Automatic Programming Assessment (or APA) is known as a method to assist educators in executing automated assessment and grading on students' programming exercises and assignments. Having to execute dynamic testing in APA, providing an adequate set of test data via a systematic process of test data generation is necessarily essential. Though researches respecting to software testing have proposed various significant methods to realize automated test data generation, it occurs that recent studies of APA rarely utilized these methods. Merely some of the limited studies appeared to resolve this circumstance, yet the focus on realizing test set and test data covering more thorough dynamic-structural testing are still deficient. Thus, we propose a method that utilizes MC/DC coverage criteria to support more thorough automated test data generation for dynamic-structural testing in APA (or is called DyStruc-TDG). In this paper, we reveal the means of deriving and generating test cases and test data for the DyStruc-TDG method and its verification concerning the reliability criteria (or called positive testing) of test data adequacy in programming assessments. This method offers a significant impact on assisting educators dealing with introductory programming courses to derive and generate test cases and test data via APA regardless of having knowledge of designing test cases mainly to execute structural testing. As regards to this, it can effectively reduce the educators' workload as the process of manual assessments is typically prone to errors and promoting inconsistency in marking and grading.
The Open Source Software (OSS) Innovation process is no more a foreign face in the software development community as it is increasingly being used as a platform for modern software innovation both in the commercial and software research community. Although the concept of freedom is mostly prominent with the OSS innovation process, less than 2% of the contributors are women in this male dominated area. Minorities, including women, are often ignored in its process. This paper presents the case of lack of participation from women in the OSS innovation process. Lack of participation and contributions from women in OSS innovation creates an imbalanced population in the OSS based knowledge demography and an unbalanced proportion of gender distribution. Based on a comprehensive review, this paper aims to suggest a Constructivist-Technofeminist-OSS Innovation Process framework for understanding female contributions in OSS innovation, not only from a singular point of technical view, but also from social constructivist and feminist perspectives.
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