Erlang Code Evolution Control

During the software lifecycle, a program can evolve several times for different reasons such as the optimisation of a bottle-neck, the refactoring of an obscure function, etc. These code changes often involve several functions or modules, so it can be difficult to know whether the correct behaviour of the previous releases has been preserved in the new release. Most developers rely on a previously defined test suite to check this behaviour preservation. We propose here an alternative approach to automatically obtain a test suite that specifically focusses on comparing the old and new versions of the code. Our test case generation is directed by a sophisticated combination of several already existing tools such as TypEr, CutEr, and PropEr; and other ideas such as allowing the programmer to chose an expression of interest that must preserve the behaviour, or the recording of the sequences of values to which this expression is evaluated. All the presented work has been implemented in an open-source tool that is publicly available on GitHub.Comment: Pre-proceedings paper presented at the 27th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2017), Namur, Belgium, 10-12 October 2017 (arXiv:1708.07854

An SMT-Based Concolic Testing Tool for Logic Programs

[EN] Concolic testing combines symbolic and concrete execution to generate test cases that achieve a good program coverage. Its benefits have been demonstrated for more than 15 years in the case of imperative programs. In this work, we present a concolic-based test generation tool for logic programs which exploits SMT-solving for constraint resolutionThird author is a research associate at FNRS that also supports this work (O05518FRG03). The last author is partially supported by the EU (FEDER) and the Spanish MCI/AEI under grants TIN2016-76843-C4-1-R/PID2019-104735RB-C41 and by the Generalitat Valenciana under grant Prometeo/2019/098 (DeepTrust)Fortz, S.; Mesnard, F.; Payet, E.; Perrouin, G.; Vanhoof, W.; Vidal, G. (2020). An SMT-Based Concolic Testing Tool for Logic Programs. Springer Nature. 215-219. https://doi.org/10.1007/978-3-030-59025-3_13S215219de Moura, L., Bjørner, N.: Z3: an efficient SMT solver. In: Ramakrishnan, C.R., Rehof, J. (eds.) TACAS 2008. LNCS, vol. 4963, pp. 337–340. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-78800-3_24Giantsios, A., Papaspyrou, N., Sagonas, K.: Concolic testing for functional languages. Sci. Comput. Program. 147, 109–134 (2017)Godefroid, P., Klarlund, N., Sen, K.: DART: directed automated random testing. In: Proceedings of PLDI 2005, pp. 213–223. ACM (2005)Mesnard, F., Payet, É., Vidal, G.: Concolic testing in logic programming. TPLP 15(4–5), 711–725 (2015). https://doi.org/10.1017/S1471068415000332Mesnard, F., Payet, É., Vidal, G.: On the completeness of selective unification in concolic testing of logic programs. In: Hermenegildo, M.V., Lopez-Garcia, P. (eds.) LOPSTR 2016. LNCS, vol. 10184, pp. 205–221. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-63139-4_12Mesnard, F., Payet, É., Vidal, G.: Selective unification in constraint logic programming. In: Vanhoof, W., Pientka, B. (eds.) PPDP, pp. 115–126. ACM (2017)Mesnard, F., Payet, É., Vidal, G.: Concolic Testing in CLP. CoRR abs/2008.00421 (2020). https://arxiv.org/abs/2008.00421Sen, K., Marinov, D., Agha, G.: CUTE: a concolic unit testing engine for C. In: ESEC/ FSE, pp. 263–272. ACM (2005)Ströder, T., Emmes, F., Schneider-Kamp, P., Giesl, J., Fuhs, C.: A linear operational semantics for termination and complexity analysis of ISO Prolog. In: Vidal, G. (ed.) LOPSTR 2011. LNCS, vol. 7225, pp. 237–252. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-32211-2_16Tikovsky, J.R.: Concolic testing of functional logic programs. In: Seipel, D., Hanus, M., Abreu, S. (eds.) WFLP/WLP/INAP -2017. LNCS (LNAI), vol. 10997, pp. 169–186. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00801-7_11Vidal, G.: Concolic execution and test case generation in prolog. In: Proietti, M., Seki, H. (eds.) LOPSTR 2014. LNCS, vol. 8981, pp. 167–181. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-17822-6_10Wielemaker, J., Schrijvers, T., Triska, M., Lager, T.: SWI-prolog. TPLP 12(1–2), 67–96 (2012). https://doi.org/10.1017/S147106841100049

Scaling Reliably: Improving the Scalability of the Erlang Distributed Actor Platform

Distributed actor languages are an effective means of constructing scalable reliable systems, and the Erlang programming language has a well-established and influential model. While the Erlang model conceptually provides reliable scalability, it has some inherent scalability limits and these force developers to depart from the model at scale. This article establishes the scalability limits of Erlang systems and reports the work of the EU RELEASE project to improve the scalability and understandability of the Erlang reliable distributed actor model. We systematically study the scalability limits of Erlang and then address the issues at the virtual machine, language, and tool levels. More specifically: (1) We have evolved the Erlang virtual machine so that it can work effectively in large-scale single-host multicore and NUMA architectures. We have made important changes and architectural improvements to the widely used Erlang/OTP release. (2) We have designed and implemented Scalable Distributed (SD) Erlang libraries to address language-level scalability issues and provided and validated a set of semantics for the new language constructs. (3) To make large Erlang systems easier to deploy, monitor, and debug, we have developed and made open source releases of five complementary tools, some specific to SD Erlang. Throughout the article we use two case studies to investigate the capabilities of our new technologies and tools: a distributed hash table based Orbit calculation and Ant Colony Optimisation (ACO). Chaos Monkey experiments show that two versions of ACO survive random process failure and hence that SD Erlang preserves the Erlang reliability model. While we report measurements on a range of NUMA and cluster architectures, the key scalability experiments are conducted on the Athos cluster with 256 hosts (6,144 cores). Even for programs with no global recovery data to maintain, SD Erlang partitions the network to reduce network traffic and hence improves performance of the Orbit and ACO benchmarks above 80 hosts. ACO measurements show that maintaining global recovery data dramatically limits scalability; however, scalability is recovered by partitioning the recovery data. We exceed the established scalability limits of distributed Erlang, and do not reach the limits of SD Erlang for these benchmarks at this scal