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Abstract Software product line engineering is a best practice for managing reuse in families of software systems that is increasingly being applied to novel and emerging domains. In this work we investigate the use of software product line engineering in one of these new domains, synthetic biology. In synthetic biology living organisms are programmed to perform new functions or improve existing functions. These programs are designed and constructed using small building blocks made out of DNA. We conjecture that there are families of products that consist of common and variable DNA parts, and we can leverage product line engineering to help synthetic biologists build, evolve, and reuse DNA parts. In this paper we perform an investigation of domain engineering that leverages an open-source repository of more than 45,000 reusable DNA parts. We show the feasibility of these new types of product line models by identifying features and related artifacts in up to 93.5% of products, and that there is indeed both commonality and variability. We then construct feature models for four commonly engineered functions leading to product lines ranging from 10 to 7.5 × 10 20 products. In a case study we demonstrate how we can use the feature models to help guide new experimentation in aspects of application engineering. Finally, in an empirical study we demonstrate the effectiveness and efficiency of automated reverse engineering on both complete and incomplete sets of products. In the process of these studies, we highlight key challenges and uncovered limitations of existing SPL techniques and tools which provide a roadmap for making SPL engineering applicable to new and emerging domains. 

Software product line engineering is a best practice for managing reuse in families of software systems. In this work, we explore the use of product line engineering in the emerging programming domain of synthetic biology. In synthetic biology, living organisms are programmed to perform new functions or improve existing functions. These programs are designed and constructed using small building blocks made out of DNA. We conjecture that there are families of products that consist of common and variable DNA parts, and we can leverage product line engineering to help synthetic biologists build, evolve, and reuse these programs. As a first step towards this goal, we perform a domain engineering case study that leverages an open-source repository of more than 45,000 reusable DNA parts. We are able to identify features and their related artifacts, all of which can be composed to make different programs. We demonstrate that we can successfully build feature models representing families for two commonly engineered functions. We then analyze an existing synthetic biology case study and demonstrate how product line engineering can be beneficial in this domain. 

This paper presents a gesture set for communicating states to novice users from a small Unmanned Aerial System (sUAS) through an elicitation study comparing gestures created by participants recruited from the general public with varying levels of experience with an sUAS. Previous work in sUAS flight paths sought to communicate intent, destination, or emotion without focusing on concrete states such as Low Battery or Landing. This elicitation study uses a participatory design approach from human-computer interaction to understand how novice users would expect an sUAS to communicate states, and ultimately suggests flight paths and characteristics to indicate those states. We asked users from the general public (N=20) to create gestures for seven distinct sUAS states to provide insights for human-drone interactions and to present intuitive flight paths and characteristics with the expectation that the sUAS would have general commercial application for inexperienced users. The results indicate relatively strong agreement scores for three sUAS states: Landing (0.455), Area of Interest (0.265), and Low Battery (0.245). The other four states have lower agreement scores, however even they show some consensus for all seven states. The agreement scores and the associated gestures suggest guidance for engineers to develop a common set of flight paths and characteristics for an sUAS to communicate states to novice users. 

As assurance cases have grown in popularity for safety-critical systems, so too has their complexity and thus the need for methods to systematically build them. Assurance cases can grow too large and too abstract for anyone but the original builders to understand, making reuse difficult. Reuse is important because different systems might have identical or similar components, and a good solution for one system should be applicable to similar systems. Prior research has shown engineers can alleviate some of the complexity issues through modularity and identifying common patterns which are more easily understood for reuse across different systems. However, we believe these patterns are too complicated for users who lack expertise in software engineering or assurance cases. This paper suggests the concept of lower-level patterns which we call recipes. We use the safety-critical field of synthetic biology, as an example discipline to demonstrate how a recipe can be built and applied.