Change Point ◽  
Growth Models ◽  
Release Time ◽  
Optimal Time ◽  
Software Project ◽  
Reliability Growth ◽  
Numerical Illustration ◽  
Time To Market ◽  
Software Product ◽  
Software Release

In software engineering literature, numerous software reliability growth models have been designed to evaluate and predict the reliability of the software products and to measure the optimal time-to-market of the software systems. Most existing studies on software release time assessment assumes that when software is released, its testing process is terminated. In practice, however, the testing team releases the software product first and continues the testing process for an added period in the operational phase. Therefore, in this study, a coherent reliability growth model is developed to predict the expected reliability of the software product. The debugging process is considered imperfect as new faults can be introduced into the software during each fault removal. The proposed model assumes that the fault observation rate of the testing team modifies after the software release. The release time of the software is therefore regarded as the change-point. It has been established that the veracity of the performance of the growth models escalates by incorporating the change-point theory. A unified approach is utilized to model the debugging process wherein both testers and users simultaneously identify the faults in the post-release testing phase. A joint optimization problem is formulated based on the two decision criteria: cost and reliability. In order to assimilate the manager’s preferences over these two criteria, a multi-criteria decision-making technique known as multi-attribute utility theory is employed. A numerical illustration is further presented by using actual data sets from the software project to determine the optimal software time-to-market and testing termination time.

scholarly journals A Multiobjective Decision-Making Model for Risk-Based Maintenance Scheduling of Railway Earthworks

2021 ◽  
Vol 11 (3) ◽  
pp. 965
Author(s):  
Irina Stipanovic ◽  
Zaharah Allah Bukhsh ◽  
Cormac Reale ◽  
Kenneth Gavin
Keyword(s):  
Utility Theory ◽  
Structural Reliability ◽  
Structural Performance ◽  
Maintenance Planning ◽  
Relative Importance ◽  
User Cost ◽  
Multi Attribute Utility Theory ◽  
Network Maintenance ◽  
Decision Making Model ◽  
Do So

Aged earthworks constitute a major proportion of European rail infrastructures, the replacement and remediation of which poses a serious problem. Considering the scale of the networks involved, it is infeasible both in terms of track downtime and money to replace all of these assets. It is, therefore, imperative to develop a rational means of managing slope infrastructure to determine the best use of available resources and plan maintenance in order of criticality. To do so, it is necessary to not just consider the structural performance of the asset but also to consider the safety and security of its users, the socioeconomic impact of remediation/failure and the relative importance of the asset to the network. This paper addresses this by looking at maintenance planning on a network level using multi-attribute utility theory (MAUT). MAUT is a methodology that allows one to balance the priorities of different objectives in a harmonious fashion allowing for a holistic means of ranking assets and, subsequently, a rational means of investing in maintenance. In this situation, three different attributes are considered when examining the utility of different maintenance options, namely availability (the user cost), economy (the financial implications) and structural reliability (the structural performance and subsequent safety of the structure). The main impact of this paper is to showcase that network maintenance planning can be carried out proactively in a manner that is balanced against the needs of the organization.

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.

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