Can we rely on smartphone applications

Smartphones have become the most used electronic devices. They carried out most of the functionalities of desktops, allowing various useful applications that suit the users' needs. Therefore, instead of the operator, the user has become the number one controller of the device and its applications and thus its reliability becomes an emergent need. We aim to investigate and evaluate the efficacy of Software Reliability Growth Models (SRGMs) when applied to Smartphone application failure data and check whether they achieve the same success as in the desktop/laptop area. We selected three of the most used SRGMs and applied them to three different Smartphone applications. None of the selected models were able to account for the data satisfactorily. Their failure is traced back to the specific features of mobile applications compared to desktop applications. Thus, a suitable model for Smartphone applications is still needed to improve their reliability.

Journal of Software Engineering and Applications, 2020

Software reliability is an important quality attribute, and software reliability models are frequently used to measure and predict software maturity. The nature of mobile environments differs from that of PC and server environments due to many factors, such as the network, energy, battery, and compatibility. Evaluating and predicting mobile application reliability are real challenges because of the diversity of the mobile environments in which the applications are used, and the lack of publicly available defect data. In addition, bug reports are optionally submitted by end-users. In this paper, we propose assessing and predicting the reliability of a mobile application using known software reliability growth models (SRGMs). Four software reliability models are used to evaluate the reliability of an open-source mobile application through analyzing bug reports. Our experiment proves it is possible to use SRGMs with defect data acquired from bug reports to assess and predict the software reliability in mobile applications. The results of our work enable software developers and testers to assess and predict the reliability of mobile software applications.

Information science, 2018

Assessment of software reliability is inevitable in modern software production process. Many works aimed at better models for measurement and prediction of reliability of software products. Tens of approaches have been developed and evaluated so far. However, very few works focus on approaches to compare existing systems with respect to reliability. Despite a tremendous importance to practice (and software management area), a complete and sound comparison methodology does not exist. In this paper, we propose a methodology for software reliability comparison. The methodology extensively applies the GQM approach and software reliability growth models. The methodology has been thoroughly evaluated on a case of assessment and comparison of three open source mobile operating systems: Sailfish, Tizen and CyanogenMod.

37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN'07), 2007

While the new generation of hand-held devices, e.g., smart phones, support a rich set of applications, growing complexity of the hardware and runtime environment makes the devices susceptible to accidental errors and malicious attacks. Despite these concerns, very few studies have looked into the dependability of mobile phones. This paper presents measurement-based failure characterization of mobile phones. The analysis starts with a high level failure characterization of mobile phones based on data from publicly available web forums, where users post information on their experiences in using hand-held devices. This initial analysis is then used to guide the development of a failure data logger for collecting failure-related information on SymbianOS-based smart phones. Failure data is collected from 25 phones (in Italy and USA) over the period of 14 months. Key findings indicate that: (i) the majority of kernel exceptions are due to memory access violation errors (56%) and heap management problems (18%), and (ii) on average users experience a failure (freeze or self shutdown) every 11 days. While the study provide valuable insight into the failure sensitivity of smart-phones, more data and further analysis are needed before generalizing the results.

Software Engineering, IEEE …, 1978

This paper examines the most widely used reliability modeLs. The models discussed fall into two categories, the data domain and the time domain. Besides tracing the historical development of the various models their advantages and disadvantages are analyzed. This includes models based on discrete as weil as continuous probability distributions. How well a given model performs its purpose in a specific economic environment will determine the usefulness of the model. Each of the models is examined with actual data as to the applicability of the error fmding process.

A software quality aspect is measured in terms of mean time to failure or failure intensity of the software. It is one of the key attributes when talk about software quality. Software quality may parts into quality aspect in various ways; however, software reliability seen as one of the key attribute of software quality. Software reliability is a valuable measure in planning and controlling the resources throughout the development process, as a result, high quality software can be developed. Scheduling and controlling the testing resources through software reliability measures can be completed by matching the additional cost of testing and the corresponding improvement in software reliability. It is too, a valuable measure for providing the user confidence about software correctness. A number of analytical models have been introduced in the past decades to assess the reliability of the software system. In this paper, researchers are giving an overview & analysis of software reliabil...

2006

There are many probabilistic and statistical approaches to modelling software reliability. Software reliability estimates are used for various purposes: during development, to make the release decision; and after the software has been taken into use, as part of system reliability estimation, as a basis of maintenance recommendations, and further improvement, or a basis of the recommendation to discontinue the use of the software. This report reviews proposed software reliability models, ways to evaluate them, and the role of software reliability estimation. Both frequentist and Bayesian approaches have been proposed. The advantage of Bayesian models is that various important but nonmeasurable factors, such as software complexity, architecture, quality of verification and validation activities, and test coverage are easily incorporated in the model. Despite their shortcomings – excessive data requirements for even modest reliability claims, difficulty of taking relevant nonmeasurable...

IEEE Transactions on Software Engineering, 1990

In spite of much research effort, there is no universally applicable software reliability growth model which can be trusted to give accurate predictions of reliability in all circumstances. Worse, we are not even in a position to be able to decide a priori which of the many models is most suitable in a particular context. Our own recent work has tried to resolve this problem by developing techniques whereby, for each program, the accuracy of various models can be analyzed. A user is thus enabled to select that model which is giving the most accurate reliability predictions for the particular program under examination. One of these ways of analyzing predictive accuracy, which we call the u-plot, in fact allows a user to estimate the relationship between the predicted reliability and the true reliability. In this paper we show how this can be used to improve reliability predictions in a very general way by a process of recalibration. Simulation results show that the technique gives improved reliability predictions in a large proportion of cases. However, a user does not need to trust the efficacy of recalibration, since the new reliability estimates produced by the technique are truly predictive and so their accuracy in a particular application can be judged using the earlier methods. The generality of this approach would therefore suggest that it be applied as a matter of course whenever a software reliability model is used. Indeed, although this work arose from the need to address the poor performance of soffware reliability models, it is likely to have applicability in other areas such as reliability growth modeling for hardware.

2018

In this brave new world of smartphone-dependent society, dependability is a strong requirement and needs to be addressed properly. Assessing the dependability of these mobile system is still an open issue, and companies should have the tools to improve their devices and beat the competition against other vendors. The main objective of this dissertation is to provide the methods to assess the dependability of mobile OS, fundamental for further improvements. Mobile OS are threatened mainly by traditional residual faults (when errors spread across components as failures), aging-related faults (when errors accumulate over time), and misuses by users and applications. This thesis faces these three aspects. First, it presents a qualitative method to define the fault model of a mobile OS, and an exhaustive fault model for Android. I designed and developed AndroFIT, a novel fault injection tool for Android smartphone, and performed an extensive fault injection campaign on three Android devi...

Software plays an important role in every field of human activity today varying from medical diagnosis to remote controlling spacecraft. Hence it is important for the software to provide failure-free performance whenever needed. The Information technology industry has witnessed rapid growth in the recent past. The competition among the firms also increased. The software organization in the developing countries like India can no longer survive on cost advantage alone. The software companies need to deliver reliable and quality software on time. A lot of research has been carried out on software quality management and reliability estimation. The objective of this paper is to provide a brief review of the major research contribution in the field of software reliability and identify the future research areas in software reliability estimation and prediction Keywords: software reliability growth models, nonhomogeneous Poisson process models, s-shaped models, imperfect debugging I. INTRODUCTION Many organizations utilize information technology (IT) to improve productivity, enhance operational efficiency, responsiveness, etc [1] As a result, the IT industry has witnessed tremendous growth in the past few decades. As the number of information technology companies increased, the competition among them also increased. The software organization in the developing countries like India can no longer survive or grow based on cost advantage alone. But delivering reliable and quality software on time within budgeted cost is a challenge for many organizations [2], [3]. Many times the companies would compromise on software testing and release the software with residual defects. This would make the software unreliable. The software reliability is defined as the probability of failure-free operation of a software system for a specified time in a specified environment [4]. The failure of the software during operations can lead to customer dissatisfaction, loss of market share, etc. The failure of a software used in the medical device or that used in air traffic control system can have a disastrous effect on the individual as well as society. Hence it is imperative for the software firms to ensure their product is sufficiently reliable before releasing the software for usage. This paper is a brief review of the important developments happened in the field of software reliability and identifies the future research areas. The remaining part of this article is arranged as follows: the session II describes the literature review methodology, the literature review analysis is given in session III and the conclusion are discussed in session IV. II. LITERATURE REVIEW METHODOLOGY A lot of articles have been presented at conferences, published in journals and books have been written in the last few decades on software reliability estimation and prediction. The aim of this paper is to provide a brief review of the important researches carried on developing software reliability models. The process started with searching for relevant published articles. The scope of the review is limited to the published books and papers published in journals and important conference proceedings. The databases searched are IEEE explore, Science direct, Google scholar and research gate. Two hundred and nine papers are identified for review. After reading the abstract, ninety-seven papers are shortlisted for review. Another twenty-nine papers are later dropped as the content is not directly related to the focus area of the review. Finally, sixty-eight papers are included in the review. The details are given in fig 1.