Purpose: Testing is one of the indispensable activities in software development and is being adopted as an independent course by software engineering departments at universities worldwide. In this paper, an investigation of the performance of learners about testing is carried out, given the tendencies in the industry and motivation caused by the unavailability of similar studies in software testing field. Design/methodology/approach: This study is based on the data collected over three years (between 2012 and 2014) from students taking the Software Testing course. The course is included in the second year of undergraduate curriculum for the Bachelor of Engineering (Software Engineering). Findings: It has been observed that, from the performance perspective, automated testing outperforms structural and functional testing techniques, and that a strong correlation exists among these three approaches. Moreover, a strong programming background does help towards further success in structural and automated testing, but has no effect on functional testing. The results of different teaching styles within the course are also presented together with an analysis exploring the relationship between students' gender and success in the software testing course, revealing that there is no difference in terms of performance between male and female students in the course. Moreover, it is advisable to introduce teaching concepts one at a time because students find it difficult to grasp the ideas otherwise. Research Limitations: These findings are based on the analysis conducted using three years of data collected while teaching a course in testing. Obviously, there are some limitations to this study. For example, student's strength in programming is calculated using the score of C programming courses taken in previous year/semester. Such scores may not reflect their current level of programming knowledge. Furthermore, attempt was made to ensure that the exercises given for different testing techniques have similar difficulty level to guarantee that the difference in success between these testing techniques is due to the inherent complexity of the technique itself and not because of different exercises. Still, there is small probability that a certain degree of change in success may be due to the difference in the difficulty levels of the exercises. As such, it is obviously premature to consider the present results as final since there is a lack of similar type of studies, with which the authors can compare their results. Therefore, more work needs to be done in different settings to draw sound conclusions in this respect. Orginality/value: Although there are few studies (see, for example, Chan et al., 2005;Garousi and Zhi, 2013;Ng et al., 2004) exploring the preference of testers over distinct software testing techniques in the industry, there appears to be no paper comparing the preferences and performances of learners in terms of different testing techniques.
Agile methodologies have gained significant popularity among software development organizations during the last decade. Although agile methodologies are regarded as minimizing formal processes, they still utilize an estimation methodology for proper management. Story point is the most common input for agile effort estimation. Story point is an arbitrary measure; it reflects experiences of project participants. On the other hand, functional size is an alternative measure used in practice as an input for effort estimation. In this research, we collect and present the outcomes of three case studies which compared the effectiveness of COSMIC-based and story point based effort estimation in agile context. On selected projects of these organizations, software functional size was measured with COSMIC functional size measurement methodology. Effort prediction models were formed by using COSMIC size and actual effort spent; and the models were tested in terms of their effectiveness. The results show controversial outcomes. For all the cases, COSMIC based estimation was more precise. Therefore, COSMIC is an appropriate measure to estimate the effort in organizations that adopt agile software development. It is also observed that COSMIC allowed for computing productivity which has less disperse distribution than the productivity computed with SP. The data is also provided to help other researchers conduct their own studies.
Functional size measurement (FSM) has been used in software engineering for decades as a main driver for estimation and significant input for other various project management activities throughout the project life span. To apply FSM accurately at the early stages of software development process, especially for estimation purposes, functional user requirements need to be available in detail as required by the adopted FSM method. However, in agile software development, requirement specifications, in general, are kept minimal. For this reason, the adjustment of the requirements to the necessary granularity level has been articulated as one of the barriers preventing the diffusion of FSM practices among agile teams. In this paper, we take a closer look at this problem in order to investigate the usability of FSM and to reveal FSM related challenges empirically through case studies on real agile projects from different software organizations. This study also provides a snapshot of agile organizations in terms of requirement specification and estimation related practices
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