Behaviour Preservation across Code Versions in Erlang

[EN] In any alive and nontrivial program, the source code naturally evolves along the lifecycle for many reasons such as the implementation of new functionality, the optimization of a bottleneck, or the refactoring of an obscure function. Frequently, these code changes affect various different functions and modules, so it can be difficult to know whether the correct behaviour of the previous version has been preserved in the new version. In this paper, we face this problem in the context of the Erlang language, where most developers rely on a previously defined test suite to check the behaviour preservation. We propose 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 it introduces novel ideas such as allowing the programmer to choose one or more expressions of interest that must preserve the behaviour, or the recording of the sequences of values to which those expressions are evaluated. All the presented work has been implemented in an open-source tool that is publicly available on GitHub.This work has been partially supported by MINECO/AEI/FEDER (EU) under Grant TIN2016-76843-C4-1-R and by Generalitat Valenciana under Grant PROMETEO-II/2015/013 (SmartLogic). Salvador Tamarit was partially supported by Conselleria de Educacion, Investigacion, Cultura y Deporte de la Generalitat Valenciana, under Grant APOSTD/2016/036.Insa Cabrera, D.; Pérez-Rubio, S.; Silva, J.; Tamarit Muñoz, S. (2018). Behaviour Preservation across Code Versions in Erlang. Scientific Programming. 2018:9251762:1-9251762:42. https://doi.org/10.1155/2018/9251762S9251762:19251762:42201

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

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

Enhancing POI Testing Approach through the Use of Additional Information

[EN] Recently, a new approach to perform regression testing has been defined: the point of interest (POI) testing. A POI, in this context, is any expression of a program. The approach receives as input a set of relations between POIs from a version of a program and POIs from another version, and also a sequence of entry points, i.e. test cases. Then, a program instrumentation, an input test case generation and different comparison functions are used to obtain the final report which indicates whether the alternative version of the program behaves as expected, e.g. it produces the same outputs or it uses less CPU/memory. In this paper, we present a method to improve POI testing by including additional context information for a certain type of POIs. Concretely, we use this method to obtain an enhanced tracing of calls. Additionally, it enables new comparison modes and a categorization of unexpected behaviours.This work has been partially supported by MINECO/AEI/FEDER (EU) under grant TIN2016-76843-C4-1-R, and by the Generalitat Valenciana under grant PROMETEOII/2015/013 (SmartLogic). Salvador Tamarit was partially supported by the Conselleria de Educación, Investigación, Cultura y Deporte de la Generalitat Valenciana under grant APOSTD/2016/036.Pérez-Rubio, S.; Tamarit Muñoz, S. (2019). Enhancing POI Testing Approach through the Use of Additional Information. Lecture Notes in Computer Science. 11285:74-90. https://doi.org/10.1007/978-3-030-16202-3_5S74901128

On Preserving the Behavior in Software Refactoring: A Systematic Mapping Study

Context: Refactoring is the art of modifying the design of a system without altering its behavior. The idea is to reorganize variables, classes and methods to facilitate their future adaptations and comprehension. As the concept of behavior preservation is fundamental for refactoring, several studies, using formal verification, language transformation and dynamic analysis, have been proposed to monitor the execution of refactoring operations and their impact on the program semantics. However, there is no existing study that examines the available behavior preservation strategies for each refactoring operation. Objective: This paper identifies behavior preservation approaches in the research literature. Method: We conduct, in this paper, a systematic mapping study, to capture all existing behavior preservation approaches that we classify based on several criteria including their methodology, applicability, and their degree of automation. Results: The results indicate that several behavior preservation approaches have been proposed in the literature. The approaches vary between using formalisms and techniques, developing automatic refactoring safety tools, and performing a manual analysis of the source code. Conclusion: Our taxonomy reveals that there exist some types of refactoring operations whose behavior preservation is under-researched. Our classification also indicates that several possible strategies can be combined to better detect any violation of the program semantics

Acute: high-level programming language design for distributed computation

Existing languages provide good support for typeful programming of standalone programs. In a distributed system, however, there may be interaction between multiple instances of many distinct programs, sharing some (but not necessarily all) of their module structure, and with some instances rebuilt with new versions of certain modules as time goes on. In this paper we discuss programming language support for such systems, focussing on their typing and naming issues. We describe an experimental language, Acute, which extends an ML core to support distributed development, deployment, and execution, allowing type-safe interaction between separately-built programs. The main features are: (1) type-safe marshalling of arbitrary values; (2) type names that are generated (freshly and by hashing) to ensure that type equality tests suffice to protect the invariants of abstract types, across the entire distributed system; (3) expression-level names generated to ensure that name equality tests suffice for type-safety of associated values, e.g. values carried on named channels; (4) controlled dynamic rebinding of marshalled values to local resources; and (5) thunkification of threads and mutexes to support computation mobility. These features are a large part of what is needed for typeful distributed programming. They are a relatively lightweight extension of ML, should be efficiently implementable, and are expressive enough to enable a wide variety of distributed infrastructure layers to be written as simple library code above the byte-string network and persistent store APIs. This disentangles the language runtime from communication intricacies. This paper highlights the main design choices in Acute. It is supported by a full language definition (of typing, compilation, and operational semantics), by a prototype implementation, and by example distribution libraries