Actor Concurrency Bugs: A Comprehensive Study on Symptoms, Root Causes, API Usages, and Differences

Actor concurrency is becoming increasingly important in the development of real-world software systems. Although actor concurrency may be less susceptible to some multithreaded concurrency bugs, such as low-level data races and deadlocks, it comes with its own bugs that may be different. However, the fundamental characteristics of actor concurrency bugs, including their symptoms, root causes, API usages, examples, and differences when they come from different sources are still largely unknown. Actor software development can significantly benefit from a comprehensive qualitative and quantitative understanding of these characteristics, which is the focus of this work, to foster better API documentations, development practices, testing, debugging, repairing, and verification frameworks. To conduct this study, we take the following major steps. First, we construct a set of 184 real-world Stackoverflow and Github actor bugs by manual analysis of 3,924 Stackoverflow questions, answers, and comments and 3,315 Github commits, messages, original and modified code snippets, issues, and pull requests. Second, we manually study these actor bugs and their fixes to understand and classify their symptoms, root causes, and API usages. Third, we study the differences between the commonalities and distributions of symptoms, root causes, and API usages of Stackoverflow and Github actor bugs. Fourth, we discuss real-world examples of bugs with these root causes and symptoms. Finally, we investigate the relation of our findings with the findings of previous work and discuss the implications of our findings using the anecdotal evidence of our actor bug examples. A few findings of our study are: (1) Symptoms of actor bugs can be classified into 5 categories with Error and Incorrect Exceptions being the most and least common symptoms (2) Root causes of actor bugs can be classified into 10 categories with Logic and Untyped Communication being the most and least common root causes (3) A small number of API packages are responsible for most of API usages by actor bugs (4) Stackoverflow and Github actors can differ significantly in the commonality and distribution of symptoms, root causes, and API usages (5) Actor developers may need help not only with complex, unknown, or semantic bugs in the development code but also with simple, well-known, well-documented, or syntactic bugs in the test code. While some of our findings are in agreement with the findings of the previous work, others are in sharp contrast

A core Erlang semantics for declarative debugging

One of the main advantages of declarative languages is their clearly established formal semantics, that allows programmers to reason about the properties of programs and to establish the correctness of tools. In particular, declarative debugging is a technique that analyses the proof trees of computations to locate bugs in programs. However, in the case of commercial declarative languages such as the functional language Erlang, sometimes the semantics is only informally defined, and this precludes these possibilities. Moreover, defining semantics for these languages is far from trivial because they include complex features needed in real applications, such as concurrency. In this paper we define a semantics for Core Erlang, the intermediate language underlying Erlang programs. We focus on the problem of concurrency and show how a medium-sized-step calculus, that avoids the details of small-step semantics but still captures the most common program errors, can be used to define an algorithmic debugger that is sound and complete.Depto. de Sistemas Informáticos y ComputaciónFac. de InformáticaTRUEpu