Challenges to support automated random testing for dynamically typed languages

International audienceAutomated random testing is a proven way to identify bugs and precondition violations, and this even in well tested libraries. In the context of statically typed languages, current automated random testing tools heavily take advantage of static method declaration (argument types, thrown exceptions) to constrain input domains while testing and to identify errors. For such reason, automated random testing has not been investigated in the context of dynamically typed languages. In this paper we present the key challenges that have to be addressed to support automated testing in dynamic languages

Challenges to support automated random testing for dynamically typed languages

International audienceAutomated random testing is a proven way to identify bugs and precondition violations, and this even in well tested libraries. In the context of statically typed languages, current automated random testing tools heavily take advantage of static method declaration (argument types, thrown exceptions) to constrain input domains while testing and to identify errors. For such reason, automated random testing has not been investigated in the context of dynamically typed languages. In this paper we present the key challenges that have to be addressed to support automated testing in dynamic languages

Untangling Fine-Grained Code Changes

After working for some time, developers commit their code changes to a version control system. When doing so, they often bundle unrelated changes (e.g., bug fix and refactoring) in a single commit, thus creating a so-called tangled commit. Sharing tangled commits is problematic because it makes review, reversion, and integration of these commits harder and historical analyses of the project less reliable. Researchers have worked at untangling existing commits, i.e., finding which part of a commit relates to which task. In this paper, we contribute to this line of work in two ways: (1) A publicly available dataset of untangled code changes, created with the help of two developers who accurately split their code changes into self contained tasks over a period of four months; (2) a novel approach, EpiceaUntangler, to help developers share untangled commits (aka. atomic commits) by using fine-grained code change information. EpiceaUntangler is based and tested on the publicly available dataset, and further evaluated by deploying it to 7 developers, who used it for 2 weeks. We recorded a median success rate of 91% and average one of 75%, in automatically creating clusters of untangled fine-grained code changes

Software Agitation of a Dynamically Typed Language

Much research has been conducted on automated testing tools. Recently, Agitar Technologies developed Agitator™, which combines input generation and invariant detection into \u27software agitation\u27. Agitator analyzes code to automatically detect and report likely program invariants. However, Agitator only operates on Java, a statically typed language. I apply Agitator\u27s techniques to Python, a dynamically typed language, in a tool called PyStick. PyStick implements some alternative techniques to Agitator due to the differences between Java and Python. Since PyStick is a proof of concept, it does not cover the entirety of Python. It has nonetheless generated very promising results, and demonstrates the power and viability of software agitation on a dynamically typed language

Fast and Lean Immutable Multi-Maps on the JVM based on Heterogeneous Hash-Array Mapped Tries

An immutable multi-map is a many-to-many thread-friendly map data structure with expected fast insert and lookup operations. This data structure is used for applications processing graphs or many-to-many relations as applied in static analysis of object-oriented systems. When processing such big data sets the memory overhead of the data structure encoding itself is a memory usage bottleneck. Motivated by reuse and type-safety, libraries for Java, Scala and Clojure typically implement immutable multi-maps by nesting sets as the values with the keys of a trie map. Like this, based on our measurements the expected byte overhead for a sparse multi-map per stored entry adds up to around 65B, which renders it unfeasible to compute with effectively on the JVM. In this paper we propose a general framework for Hash-Array Mapped Tries on the JVM which can store type-heterogeneous keys and values: a Heterogeneous Hash-Array Mapped Trie (HHAMT). Among other applications, this allows for a highly efficient multi-map encoding by (a) not reserving space for empty value sets and (b) inlining the values of singleton sets while maintaining a (c) type-safe API. We detail the necessary encoding and optimizations to mitigate the overhead of storing and retrieving heterogeneous data in a hash-trie. Furthermore, we evaluate HHAMT specifically for the application to multi-maps, comparing them to state-of-the-art encodings of multi-maps in Java, Scala and Clojure. We isolate key differences using microbenchmarks and validate the resulting conclusions on a real world case in static analysis. The new encoding brings the per key-value storage overhead down to 30B: a 2x improvement. With additional inlining of primitive values it reaches a 4x improvement

An Investigation Into the Generality of a Graphical Representation of Program Code for Source to Source Translation

This thesis addresses the problem of defining a source-to-source translation system for reusable software components. It describes the development of an interoperable language for writing software components, and presents a system to translate components written in the interoperable language to a set of compatible target languages. The common features in a set of popular programming languages are analyzed to inform the design of the interoperable language. An evaluation is performed by using the source-to-source translator to convert two well-known open source Java libraries to C++ and Python, and the accuracy and performance of the resulting translations are assessed