Modelling the successive software release time of S-shaped model with imperfect debugging

2016 ◽  
Author(s):  
Sunil Kumar Khatri ◽  
Aakanksha Sonik ◽  
Deepak Kumar ◽  
Rana Majumdar
Keyword(s):  
Release Time ◽  
Imperfect Debugging ◽  
Software Release

Software warranty cost optimization under imperfect debugging

2019 ◽  
Vol 37 (9/10) ◽  
pp. 1233-1257
Author(s):  
Vibha Verma ◽  
Sameer Anand ◽  
Anu Gupta Aggarwal
Keyword(s):  
Software Development ◽  
Optimization Problem ◽  
Failure Process ◽  
Release Time ◽  
Development Cost ◽  
Data Set ◽  
Imperfect Debugging ◽  
Content Type ◽  
Software Release ◽  
The Impact

Purpose The purpose of this paper is to identify and quantify the key components of the overall cost of software development when warranty coverage is given by a developer. Also, the authors have studied the impact of imperfect debugging on the optimal release time, warranty policy and development cost which signifies that it is important for the developers to control the parameters that cause a sharp increase in cost. Design/methodology/approach An optimization problem is formulated to minimize software development cost by considering imperfect fault removal process, faults generation at a constant rate and an environmental factor to differentiate the operational phase from the testing phase. Another optimization problem under perfect debugging conditions, i.e. without error generation is constructed for comparison. These optimization models are solved in MATLAB, and their solutions provide insights to the degree of impact of imperfect debugging on the optimal policies with respect to software release time and warranty time. Findings A real-life fault data set of Radar System is used to study the impact of various cost factors via sensitivity analysis on release and warranty policy. If firms tend to provide warranty for a longer period of time, then they may have to bear losses due to increased debugging cost with more number of failures occurring during the warrantied time but if the warranty is not provided for sufficient time it may not act as sufficient hedge during field failures. Originality/value Every firm is fighting to remain in the competition and expand market share by offering the latest technology-based products, using innovative marketing strategies. Warranty is one such strategic tool to promote the product among masses and develop a sense of quality in the user’s mind. In this paper, the failures encountered during development and after software release are considered to model the failure 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.

Two-Dimensional Generalized Framework to Determine Optimal Release and Patching Time of a Software

2017 ◽  
Vol 24 (06) ◽  
pp. 1740003
Author(s):  
Chetna Choudhary ◽  
P. K. Kapur ◽  
A. K. Shrivastava ◽  
Sunil K. Khatri
Keyword(s):  
High Reliability ◽  
Cost Model ◽  
Real Life ◽  
Release Time ◽  
Two Dimensional ◽  
Data Set ◽  
Software Firms ◽  
Software Release ◽  
A Minor ◽  
Reliable Software

Demand for highly reliable software is increasing day by day which in turn has increased the pressure on the software firms to provide reliable software in no time. Ensuring high reliability of the software can only be done by prolonged testing which in result consumes more resources which is not feasible in the existing market situation. To overcome this, software firms are providing patches after software release so as to fix the remaining number of bugs and to give better product experience to users. An update/fix is a minor portion of software to repair the bugs. With such patches, organizations enhance the performance of the software. Delivering patches after release demands extra effort and resources which are costly and hence not economical for the firms. Also, early patch release might cause improper fixation of bugs, on the other hand, delayed release may increase the chances of more failure during the operational phase. Therefore, determining optimal patch release time is imperative. To overcome the above issues we have formulated a two-dimensional time and effort-based cost model to regulate the optimum release and patch time of software, so that the total cost is minimized. Proposed model is validated on a real life data set.

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 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.

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