Abstract
Software testing and benchmarking is a key component of the software development process. Nowadays, a good practice in big software projects is the Continuous Integration (CI) software development technique. The key idea of CI is to let developers integrate their work as they produce it, instead of doing the integration at the end of each software module. In this paper, we extend a previous work on a benchmark suite for the Yap Prolog system and we propose a fully automated test bench environment for Prolog systems, named Yet Another Prolog Test Bench Environment (YAPTBE), aimed to assist developers in the development and CI of Prolog systems. YAPTBE is based on a cloud computing architecture and relies on the Jenkins framework and in a set of new Jenkins plugins to manage the underneath infrastructure. We present the key design and implementation aspects of YAPTBE and show its most important features, such as its graphical user interface and the automated process that builds and runs Prolog systems and benchmarks.

Abstract
Tabling is an implementation technique that improves the declarativeness and expressiveness of Prolog systems in dealing with recursion and redundant sub-computations. A critical component in the design of a concurrent tabling system is the implementation of the table space. One of the most successful proposals for representing tables is based on a two-level trie data structure, where one trie level stores the tabled subgoal calls and the other stores the computed answers. In previous work, we have presented a sophisticated lock-free design where both levels of the tries where shared among threads in a concurrent environment. To implement lock-freedom we used the CAS atomic instruction that nowadays is widely found on many common architectures. CAS reduces the granularity of the synchronization when threads access concurrent areas, but still suffers from problems such as false sharing or cache memory effects. In this work, we present a simpler and efficient lock-free design based on hash tries that minimizes these problems by dispersing the concurrent areas as much as possible. Experimental results in the Yap Prolog system show that our new lock-free design can effectively reduce the execution time and scales better than previous designs.

Abstract
This work proposes a new design for the supporting data structures used to implement multithreaded tabling in Prolog systems. Tabling is an implementation technique that improves the expressiveness of traditional Prolog systems in dealing with recursion and redundant computations. Mode-directed tabling is an extension to the tabling technique that supports the definition of alternative criteria for specifying how answers are aggregated, thus being very suitable for problems where the goal is to dynamically calculate optimal or selective answers. In this work, we leverage the intrinsic potential that mode-directed tabling has to express dynamic programming problems by creating a new design that improves the representation of multi-dimensional arrays in the context of multithreaded tabling. To do so, we introduce a new mode for indexing arguments in mode-directed tabled evaluations, named dim, where each dim argument features a uni-dimensional lock-free array. Experimental results using well-known dynamic programming problems on a 32-core machine show that the new design introduces less overheads and clearly improves the execution time for sequential and multithreaded tabled evaluations.

Abstract
Searching is a crucial time-consuming part of many programs, and using a good search method instead of a bad one often leads to a substantial increase in performance. Hash tries are a trie-based data structure with nearly ideal characteristics for the implementation of hash maps. In this paper, we present a novel, simple and concurrent hash map design that fully supports the concurrent search, insert and remove operations on hash tries designed to store sorted keys. To the best of our knowledge, our design is the first concurrent hash map design that puts together the following characteristics: (i) use fixed size data structures; (ii) use persistent memory references; (iii) be lock-free; and (iv) store sorted keys. Experimental results show that our design is quite competitive when compared against other state-of-the-art designs implemented in Java.

Abstract
Hash tries are a trie-based data structure with nearly ideal characteristics for the implementation of hash maps. Starting from a particular lock-free hash map data structure, named Lock-Free Hash Tries (LFHT), we focus on solving the problem of memory reclamation without losing the lock-freedom property. We propose an approach that explores the characteristics of the LFHT structure in order to achieve efficient memory reclamation with low and well-defined memory bounds. Experimental results show that our approach obtains better results when compared with other state-of-the-art memory reclamation methods and provides a competitive and scalable hash map implementation, if compared to lock-based implementations.

Abstract
Lock-free implementation techniques are known to improve the overall throughput of concurrent data structures. A hash map is an important data structure used to organize information that must be accessed frequently. A key role of a hash map is the ability to balance workloads by dynamically adjusting its internal data structures in order to provide the fastest possible access to the information. This work extends a previous lock-free hash map design to also support lock-free compression. The main goal is to significantly reduce the depth of the internal hash levels within the hash map, in order to minimize cache misses and increase the overall throughput. To materialize our design, we redesigned the existent search, insert, remove and expand operations in order to maintain the lock-freedom property of the whole design. Experimental results show that lock-free compression effectively improves the search operation and, in doing so, it outperforms the previous design, which was already quite competitive when compared against the concurrent hash map design supported by Intel.