Understanding the perception of very small software companies towards the adoption of process standards

This paper is concerned with understanding the issues that affect the adoption of software process standards by Very Small Entities (VSEs), there needs from process standards and there willingness to engage with the new ISO/IEC 29110 standard in particular. In order to achieve this goal, a series of industry data collection studies were undertaken with a collection of VSEs. A twin track approach of a qualitative data collection (interviews and focus groups) and quantitative data collection (questionnaire), with data analysis being completed separately and finally results merged, using the coding mechanisms of grounded theory. This paper serves as a roadmap for both researchers wishing to understand the issues of process standards adoption by very small companies and also for the software process standards community

Software Process Improvement in Very Small Entities: An investigation of Software Development Knowledge Management and Team issues in maintaining and evolving software process and process improvement.

technique at both management and team level in software development VSEs. These methods assisted the researchers in examining the attitude and perceptions of practitioners towards the research issues. The researchers also made use of survey questionnaires in VSEs in order to gain more input and to validate the qualitative data. The findings from the first stage analysis (qualitative analysis), in which the content analysis and grounded theory coding approaches were used, show the pattern and detailed categories that influence and are related with the software process and process improvement in VSEs. These categories are related to each other and allow the researchers to produce and validate the studies theoretical model. Likewise the second stage analysis (quantitative analysis) assisted the researchers in conforming and enhancing the first stage findings. This investigation shows that SPI programmes in VSEs are being undertaken in a very informal manner and also in indirect ways. The primary reasons identified for the informal nature of VSE SPI are due to cost, time, customer and company size, which give a higher priority to the product rather than process. In relation to teams, the small team size coupled with the working and management style have lead VSEs to be more informal in their knowledge management process and team organization. Moreover VSEs are largely ignoring the best practice SPI models. The reasons and acceptance criteria for this are discussed. This research also confirmed that SPI does not solely depend on technology but also the contributions of human aspects have a strong emphasize, especially in VSEs. Therefore a contribution of this research is to provide an extended knowledge and understanding of SPI research area in general and within VSEs domain in particular

Managerial commitment towards SPI in small and very small enterprises

This paper compares and contrasts the results of two similar studies into the software process practices in Irish Small and Very Small Enterprises. The first study contains rich findings in relation to the role and influence of managerial experience and style, with particular respect to the company founder and software development managers in small to medium seized enterprises (SMEs), whilst the second study contains extensive findings in relation to people and management involvement / commitment and SPI goal planning in very small enterprises (VSEs). By combining these results of these two studies of Irish SMEs/VSEs we can develop a rich picture of managerial commitment towards SPI and in particular explore the similarities between Small and Very Small Enterprises

Knowledge management in software process improvement: A case study of very small entities

This chapter discusses knowledge management (KM) aspects of how software process and software process improvement (SPI) is practiced within very small entities (VSEs) in the context of Irish software development industry. In particular, this study is concerned with the process of software development knowledge management in supporting the SPI. In order to understand the support process, the authors of this chapter have studied how KM processes are practiced within VSEs which includes communica- tion, learning, sharing, and documentation process. This study also focuses in detail on the issues of the knowledge atrophy problem in VSEs. The findings explain how KM has been practiced and influenced the software development process and process improvement in VSEs. This result indicates that KM processes in VSEs are being undertaken in a very informal manner and also in indirect way. This is due to a small team size, autonomous working and macro-management style and caused VSEs to be more informal in their KM processes specifically and SPI generally. In addition, the results have indicated that the informal environment and culture helped VSEs to easily create and share knowledge between staff members and also assisted VSEs to mitigate the knowledge atrophy problem in their organization

Understanding the role of knowledge management in software development: a case study in very small companies

Software and systems engineering is distinct from other forms of engineering as it deals with an intangible product, where the progress in construction is not explicitly visible and team members often rely on the docu- mentation of others to follow and review progress. Furthermore unlike traditional engineering disciplines, there is no single standardized unified process. The role of knowledge management in the software engineering literature is becoming more evident, as the software development activity is essentially a human knowledge intensive activity and is seen by many as a key factor. This paper discusses the role of software development knowledge management within software development process and specifically how software development knowledge is managed in software development in order to support software process improvement and the role of knowledge management in this. The authors present the results of a study of knowledge management process practices in very small software companies and discusses these under the major identified issues of: Communication; Learning and sharing; Documentation and Knowledge management process and com- mitment. The findings in this study give an insight towards knowledge management practices as they relate to software development process practices in very small companies and the important factors that must be considered to preserve knowledge and quality software

A Reusability Assessment of UCP-Based Effort Estimation Framework using Object-Oriented Approach

Software effort estimation has become one of the most important concerns of software industries and Use Case Points (UCP) is seen as one of the most popular estimation models for object-oriented software development. Since year 2005, more than 10 UCP-based effort estimation techniques have been proposed either to give more options or to enhance the capability of UCP. However, there is no guidance for software practitioners to develop a quality UCP-based effort estimation applications. Therefore, we have proposed a new design framework for UCP-based technique to promote reusability in developing software applications. This paper will experiment and provide evidence showing that the framework achieved a good quality design using Quality Model for Objectoriented Design (QMOOD). The results showed that the framework has met five quality attributes and good to be reused as a guideline at the early stages of software development

An Empirical Study of User Support Tools in Open Source Software

End users’ positive response is essential for the success of any software. This is true for both commercial and Open Source Software (OSS). OSS is popular not only because of its availability, which is usually free but due to the user support it provides, generally through public platforms. The study model of this research establishes a relationship between OSS user support and available support tools. To conduct this research, we used a dataset of 100 OSS projects in different categories and examined five user support tools provided by different OSS projects. The results show that project trackers, user mailing lists, and updated versions have a significant role in gaining user support. However, we were unable to find a significant association between user support and documentation, as well as between user support and the troubleshooting guidelines provided by OSS projects

Comparing the Popularity of Testing Careers among Canadian, Indian, Chinese, and Malaysian Students

This study attempts to understand motivators and de-motivators that influence the decisions of software students to take up and sustain software testing careers across four different countries, Canada, India, China, and Malaysia. Towards that end, we have developed a cross-sectional, but simple, survey-based instrument. In this study we investigated how software engineering and computer science students perceive and value what they do and their environmental settings. This study found that very few students are keen to take up software testing careers - why is this happening with such an important task in the software life cycle? The common advantages of a software testing career are learning opportunities and easiness of the job and the common drawbacks are tediousness, complexity, and missing the opportunity to do (software) development. Our findings highlight the importance of depicting software testing activities as a set of human-dependent tasks, and emphasizes the need for research that critically examines the way in which software testers view testing activities

A Hybrid Multi-Filter Wrapper Feature Selection Method for Software Defect Predictors

Software Defect Prediction (SDP) is an approach used for identifying defect-prone software modules or components. It helps software engineer to optimally, allocate limited resources to defective software modules or components in the testing or maintenance phases of software development life cycle (SDLC). Nonetheless, the predictive performance of SDP models reckons largely on the quality of dataset utilized for training the predictive models. The high dimensionality of software metric features has been noted as a data quality problem which negatively affects the predictive performance of SDP models. Feature Selection (FS) is a well-known method for solving high dimensionality problem and can be divided into filter-based and wrapper-based methods. Filter-based FS has low computational cost, but the predictive performance of its classification algorithm on the filtered data cannot be guaranteed. On the contrary, wrapper-based FS have good predictive performance but with high computational cost and lack of generalizability. Therefore, this study proposes a hybrid multi-filter wrapper method for feature selection of relevant and irredundant features in software defect prediction. The proposed hybrid feature selection will be developed to take advantage of filter-filter and filter-wrapper relationships to give optimal feature subsets, reduce its evaluation cycle and subsequently improve SDP models overall predictive performance in terms of Accuracy, Precision and Recall values

A Novel Multidimensional Reference Model For Heterogeneous Textual Datasets Using Context, Semantic And Syntactic Clues

With the advent of technology and use of latest devices, they produces voluminous data. Out of it, 80% of the data are unstructured and remaining 20% are structured and semi-structured. The produced data are in heterogeneous format and without following any standards. Among heterogeneous (structured, semi-structured and unstructured) data, textual data are nowadays used by industries for prediction and visualization of future challenges. Extracting useful information from it is really challenging for stakeholders due to lexical and semantic matching. Few studies have been solving this issue by using ontologies and semantic tools, but the main limitations of proposed work were the less coverage of multidimensional terms. To solve this problem, this study aims to produce a novel multidimensional reference model using linguistics categories for heterogeneous textual datasets. The categories such context, semantic and syntactic clues are focused along with their score. The main contribution of MRM is that it checks each tokens with each term based on indexing of linguistic categories such as synonym, antonym, formal, lexical word order and co-occurrence. The experiments show that the percentage of MRM is better than the state-of-the-art single dimension reference model in terms of more coverage, linguistics categories and heterogeneous datasets.Comment: International Journal of Advanced Science and Applications, Volume 14, Issue 10, pp. 754-763, 202