An Open-Source Software Reliability Model Considering Learning Factors and Stochastically Introduced Faults

work of W. Edwards Deming has convinced industry that must first measure quality and then emphasise process to improve quality. In response to Deming's arguments and in light of perception that software industry is unable to produce quality products on schedule, and within budget, more software development organisations are now emphasising process measurement, monitoring, and assessment. This paper describes what is meant by software process and discusses an approach for its measurement and improvement. INTRODUCTION Unreliable software makes big news, from emergency services disasters to social security payment blunders. Improved software quality is essential to ensure reliable products and services, and gain customer satisfaction. While software development has existed for more than four decades, we failed so far to make as an industry and as an engineering discipline rather than craft. Developing reliable and usable software that is delivered on and within budget still represents difficult endeavour for many organisations. As role of software becomes increasingly critical for businesses as well as for human lives, problems caused by software products that are late, over budget, or that do not work, become magnified. If lives are lost or people inconvenienced due to incapable computer software, news media is there to make big stories. Organisations are realising that their fundamental problems is immaturity of their software process. Robert Lai (1993) proposes that process improvement is second maturity wave of software industry. He states that the first wave of software was developed using waterfall model in 1970's. Today we are Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517 216 Software Management in midst of second wave maturity movement as we attempt to formally define development process and best ways to continuously improve it (Lai 1993). Taking lead in this area has been Watts Humphrey (Humphrey 1989, 1990, 1991), and Software Engineering Institute (SEI) at Carnegie Mellon University. SEI started in 1986 to develop process maturity framework to help organisations appraise maturity of their software process, and to provide guidance for organisations to improve their software process capability. A brief description of framework was released in September 1987, including maturity questionnaire. SEI evolved model and questionnaire into 5 -Level Capability Maturity Model (CMM) in 1991. In February 1993, released CMM version 1.1 (Paulk et al 1993). This paper discusses software process and describes capability maturity model (CMM). It also shows how CMM can be used as basis to measure maturity of software process of an organisation and plan its improvement. SOFTWARE QUALITY AND PROCESS IMPROVEMENT In his book Quality is Free Phil Crosby states that: Quality is free. It is not gift, is free. What cost money are unqualify of things all actions that involve not doing jobs right first time (Crosby 1980). If such statement is true for many disciplines, is particularly true for evidence is abundant in number of software products which exceeded their budget, were produced late, failed to satisfy user requirements, and are full of bugs. demand for improved software quality is increasing to ensure reliable products and services. benefits of improved quality comes in form of reduction in failure costs. For software projects failure costs include (DTI 1992): • costs of correcting defects, both before and after delivery • overruns against and budget • unnecessary high maintenance costs • indirect costs which users incur due to poor quality software link between process maturity and software quality is expressed in premise that The quality of software system is governed by quality of process used to develop and maintain it. One stumbling block to improving software quality seems to be that not enough attention is paid to overall development process itself. While software professionals typically devote their to developing, testing or documenting software products, no one has prime responsibility for improving software process. Experience has shown that if Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517 Managing Systems 217 no one is working on software process, orderly improvement is unlikely. process certainly won't improve itself, rather, most likely, will deteriorate over time. Continuous improvement can occur only if process infrastructure is in place. Watts Humphrey argues in an early article published in Datamation, April 1989 that: Without work on process, there will be little or no progress in improving software. THE SOFTWARE PROCESS Adopting process view of software development represents revolutionary change in perspective. A process orientation to software development involves elements of structure, focus, measurement, ownership, skills, and supporting technology. In this section we investigate what is meant by software process. What Is Software Process According to Webster's dictionary, process is a system of operations in producing something .. series of actions, changes, or functions that achieve an end result. Chambers Concise Dictionary defines process as a series of actions or events .. sequence of operations or changes undergone. IEEE defines process as a sequence of steps performed for given purpose. In general business context, process is defined as a structured, measured set of activities designed to produce specified output for particular customer or market (Davenport 1993). These definitions put strong emphasis on HOW work is done, in contrast to product focus's emphasis on WHAT. Accordingly, process can be considered as a specific ordering of work activities across and place, with beginning, an end, and clearly identified inputs and outputs: structure for action. In this paper we will adopt following definitions quoted in (Humphrey 1990, Paulk et al 1993) are intended to encompass software throughout its life, which covers new development, enhancement, and repair. software process is The set of activities, methods, and practices used in production and evolution of software. software engineering process is The total set of software engineering activities needed to transform user's requirements into software. Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517 218 Software Management People and Software Process Software development is still people-intensive activity. Talented people are most important element in any software organisation. Even if you get best people available, if they do not follow common process, if everyone wrote in different programming languages, used different conventions, or didn't co-ordinate their design and code changes with their peers, results will be chaos. Successful software organisations have learned that even best professionals need structured and disciplined environment in which to do cooperative work. Software organisations that do not establish such disciplines condemn their people to endless hours of repetitively solving technically trivial problems. obvious fact is that attracting best people is vital, but is also essential to support them with an effectively managed software process. Technology and Software Process Another myth is widespread belief that some technologically advanced tool or method will provide magic answer to software crisis. This is not only wrong, but is dangerous. Organisations which jumped on bandwagon of CASE tools, and ended up in failure and wasted and effort have learned their lesson hard way. Just ask yourself before introducing technology: What do I want to automate? In absence of defined, practised, and managed process, introducing automation can lead to increased chaos. There are several factors which limit effective use of software technology: an illdefined process, inconsistent process implementation, and poor process management. Software technology cannot be fully effective until these problems have been properly addressed. Need for Defined Process If no effort is made to define and enhance software development process across whole organisation, each software development project latches on to its own tools, methods, and practices with little guidance available on how to use them. This ad hoc approach will not be sufficient to tackle task of developing complex software systems. goal of software process management is to enable organisations to produce software that meets cost, schedules, and quality objectives. principles are same that underpins statistical process control-principles that have been successfully used in controlling scientific experiments and in high -volume manufacturing operations. Statistical concepts have been found to be just as applicable to software development as they are to production of manufactured goods such as motor cars. Applying such concepts will only be possible if there is defined and managed process. Software Process Models Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517

Welcome to the International Conference on Software and Systems Process (ICSSP) held in Zurich, Switzerland, on June 2nd and 3rd, 2012. Having grown from a Software Process Workshop in 2005 to the International Conference on Software Process (ICSP) in 2007, and finally to the International Conference on Software and Systems Process (ICSSP) in 2011, this conference series has established its place in the software engineering community as a respected conference focusing on research and practice related to software and systems development process. Software and software systems development use processes as one major means for achieving and ensuring the quality of the final product. This leads to specific challenges regarding software processes such as simplicity, adaptability, standard conformance, the coordination of multiple domains and lifecycles, etc. Processes from other domains (e.g., health care, manufacturing, business, aerospace, automotive systems, and others) face similar challenges. Yet, they share interesting similarities with and differences to software processes. The question is: How can we in the software domain learn from other domains to meet our software process engineering challenges? The ICSSP conferences hence connect the traditional software and systems process community with outside views and insights, broadening its scope of software development processes to system development and explicitly including processes of other domains such as health care, business, and manufacturing. By sharing process development theories and practices from such domains, ICSSP 2012 is investigating novel solutions to today's process challenges. Correspondingly, the main theme of ICSSP 2012 is Beyond Software and Software Systems Processes, signaling our goal of learning from domains other than the traditional software process community.

In the software industry, two software engineering development best practices coexist: open-source and closed-source software. The former has a shared code that anyone can contribute, whereas the latter has a proprietary code that only the owner can access. Software reliability is crucial in the industry when a new product or update is released. Applying meta-heuristic optimization algorithms for closed-source software reliability prediction has produced significant and accurate results. Now, open-source software dominates the landscape of cloud-based systems. Therefore, providing results on open- source software reliability - as a quality indicator - would greatly help solve the open-source software reliability growth- modelling problem. The reliability is predicted by estimating the parameters of the software reliability models. As software reliability models are inherently nonlinear, traditional approaches make estimating the appropriate parameters difficult and ineffective. Consequently, software reliability models necessitate a high- quality parameter estimation technique. These objectives dictate the exploration of potential applications of meta- heuristic swarm intelligence optimization algorithms for optimizing the parameter estimation of nonhomogeneous Poisson process-based open-source software reliability modelling. The optimization algorithms are firefly, social spider, artificial bee colony, grey wolf, particle swarm, moth flame, and whale. The applicability and performance evaluation of the optimization modelling approach is demonstrated through two real open-source software reliability datasets. The results are promising

We empirically examine the relationship between software design modularity and software quality in open source software (OSS) development projects. Conventional wisdom suggests that degree of software modularity affects software quality. An analysis of 203 software releases in 46 OSS projects hosted on SourceForge.net lends support for a more complex relationship between software modularity and software quality than conventional wisdom suggests. We find that software modularity is associated with reduced software complexity, an increased number of static software bugs, and a mixed relationship with the percentage of bugs closed. We do not find empirical evidence supporting any relationship between modularity and other measures of customer satisfaction. In addition to empirically testing the relationship between modularity and quality, we introduce new measures of software modularity and software quality. Implications are developed for the theory of modularity and the practice of software development.

In recent years, more and more companies have moved from closed source software development to open source software (OSS) development. The reliability assessment of OSS has become an important issue. However, due to the lack of a standardized development process and uncertain number of participating developers, it is hard to measure the reliability of OSS compared to closed source software. This paper proposes a framework for reliability automatic assessment of OSS based on JIRA. It contains the failure data acquisition module, the reliability modeling module and the reliability attribute analysis module. The proposed framework is applied on popular OSS Kafka to assess the reliability. The experimental results show that the proposed framework is good for the reliability assessment of OSS.

Measuring open source software success

One opportunity for organizations to participate in open source software (OSS) development is through <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">organizations OSS</i> (orgsOSS), a term we use to describe a group of organizations that commit resources to collectively develop OSS. This archetype of OSS development is distinct from other types that include organizations, yet is understudied. As organizations increasingly contribute to and rely on OSS as part of their strategy, understanding how they can collaborate to build software holds importance for the future of software development. This study collects a unique dataset of development tasks from a large orgsOSS project spanning over two years and seven releases. Building on existing OSS research, we explore norms with respect to collaboration, i.e., how developers assign, discuss, and complete tasks, in an orgsOSS project. Interestingly, our analysis reveals that developers in orgsOSS do not always adhere to ideals of widespread sharing and participation espoused by traditional OSS, however some developer and task characteristics helped foster these ideals. Based on these and other findings, we develop a set of propositions and associated collaboration mechanisms that are important to future orgsOSS and other similarly structured software development projects.

Open source software is becoming increasingly prominent, and the economic structure of open-source development is changing. In recent years, firms motivated by revenues from software services markets have become the primary contributors to open-source development. In this paper we study the role of services in open source software development and explore the choice between open source and proprietary software. Specifically, our economic model jointly analyzes the investment and pricing decisions of the originators of software and of subsequent open-source contributors. We find that if a contributor is efficient in software development, the originator should adopt an open-source strategy, allowing the contributor to offer higher total quality and capture the higher end of the market while the originator focuses on providing software services to lower end consumers. Conversely, if the contributor is not efficient in development, the originator should adopt a proprietary software development strategy, gaining revenue from software sales and squeezing the contributor out of the services market. In certain cases an increase in originator development efficiency can result in increased contributor profits. Finally, we find that, somewhat counterintuitively, an increase in contributor development efficiency can reduce overall social welfare.

Open Source vs. Proprietary Software: Competition and Compatibility

Many papers proposed in the software engineering and information systems literature are dedicated to analysis of software projects missing their schedules, exceeding their budgets, delivering software products with poor quality and in some cases even wrong functionality. The expression “software crisis“ has been coined since the late 60's to illustrate this phenomenon. Various solutions has been proposed by academics and practitioners in order to deal with the software crisis, counter these trends and improve productivity and software quality. Such solutions recommend software process improvement as the best way to build software products needed by modern organizations. Among the well-known solutions, many are based either on software development tools or on software development approaches, methods, processes, and notations. Nevertheless, the scope of these solutions seems to be limited and the improvements they provide are often not significant. We think that since software artifacts are accumulation of knowledge owned by organizational stakeholders, the software crisis is due to a knowledge gap resulting from the discrepancy between the knowledge integrated in software systems and the knowledge owned by organizational actors. In particular, integrating knowledge management in software development process permits reducing the knowledge gap through building software products which reflect at least partly the organization's know-how. In this paper, we propose a framework which provides a definition of knowledge based on information systems architecture and describes a knowledge-oriented software development process to help organizations in reducing the software crisis impacts.

The purpose of this study is to analyze the reliability growth of Open Source Software (OSS) versus software developed in-house (i.e. Closed Source Software, CSS) using Software Reliability Growth Model. This study uses 22 datasets containing failure data of CSS and 18 datasets containing defect data of OSS projects. The failure data are modelled by eight SRGM (Musa Okumoto, Inflection S-Shaped, Goel Okumoto, Delayed S-Shaped, Logistic, Gompertz, Yamada Exponential, and Generalized Goel Model). These models are chosen due to their widespread use. The results can be summarized as follows All selected SRGM fit to defect data of the OSS projects in the same manner as that of CSS. OSS reliability grows similarly to that of CSS. Musa Okumoto and Inflection S-Shaped perform well for CSS, while for OSS Inflection S-Shaped and Gompertz are good performers. SRGM can be used for reliability characterization of OSS projects.

The method of earned value management is traditionally applied to the progress assessment of actual software projects in many IT companies. Also, Open Source Software (OSS) are used under the various situations because of cost reduction, standardization, and quick delivery. In particular, many OSS are developed and managed by using fault big data recorded on the bug tracking systems. Several research papers in terms of OSS reliability assessment have been published in the past. The fault is caused by the poor handling of effort control. Therefore, we can make a stable and safety operation for OSS system if the OSS project is appropriately managed by using the software effort. The OSS effort estimation model by using a conventional stochastic differential equation model is discussed in this paper. Then, we propose the optimal maintenance problem based on the earned value requirement. In particular, we develop the OSS project stability support tool. Furthermore, several performance illustrations of the developed software tool are shown by using the effort data under actual OSS project.

Third-party libraries are used frequently in modern software development. Websites that are visited millions of times a day often make heavy use of open-source software libraries. As a software developer, using these libraries has a number of advantages. Developers save time and effort because functionality does not have to be rebuilt from scratch. Additionally, these libraries are often completely free to use, have been tested extensively by other users and contain a large amount of expertise of other developers. There are also a number of disadvantages to using these libraries. When the interface of a software library changes, this has direct impact on software systems using this interface. In this thesis, the origin, impact and costs of interface instability is investigated. As it turns out, public interfaces of software libraries frequently change without providing proper signals to users of that interface. These changes have measurable impact in systems using these interfaces. Besides changes in interfaces, changes in functionality can also impact end users of a library. In this thesis, compression is employed to measure changes in functionality that a library provides. These changes in functionality are then used in a software growth model that relates the concepts of software growth, quality, work done and size to each other.

Open source software systems are playing important roles in many scientific and business software applications. To ensure acceptable levels of software quality Open source software (OSS) development process uses advanced and effective techniques. Quality improvement involves the detection of potential relationship between defect and open source software metrics. Many companies are investing in open source projects for making effective software. But, because open source software is often developed with a different management style and groups of people than the industrial ones, the quality and reliability of the code needs to be investigated. Hence, more projects need to be measured to obtain information about the characteristics and nature of the source code. This paper presents an empirical study of the fault prediction capabilities of object-oriented metrics given by Chidamber and Kemerer. We have carried out an empirical study and tried to find whether these metrics are significantly associated with faults or not. For this we have extracted source code processed it for metrics and associated it with the bugs. Finally the fault prediction capabilities of object oriented metrics have been evaluated by using Naive Bayes and J48 machine learning algorithms

The development of information technology in Indonesia has increasingly driven the use of Open Source Software (OSS), which enables open collaboration among developers worldwide. However, the implementation of copyright protection for OSS in Indonesia faces challenges, as the basic principle of copyright, which grants exclusive rights to creators, contradicts the spirit of sharing that lies at the core of OSS. This article aims to analyze the challenges faced in implementing copyright for OSS in Indonesia and explore how the adaptation of copyright regulations can support OSS development. This research employs a descriptive qualitative approach with document analysis and interviews as data collection methods. Data sources are derived from relevant legal literature on copyright, OSS licenses, and interviews with software developers and legal experts in Indonesia. The findings indicate that the mismatch between the exclusive nature of copyright principles and the collaborative spirit of OSS is the main challenge in legal regulation. Moreover, limited understanding of OSS licenses among software developers in Indonesia exacerbates the potential for copyright violations. Therefore, this study recommends the need for updates to the Copyright Law to better support the concept of open licensing and to provide better education for developers regarding the legal implications of using OSS. Strengthening the monitoring system is also necessary to ensure that OSS developers in Indonesia can continue to innovate safely while respecting copyright.