The Experts below are selected from a list of 61938 Experts worldwide ranked by ideXlab platform
Shigeru Yamada - One of the best experts on this subject based on the ideXlab platform.
-
optimal Software Release policy with change point
Industrial Engineering and Engineering Management, 2008Co-Authors: Shinji Inoue, Shigeru YamadaAbstract:Testing-time when a characteristic of a Software failure-occurrence or fault-detection phenomenon is notably changed is ordinarily called change-point. The effect of the change-point on Software reliability growth process influences on accuracy of the Software reliability assessment based on SRGMs which are mostly developed under the assumption that the stochastic characteristic of the Software failure-occurrence or the fault-detection phenomenon does not change throughout the testing. In this paper, we discuss a framework for Software reliability growth modeling with change-point as one of the solutions to incorporate the effect of the change-point into Software reliability assessment, and also discuss its application to an optimal Software Release problem with change-point. That is one of the interesting issues for project management of Software development. Finally, we show numerical examples of our model and derived Software Release policy by using actual data.
-
a flexible stochastic differential equation model in distributed development environment
European Journal of Operational Research, 2006Co-Authors: Yoshinobu Tamura, Shigeru YamadaAbstract:Abstract In recent years, the dependence on a computer system has become large in our social life. Especially, a Software development environment has been changing into distributed development environment interconnected with work-stations. Therefore, it becomes more difficult for Software developers to produce highly reliable Software systems efficiently, because of the more diversified and complicated Software requirements. Also, in the Software development process, the Software testing-cost occupies more than a half of the total development cost. In this paper, we derive a flexible stochastic differential equation model describing a fault-detection process during the system testing phase of the distributed development environment by applying a mathematical technique of stochastic differential equations of an It o ˆ type. Moreover, we discuss optimal Software Release problems based on the reusable rate of Software components minimizing the expected total Software cost, and also minimizing the cost with satisfying a Software reliability requirement based on the coefficient of variation.
-
economic analysis of Software Release problems with warranty cost and reliability requirement
Reliability Engineering & System Safety, 1999Co-Authors: M Kimura, T Toyota, Shigeru YamadaAbstract:Abstract We discuss optimal Software Release problems which consider both a present value and a warranty period (in the operational phase) during which the developer has to pay the cost for fixing any faults detected. It is very important with respect to Software development management that we solve an optimal Software testing time by integrating the total expected testing cost and the reliability requirement. We apply a nonhomogeneous Poisson process model to the formulation of a Software cost model and analyze three typical cases of the cost model. Moreover, we derive several optimal Release polices. Finally, numerical examples are shown to illustrate the results of the optimal policies.
-
Software reliability measurement in imperfect debugging environment and its application
Reliability Engineering & System Safety, 1993Co-Authors: Shigeru Yamada, Koichi Tokuno, Shunji OsakiAbstract:Abstract In practice, debugging operations during the testing phase of Software development are not always performed perfectly. In other words, not all the Software faults detected are corrected and removed. Generally, this is called imperfect debugging. In this paper, we discuss a Software reliability growth model considering imperfect debugging. Defining a random variable representing the cumulative number of faults corrected up to a specified testing time, this model is described by a semi-Markov process. Then, several quantitative measures are derived for Software reliability assessment in an imperfect debugging environment. The application of this model to optimal Software Release problems is also discussed. Finally, numerical illustrations for Software reliability measurement and optimal Software Release policies are presented.
Chinyu Huang - One of the best experts on this subject based on the ideXlab platform.
-
analysis of Software reliability modeling considering testing compression factor and failure to fault relationship
IEEE Transactions on Computers, 2010Co-Authors: Chinyu HuangAbstract:This paper is an attempt to relax and improve the assumptions regarding Software reliability modeling. To approximate reality much more closely, we take into account the concepts of testing compression factor and the quantified ratio of faults to failures in the modeling. Numerical examples based on real failure data show that the proposed framework has a fairly good prediction capability. Further, we also address the optimal Software Release time problem and conduct a detailed sensitivity analysis through the proposed model.
-
enhancing and measuring the predictive capabilities of testing effort dependent Software reliability models
Journal of Systems and Software, 2008Co-Authors: Chuti Lin, Chinyu HuangAbstract:Software testing is necessary to accomplish highly reliable Software systems. If the project manager can conduct well-planned testing activities, the consumption of related testing-resources will be cost-effective. Over the past 30 years, many Software reliability growth models (SRGMs) have been proposed to estimate the reliability growth of Software, and they are mostly applicable to the late stages of testing in Software development. Thus far, it appears that most SRGMs do not take possible changes of testing-effort consumption rates into consideration. However, in some cases, the policies of testing-resource allocation could be changed or adjusted. Thus, in this paper, we will incorporate the important concept of multiple change-points into Weibull-type testing-effort functions. The applicability and performance of the proposed models are demonstrated through two real data sets. Experimental results show that the proposed models give a fairly accurate prediction capability. Finally, based on the proposed SRGM, constructive rules are developed for determining optimal Software Release times.
-
cost reliability optimal Release policy for Software reliability models incorporating improvements in testing efficiency
Journal of Systems and Software, 2005Co-Authors: Chinyu HuangAbstract:Over the past 30years, many Software reliability growth models (SRGMs) have been proposed for estimation of reliability growth of products during Software development processes. One of the most important applications of SRGMs is to determine the Software Release time. Most Software developers and managers always want to know the date on which the desired reliability goal will be met. In this paper, we first review a SRGM with generalized logistic testing-effort function and the proposed generalized logistic testing-effort function can be used to describe the actual consumption of resources during the Software development process. Secondly, if Software developers want to detect more faults in practice, it is advisable to introduce new test techniques, tools, or consultants, etc. Consequently, here we propose a Software cost model that can be used to formulate realistic total Software cost projects and discuss the optimal Release policy based on cost and reliability considering testing effort and efficiency. Some theorems and several numerical illustrations are also presented. Based on the proposed models and methods, we can specifically address the problem of how to decide when to stop testing and when to Release Software for use.
-
analysis of incorporating logistic testing effort function into Software reliability modeling
IEEE Transactions on Reliability, 2002Co-Authors: Chinyu Huang, Syyen KuoAbstract:This paper investigates a SRGM (Software reliability growth model) based on the NHPP (nonhomogeneous Poisson process) which incorporates a logistic testing-effort function. SRGM proposed in the literature consider the amount of testing-effort spent on Software testing which can be depicted as an exponential curve, a Rayleigh curve, or a Weibull curve. However, it might not be appropriate to represent the consumption curve for testing-effort by one of those curves in some Software development environments. Therefore, this paper shows that a logistic testing-effort function can be expressed as a Software-development/test-effort curve and that it gives a good predictive capability based on real failure-data. Parameters are estimated, and experiments performed on actual test/debug data sets. Results from applications to a real data set are analyzed and compared with other existing models to show that the proposed model predicts better. In addition, an optimal Software Release policy for this model, based on cost-reliability criteria, is proposed.
Hoang Pham - One of the best experts on this subject based on the ideXlab platform.
-
predicting operational Software availability and its applications to telecommunication systems
International Journal of Systems Science, 2002Co-Authors: Xuemei Zhang, Hoang PhamAbstract:It is essential to predict customer-perceived Software availability during Software development and determine when to Release the Software to maintain a balance among time-to-market, development cost and Software quality. This paper presents methods and procedures to predict Software failure rates from a user perspective in system test phases and to reverse-engineer in order to estimate Software Release time for given availability targets. Software reliability analysis is conducted based on non-homogenous Poisson process models. Software system test data of current Release are used to estimate the number of residual faults by the end of system tests and data of previous Releases or similar products (including system test data, post-system test data and field failure data) provide a means to predict a user-perceived average failure rate of a fault. Software system availability can be predicted from these estimates. Both execution and calendar times are considered. A Software resource utilization model is d...
-
a Software cost model with warranty and risk costs
IEEE Transactions on Computers, 1999Co-Authors: Hoang Pham, Xuemei ZhangAbstract:In this paper, a cost model with warranty cost, time to remove each error detected in the Software system, and risk cost due to Software failure is developed. A Software reliability model based on non-homogeneous Poisson process is used. The optimal Release policies to minimize the expected total Software cost are discussed. A Software tool is also developed using Excel and Visual Basic to facilitate the task of determining the optimal Software Release time. Numerical examples are provided to illustrate the results.
-
a Software cost model with imperfect debugging random life cycle and penalty cost
International Journal of Systems Science, 1996Co-Authors: Hoang PhamAbstract:The paper develops a cost model with an imperfect debugging and random life cycle as well as a penalty cost that is used to determine the optimal Release policies for a Software system. The Software reliability model, based on the nonhomogeneous Poisson process, allows for three different error types: critical, major and minor errors. The model also allows for the introduction of any of these errors during the removal of an error. Using the Software reliability model presented, the cost model with multiple error types and imperfect debugging is developed. This cost also considers the penalty cost due to delay for a scheduled delivery time and the length of the Software life cycle is random with a known distribution. The optimal Software Release policies that minimize the expected Software system costs (subject to the various constraints) or maximize the Software reliability subject to a cost constraint, are then determined. Numerical examples are provided to illustrate the results.
Gunther Ruhe - One of the best experts on this subject based on the ideXlab platform.
-
intelligent support for Software Release planning
Product Focused Software Process Improvement, 2004Co-Authors: Gunther Ruhe, Mark StanfordAbstract:One of the most prominent issues involved in incremental Software development is to decide upon the most appropriate Software Release plans taking into account all explicit and implicit objectives and constraints. Such decisions have become even more complicated in the presence of large number of stakeholders such as different groups of users, managers, or developers. However, early involvement of customers and understanding of their real needs is one of the core success factors of Software business [16].
-
hybrid intelligence in Software Release planning
Hybrid Intelligent Systems, 2004Co-Authors: Gunther Ruhe, An NgoAbstract:There is a growing recognition that an incremental approach to Software development is often more suitable and less risky than the traditional waterfall approach. Delivering Software in an incremental fashion suggests better customer satisfaction and reduces many of the risks associated with delivering large Software projects. In this paper, we consider the problem of deciding which requirements should be assigned to which Release. The proposed hybrid approach called EVOLVE* improves existing methods for Release planning by combining the strength of mathematical models with the subtleness of experts' knowledge and judgment. It makes use of different computationally intelligent techniques such as evolutionary computing and principles of multi-criteria decision aid. This is combined with appropriate involvement of human intelligence. EVOLVE* consists of three main phases called modeling, exploration, and consolidation. Different from former algorithms of the EVOLVE family, our new approach plans only two Releases in advance, i.e., each requirement is assigned to one of the following three categories: "next Release", "next but one Release", "not yet assigned". EVOLVE* aims to achieve maximum stakeholder satisfaction. Our iterative procedure allows intelligent search of most promising solutions under the competing criteria of time, benefit and quality as described by the "magic triangle". The complete approach is illustrated by a case study example.
-
Software Release planning an evolutionary and iterative approach
Information & Software Technology, 2004Co-Authors: Des Greer, Gunther RuheAbstract:Abstract To achieve higher flexibility and to better satisfy actual customer requirements, there is an increasing tendency to develop and deliver Software in an incremental fashion. In adopting this process, requirements are delivered in Releases and so a decision has to be made on which requirements should be delivered in which Release. Three main considerations that need to be taken account of are the technical precedences inherent in the requirements, the typically conflicting priorities as determined by the representative stakeholders, as well as the balance between required and available effort. The technical precedence constraints relate to situations where one requirement cannot be implemented until another is completed or where one requirement is implemented in the same increment as another one. Stakeholder preferences may be based on the perceived value or urgency of delivered requirements to the different stakeholders involved. The technical priorities and individual stakeholder priorities may be in conflict and difficult to reconcile. This paper provides (i) a method for optimally allocating requirements to increments; (ii) a means of assessing and optimizing the degree to which the ordering conflicts with stakeholder priorities within technical precedence constraints; (iii) a means of balancing required and available resources for all increments; and (iv) an overall method called EVOLVE aimed at the continuous planning of incremental Software development. The optimization method used is iterative and essentially based on a genetic algorithm. A set of the most promising candidate solutions is generated to support the final decision. The paper evaluates the proposed approach using a sample project.
-
intelligent support for Software Release planning
Lecture Notes in Computer Science, 2004Co-Authors: Gunther Ruhe, Mark StanfordAbstract:One of the most prominent issues involved in incremental Software development is to decide upon the most appropriate Software Release plans taking into account all explicit and implicit objectives and constraints. Such decisions have become even more complicated in the presence of large number of stakeholders such as different groups of users, managers, or developers. However, early involvement of customers and understanding of their real needs is one of the core success factors of Software business [16]. This paper introduces a six step process model for Release planning. It is inspired by the Quality Improvement Paradigm [2], as Release planning is a learning and improvement process as well. Emphasis is on proposing the tool support implementing this process. The use of the intelligent decision support tool ReleasePlanner is presented by comparing a baseline scenario reflecting current state-of-the practice of Release planning with a supposed improvement scenario obtained after usage of the tool. Initial experience from a real-world environment at iGrafx Corel Inc. is used to validate the improvement scenario.
-
quantitative studies in Software Release planning under risk and resource constraints
International Symposium on Empirical Software Engineering, 2003Co-Authors: Gunther Ruhe, Des GreerAbstract:Delivering Software in an incremental fashion implicitly reduces many of the risks associated with delivering large Software projects. However, adopting a process, where requirements are delivered in Releases means decisions have to be made on which requirements should be delivered in which Release. This paper describes a method called EVOLVE+, based on a genetic algorithm and aimed at the evolutionary planning of incremental Software development. The method is initially evaluated using a sample project. The evaluation involves an investigation of the tradeoff relationship between risk and the overall benefit. The link to empirical research is two-fold: firstly, our model is based on interaction with industry and randomly generated data for effort and risk of requirements. The results achieved this way are the first step for a more comprehensive evaluation using real-world data. Secondly, we try to approach uncertainty of data by additional computational effort providing more insight into the problem solutions: (i) effort estimates are considered to be stochastic variables following a given probability function; (ii) instead of offering just one solution, the L-best (L > 1) solutions are determined. This provides support in finding the most appropriate solution, reflecting implicit preferences and constraints of the actual decision-maker. Stability intervals are given to indicate the validity of solutions and to allow the problem parameters to be changed without adversely affecting the optimality of the solution.
Guenther Ruhe - One of the best experts on this subject based on the ideXlab platform.
-
an empirical study of meta and hyper heuristic search for multi objective Release planning
ASSOC COMPUTING MACHINERY, 2018Co-Authors: Yuanyuan Zhang, Guenther Ruhe, Mark Harman, Gabriela Ochoa, Sjaak BrinkkemperAbstract:A variety of meta-heuristic search algorithms have been introduced for optimising Software Release planning. However, there has been no comprehensive empirical study of different search algorithms across multiple different real-world datasets. In this article, we present an empirical study of global, local, and hybrid meta- and hyper-heuristic search-based algorithms on 10 real-world datasets. We find that the hyper-heuristics are particularly effective. For example, the hyper-heuristic genetic algorithm significantly outperformed the other six approaches (and with high effect size) for solution quality 85% of the time, and was also faster than all others 70% of the time. Furthermore, correlation analysis reveals that it scales well as the number of requirements increases.
-
Software Release Planning
2016 IEEE ACM 38th International Conference on Software Engineering Companion (ICSE-C), 2016Co-Authors: Xavier Franch, Guenther RuheAbstract:One of the most critical activities in Software product development is the decisional process that assigns features to subsequent Releases under technical, resource, risk, and budget constraints. This decision-centric process is referred to as Software Release planning (SRP).This briefing will expose a state of the art on SRP. A survey of the most relevant approaches will be presented. Emphasis will be made on their applicability (concerning e.g. type of development process - being more predictive versus more adaptive, type of system - commercial, open source product or mobile app), tool support and degree of validation in industry. One of these approaches, EVOLVE, will be analysed in detail.
-
balancing value and modifiability when planning for the next Release
International Conference on Software Maintenance, 2009Co-Authors: Anas Jadallah, Matthias Galster, Mahmood Moussavi, Guenther RuheAbstract:Planning the next Release in Software Release planning addresses the problem of assigning features to the next Release such that technical, resource, risk, and budget constraints are met. This paper studies the planning for the next Release of an evolving system from a bi-criteria perspective. We introduce a method called NRP-trade-off to adjust baseline Release plans for more modifiability by replacing lower value features with features having a higher modifiability. For that purpose, we include a new approach for feature modeling and assessing modifiability by applying object-oriented design metrics to the feature domain. We also briefly introduce a case study.
-
optimized resource allocation for Software Release planning
IEEE Transactions on Software Engineering, 2009Co-Authors: An Ngothe, Guenther RuheAbstract:Release planning for incremental Software development assigns features to Releases such that technical, resource, risk and budget constraints are met. Planning of Software Releases and allocation of resources cannot be handled in isolation. A feature can be offered as part of a Release only if all its necessary tasks are done before the given Release date. We assume a given pool of human resources with different degrees of productivity to perform different types of tasks. To address the inherent difficulty of this process, we propose a two-phased optimization approach that combines the strength of two existing solution methods. The industrial applicability of the approach is primarily directed towards mature organizations having systematic development and measurement processes in place. The expected practical benefit of the planning method is to provide Release plan solutions that achieve a better overall business value (e.g., expressed by the degree of stakeholder satisfaction) by better allocation of resources. Without ignoring the importance of the human expert in this process, the contributions of the paper are seen in making the overall process more objective and the resulting decisions more transparent.
-
a systematic approach for solving the wicked problem of Software Release planning
Soft Computing, 2007Co-Authors: An Ngothe, Guenther RuheAbstract:Release planning is known to be a cognitively and computationally difficult problem. Different kinds of uncertainties make it hard to formulate and solve the problem. Our solution approach called EVOLVE+ mitigates these difficulties by (i) an evolutionary problem solving method combining rigorous solution methods to solve the actual formalization of the problem combined with the interactive involvement of the human experts in this process, (ii) provision of a portfolio of diversified and qualified solutions at each iteration of the solution process, and (iii) the application of a multi-criteria decision aid method (ELECTRE IS) to assist the selection of the final solution from a set of qualified solutions. At the final stage of the process, an outranking relation is established among the qualified candidate solutions to address existing soft constraints or objectives. A case study is provided to illustrate and initially evaluate the given approach. The proposed method and results are not limited to Software Release planning, but can be adapted to a wider class of wicked planning problems.
