No Arabic abstract
Recently, many software organizations have been adopting Continuous Delivery and Continuous Deployment (CD) practices to develop and deliver quality software more frequently and reliably. Whilst an increasing amount of the literature covers different aspects of CD, little is known about the role of software architecture in CD and how an application should be (re-) architected to enable and support CD. We have conducted a mixed-methods empirical study that collected data through in-depth, semi-structured interviews with 21 industrial practitioners from 19 organizations, and a survey of 91 professional software practitioners. Based on a systematic and rigorous analysis of the gathered qualitative and quantitative data, we present a conceptual framework to support the process of (re-) architecting for CD. We provide evidence-based insights about practicing CD within monolithic systems and characterize the principle of small and independent deployment units as an alternative to the monoliths. Our framework supplements the architecting process in a CD context through introducing the quality attributes (e.g., resilience) that require more attention and demonstrating the strategies (e.g., prioritizing operations concerns) to design operations-friendly architectures. We discuss the key insights (e.g., monoliths and CD are not intrinsically oxymoronic) gained from our study and draw implications for research and practice.
GraphQL is a query language for APIs and a runtime to execute queries. Using GraphQL queries, clients define precisely what data they wish to retrieve or mutate on a server, leading to fewer round trips and reduced response sizes. Although interest in GraphQL is on the rise, with increasing adoption at major organizations, little is known about what GraphQL interfaces look like in practice. This lack of knowledge makes it hard for providers to understand what practices promote idiomatic, easy-to-use APIs, and what pitfalls to avoid. To address this gap, we study the design of GraphQL interfaces in practice by analyzing their schemas - the descriptions of their exposed data types and the possible operations on the underlying data. We base our study on two novel corpuses of GraphQL schemas, one of 16 commercial GraphQL schemas and the other of 8,399 GraphQL schemas mined from GitHub projects. We make both corpuses available to other researchers. Using these corpuses, we characterize the size of schemas and their use of GraphQL features and assess the use of both prescribed and organic naming conventions. We also report that a majority of APIs are susceptible to denial of service through complex queries, posing real security risks previously discussed only in theory. We also assess ways in which GraphQL APIs attempt to address these concerns.
Continuous Deployment (CD) has emerged as a new practice in the software industry to continuously and automatically deploy software changes into production. Continuous Deployment Pipeline (CDP) supports CD practice by transferring the changes from the repository to production. Since most of the CDP components run in an environment that has several interfaces to the Internet, these components are vulnerable to various kinds of malicious attacks. This paper reports our work aimed at designing secure CDP by utilizing security tactics. We have demonstrated the effectiveness of five security tactics in designing a secure pipeline by conducting an experiment on two CDPs - one incorporates security tactics while the other does not. Both CDPs have been analyzed qualitatively and quantitatively. We used assurance cases with goal-structured notations for qualitative analysis. For quantitative analysis, we used penetration tools. Our findings indicate that the applied tactics improve the security of the major components (i.e., repository, continuous integration server, main server) of a CDP by controlling access to the components and establishing secure connections.
The performance of fault localization techniques is critical to their adoption in practice. This paper reports on an empirical study of a wide range of fault localization techniques on real-world faults. Different from previous studies, this paper (1) considers a wide range of techniques from different families, (2) combines different techniques, and (3) considers the execution time of different techniques. Our results reveal that a combined technique significantly outperforms any individual technique (200% increase in faults localized in Top 1), suggesting that combination may be a desirable way to apply fault localization techniques and that future techniques should also be evaluated in the combined setting. Our implementation is publicly available for evaluating and combining fault localization techniques.
Software systems are designed according to guidelines and constraints defined by business rules. Some of these constraints define the allowable or required values for data handled by the systems. These data constraints usually originate from the problem domain (e.g., regulations), and developers must write code that enforces them. Understanding how data constraints are implemented is essential for testing, debugging, and software change. Unfortunately, there are no widely-accepted guidelines or best practices on how to implement data constraints. This paper presents an empirical study that investigates how data constraints are implemented in Java. We study the implementation of 187 data constraints extracted from the documentation of eight real-world Java software systems. First, we perform a qualitative analysis of the textual description of data constraints and identify four data constraint types. Second, we manually identify the implementations of these data constraints and reveal that they can be grouped into 30 implementation patterns. The analysis of these implementation patterns indicates that developers prefer a handful of patterns when implementing data constraints and deviations from these patterns are associated with unusual implementation decisions or code smells. Third, we develop a tool-assisted protocol that allows us to identify 256 additional trace links for the data constraints implemented using the 13 most common patterns. We find that almost half of these data constraints have multiple enforcing statements, which are code clones of different types.
It is becoming increasingly difficult for game developers to manage the cost of developing a game, while meeting the high expectations of gamers. One way to balance the increasing gamer expectation and development stress is to build an active modding community around the game. There exist several examples of games with an extremely active and successful modding community, with the Minecraft game being one of the most notable ones. This paper reports on an empirical study of 1,114 popular and 1,114 unpopular Minecraft mods from the CurseForge mod distribution platform, one of the largest distribution platforms for Minecraft mods. We analyzed the relationship between 33 features across 5 dimensions of mod characteristics and the popularity of mods (i.e., mod category, mod documentation, environmental context of the mod, remuneration for the mod, and community contribution for the mod), to understand the characteristics of popular Minecraft mods. We firstly verify that the studied dimensions have significant explanatory power in distinguishing the popularity of the studied mods. Then we evaluated the contribution of each of the 33 features across the 5 dimensions. We observed that popular mods tend to have a high quality description and promote community contribution.