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Context: In this article we considered knowledge transfer (KT) in global software development (GSD) from two perspectives, state-of-the-art and state-of-the-practice, in order to identify what are the challenges that hamper the success of KT in global software teams, as well as to find out what are the mitigation strategies that can be used to overcome such challenges. Objectives: The overall aim of this work is to provide a body of knowledge for enabling successful KT in GSD settings. This is achieved by an in-depth understanding of KT challenges and mitigation strategies, both from the perspective of literature and industry. It also identifies the similarities and di↵erences in challenges and strategies gathered from literature studies and industrial experts. Methods: In order to fulfill the aim of the research, we collected data through a Systematic Literature Review (SLR) and conducted interviews with industrial experts. Through the SLR we found 35 primary studies relevant to our objectives. We also conducted eight interviews of experienced industrial professionals from eight di↵erent multinational companies world-wide. For analyzing the data we used grounded theory and cross-case analysis. Results: In total, 60 di↵erent challenges and 79 unique mitigation strategies are identified from both SLR and interview results. The challenges and mitigation strategies are grouped into three core categories of personnel, project and technology factors, thus giving rise to a conceptualization called as 2PT factors. There are greater numbers of challenges and mitigation strategies in the project and personnel factors, highlighting the complex interplay of project-related and human-intensive issues in GSD projects, while the technology factor plays the role as facilitator in transferring knowledge. The study also maps the mitigation strategies to challenges, which can guide practitioners in their selection of strategies to use for overcoming KT challenges in GSD. Conclusions: We conclude that e↵ective management of project and personnel factors, facilitated by technological factors, are crucial for a successful transfer of knowledge in GSD projects. Thus in future, the researchers and practitioners need to focus on the 2PT factors for ensuring e↵ective KT in GSD settings.

Search-based software testing (SBST) has shown a potential to decrease cost and increase quality of testingrelated software development activities. Research in SBST has so far mainly focused on the search for isolated tests that are optimal according to a fitness function that guides the search. In this paper we make the case for fitness functions that measure test fitness in relation to existing or previously found tests; a test is good if it is diverse from other tests. We present a model for test variability and propose the use of a theoretically optimal diversity metric at variation points in the model. We then describe how to apply a practically useful approximation to the theoretically optimal metric. The metric is simple and powerful and can be adapted to a multitude of different test diversity measurement scenarios. We present initial results from an experiment to compare how similar to human subjects, the metric can cluster a set of test cases. To carry out the experiment we have extended an existing framework for test automation in an object-oriented, dynamic programming language.

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Food supply chain plays a vital role in human health and food prices. Food supply chain inefficiencies in terms of unfair competition and lack of regulations directly affect the quality of human life and increase food safety risks. This work merges Hyperledger Fabric, an enterprise-ready blockchain platform with existing conventional infrastructure, to trace a food package from farm to fork using an identity unique for each food package while keeping it uncomplicated. It keeps the records of business transactions that are secured and accessible to stakeholders according to the agreed set of policies and rules without involving any centralized authority. This paper focuses on exploring and building an uncomplicated, low-cost solution to quickly link the existing food industry at different geographical locations in a chain to track and trace the food in the market.

Context: Combinatorial testing strategies have lately received a lot of attention as a result of their diverse applications. In its simple form, a combinatorial strategy can reduce several input parameters (configurations) of a system into a small set based on their interaction (or combination). In practice, the input configurations of software systems are subjected to constraints, especially in case of highly configurable systems. To implement this feature within a strategy, many difficulties arise for construction. While there are many combinatorial interaction testing strategies nowadays, few of them support constraints.Objective: This paper presents a new strategy, to construct combinatorial interaction test suites in the presence of constraints.Method: The design and algorithms are provided in detail. To overcome the multi-judgement criteria for an optimal solution, the multi-objective particle swarm optimisation and multithreading are used. The strategy and its associated algorithms are evaluated extensively using different benchmarks and comparisons.Results: Our results are promising as the evaluation results showed the efficiency and performance of each algorithm in the strategy. The benchmarking results also showed that the strategy can generate constrained test suites efficiently as compared to state-of-the-art strategies.Conclusion:The proposed strategy can form a new way for constructing of constrained combinatorial interaction test suites. The strategy can form a new and effective base for future implementations.of input parameters based on their combination. Each combination could form a specific configuration of the software-under-test (SUT). The goal is to cover all possible t-combinations (sometimes called t − tuples) by an optimised set (where t is the interaction strength) [1]. This could be a difficult task in case of highly configurable systems, which leads to combinatorial explosion and nondeterministic polynomial-time hard (NP-hard) problems [2]. In addition, the problem of constrained interactions has recently appeared [3].Nowadays, software development is shifted from building an isolated, product-by-product approach to software product lines (SPL) [4]. In addition to the many features this approach provides like minimising the cost and market reachability time, it facilitates the idea of customisable software products. With this approach, there are many customisable features that could be added to or extracted from the functionality of a specific software based on the needs of the developers or customers. Eclipse represents a well-known example of SPL in which many functions and plug-ins (i.e., having different features) can be added or extracted from its main framework [5]. Evidence showed that most of the faults may result due to the interaction among these features [1,6]. Hence, all the interactions must be tested carefully. However, in reality, there are many constraints among the features. Some features must or must not appear with others and they may be included or excluded from th...