Semantic mutation testing

This is the Pre-print version of the Article. The official published version can be obtained from the link below - Copyright @ 2011 ElsevierMutation testing is a powerful and flexible test technique. Traditional mutation testing makes a small change to the syntax of a description (usually a program) in order to create a mutant. A test suite is considered to be good if it distinguishes between the original description and all of the (functionally non-equivalent) mutants. These mutants can be seen as representing potential small slips and thus mutation testing aims to produce a test suite that is good at finding such slips. It has also been argued that a test suite that finds such small changes is likely to find larger changes. This paper describes a new approach to mutation testing, called semantic mutation testing. Rather than mutate the description, semantic mutation testing mutates the semantics of the language in which the description is written. The mutations of the semantics of the language represent possible misunderstandings of the description language and thus capture a different class of faults. Since the likely misunderstandings are highly context dependent, this context should be used to determine which semantic mutants should be produced. The approach is illustrated through examples with statecharts and C code. The paper also describes a semantic mutation testing tool for C and the results of experiments that investigated the nature of some semantic mutation operators for C

Translate One, Analyze Many: Leveraging the Microsoft Intermediate Language and Source Code Transformation for Model Checking

AbstractIn this paper we present a source transformation-based framework to support model checking of source code written with languages belonging to Microsoft's .NET platform. The framework includes a set of source transformation rules to guide the transformation, tools to support assertion checking, as well as a tool for the automation of deadlock detection. The framework results in both executable and formally verifiable artifacts. We provide details of the tools in the framework, and evaluate the framework on a few small case studies

GAMESPECT: A Composition Framework and Meta-Level Domain Specific Aspect Language for Unreal Engine 4

Game engine programming involves a great number of software components, many of which perform similar tasks; for example, memory allocation must take place in the renderer as well as in the creation routines while other tasks such as error logging must take place everywhere. One area of all games which is critical to the success of the game is that of game balance and tuning. These balancing initiatives cut across all areas of code from the player and AI to the mission manager. In computer science, we’ve come to call these types of concerns “cross cutting”. Aspect oriented programming was developed, in part, to solve the problems of cross cutting: employing “advice” which can be incorporated across different pieces of functionality. Yet, despite the prevalence of a solution, very little work has been done to bring cross cutting to game engine programming. Additionally, the discipline involves a heavy amount of code rewriting and reuse while simultaneously relying on many common design patterns that are copied from one project to another. In the case of game balance, the code may be wildly different across two different games despite the fact that similar tasks are being done. These two problems are exacerbated by the fact that almost every game engine has its own custom DSL (domain specific language) unique to that situation. If a DSL could showcase the areas of cross cutting concerns while highlighting the ability to capture design patterns that can be used across games, significant productivity savings could be achieved while simultaneously creating a common thread for discussion of shared problems within the domain. This dissertation sought to do exactly that- create a metalanguage called GAMESPECT which supports multiple styles of DSLs while bringing aspect-oriented programming into the DSL’s to make them DSAL (domain specific aspect languages). The example cross cutting concern was game balance and tuning since it’s so pervasive and important to gaming. We have created GAMESPECT as a language and a composition framework which can assist engine developers and game designers in balancing their games, forming one central place for game balancing concerns even while these concerns may cross different languages and locations inside the source code. Generality was measured by showcasing the composition specifications in multiple contexts and languages. In addition to evaluating generality and performance metrics, effectiveness was be measured. Specifically, comparisons were made between a balancing initiative when performed with GAMESPECT vs a traditional methodology. In doing so, this work shows a clear advantage to using a Metalanguage such as GAMESPECT for this task. In general, a line of code reduction of 9-40% per task was achieved with negligible effects to performance. The use of a metalanguage in Unreal Engine 4 is a starting point to further discussions concerning other game engines. In addition, this work has implications beyond video game programming. The work described highlights benefits which might be achieved in other disciplines where design pattern implementations and cross-cutting concern usage is high; the real time simulation field and the field of Windows GUI programming are two examples of future domains

An open framework for semantic code queries on heterogeneous repositories

To help developers understand and reuse programs, semantic queries on the source code itself is attractive. Although programs in heterogeneous languages are being controlled for collaborative software development, most queries supported by various source code repositories are based either on the metadata of the repositories, or on indexed identifiers and method signatures. Few provide full support to search for structures that are common across different programming languages and different viewpoints (hence heterogeneous). To facilitate understanding and reuses, in this paper, we propose a novel source code query framework that (1) transforms source code to a unified abstract syntax format, and handles heterogeneity (non-isomorphism) at the abstract syntax level; (2) stores source code on a cloud-based NoSQL storage in MongoDB; (3) rewrites semantic query patterns into the NoSQL form. The efficiency of the framework has been evaluated to support several open-source hosting platforms

Proceedings of the 3rd Workshop on Domain-Specific Language Design and Implementation (DSLDI 2015)

The goal of the DSLDI workshop is to bring together researchers and practitioners interested in sharing ideas on how DSLs should be designed, implemented, supported by tools, and applied in realistic application contexts. We are both interested in discovering how already known domains such as graph processing or machine learning can be best supported by DSLs, but also in exploring new domains that could be targeted by DSLs. More generally, we are interested in building a community that can drive forward the development of modern DSLs. These informal post-proceedings contain the submitted talk abstracts to the 3rd DSLDI workshop (DSLDI'15), and a summary of the panel discussion on Language Composition

Transforming Programs between APIs with Many-to-Many Mappings

Transforming programs between two APIs or different versions of the same API is a common software engineering task. However, existing languages supporting for such transformation cannot satisfactorily handle the cases when the relations between elements in the old API and the new API are many-to-many mappings: multiple invocations to the old API are supposed to be replaced by multiple invocations to the new API. Since the multiple invocations of the original APIs may not appear consecutively and the variables in these calls may have different names, writing a tool correctly to cover all such invocation cases is not an easy task. In this paper we propose a novel guided-normalization approach to address this problem. Our core insight is that programs in different forms can be semantics-equivalently normalized into a basic form guided by transformation goals, and developers only need to write rules for the basic form to address the transformation. Based on this approach, we design a declarative program transformation language, PATL, for adapting Java programs between different APIs. PATL has simple syntax and basic semantics to handle transformations only considering consecutive statements inside basic blocks, while with guided-normalization, it can be extended to handle complex forms of invocations. Furthermore, PATL ensures that the user-written rules would not accidentally break def-use relations in the program. We formalize the semantics of PATL on Middleweight Java and prove the semantics-preserving property of guided-normalization. We also evaluated our language with three non-trivial case studies: i.e. updating Google Calendar API, switching from JDom to Dom4j, and switching from Swing to SWT. The result is encouraging; it shows that our language allows successful transformations of real world programs with a small number of rules and little manual resolution

Compact q-gram Profiling of Compressed Strings

We consider the problem of computing the q-gram profile of a string \str of size $N$ compressed by a context-free grammar with $n$ production rules. We present an algorithm that runs in $O(N-\alpha)$ expected time and uses O(n+q+\kq) space, where $N-\alpha\leq qn$ is the exact number of characters decompressed by the algorithm and \kq\leq N-\alpha is the number of distinct q-grams in \str. This simultaneously matches the current best known time bound and improves the best known space bound. Our space bound is asymptotically optimal in the sense that any algorithm storing the grammar and the q-gram profile must use \Omega(n+q+\kq) space. To achieve this we introduce the q-gram graph that space-efficiently captures the structure of a string with respect to its q-grams, and show how to construct it from a grammar