Co-evolution Of Code Research Articles

Automated testing of metamodels and code co-evolution

Automated testing of metamodels and code co-evolution

An Empirical Study on Leveraging LLMs for Metamodels and Code Co-evolution.

An Empirical Study on Leveraging LLMs for Metamodels and Code Co-evolution.

A Quality-Driven Iterative Evolution Approach for Software Architecture

The quality attributes of software architecture (SA) determine whether SA can be easily understood, tested, modified and so on, so quality-driven architecture evolution is important for keeping the viability and competitiveness. SA evolution is a process, and it contains multiple steps, such as SA quality measurement, SA modification, code co-evolution and so on. In order to guarantee that the software can be continuously improved and iteratively evolved in the future, we need to focus on all steps. However, most existing approaches only focus on one aspect, so they did not pay attention to how to finish the evolution process. In this paper, we propose a quality-driven iterative evolution approach for SA. This approach focuses on the whole process. In the first step, we use a quantitative approach to measure the architecture quality. Then, we construct the conflict graph to detect conflicts between evolution requirements to generate the final evolution scheme. In the third step, we modify architecture based on the evolution scheme. Finally, we co-evolve file dependency graph (FDG) based on the modified architecture. By focusing on the above steps, our approach can support a complete quality-driven architecture evolution process and obtain the maximum benefit in terms of the combined SA quality. We conduct our experiments with four open source projects, the experimental results indicate that our approach can improve SA quality, and our approach can effectively co-evolve the FDG to lay the foundation for the next evolution.

The Virtual Developer

Model Driven Development (MDD) requires proper tools to derive the implementation code from the application models. However, the integration of handwritten and generated code is a long-standing issue that affects the adoption of MDD in the industry. This article presents a model and code co-evolution approach that addresses such a problem a posteriori , using the standard collision detection capabilities of Version Control Systems to support the semi-automatic merge of the two types of code. We assess the proposed approach by contrasting it with the more traditional template-based, forward-engineering process, adopted by most MDD tools.

Analyzing the co-evolution of comments and source code

Source code comments are a valuable instrument to preserve design decisions and to communicate the intent of the code to programmers and maintainers. Nevertheless, commenting source code and keeping comments up-to-date is often neglected for reasons of time or programmers obliviousness. In this paper, we investigate the question whether developers comment their code and to what extent they add comments or adapt them when they evolve the code. We present an approach to associate comments with source code entities to track their co-evolution over multiple versions. A set of heuristics are used to decide whether a comment is associated with its preceding or its succeeding source code entity. We analyzed the co-evolution of code and comments in eight different open source and closed source software systems. We found with statistical significance that (1) the relative amount of comments and source code grows at about the same rate; (2) the type of a source code entity, such as a method declaration or an if-statement, has a significant influence on whether or not it gets commented; (3) in six out of the eight systems, code and comments co-evolve in 90% of the cases; and (4) surprisingly, API changes and comments do not co-evolve but they are re-documented in a later revision. As a result, our approach enables a quantitative assessment of the commenting process in a software system. We can, therefore, leverage the results to provide feedback during development to increase the awareness of when to add comments or when to adapt comments because of source code changes.

Observations on the assured evolution of concurrent Java programs

Evolving and refactoring concurrent Java software can be error-prone, resulting in race conditions and other concurrency difficulties. We suggest that there are two principal causes: concurrency design intent is often not explicit in code and, additionally, consistency of intent and code cannot easily be established through either testing or inspection. We explore several aspects of this issue in this paper. First, we describe a tool-assisted approach to modeling and assurance for concurrent programs. Second, we give an account of recent case study experience on larger-scale production Java systems. Third, we suggest an approach to scalable co-evolution of code and models that is designed to support working programmers without special training or incentives. Fourth, we propose some concurrency-related refactorings that, with suitable analysis and tool support, can potentially offer assurances of soundness.

Testing a biosynthetic theory of the genetic code: fact or artifact?

It has long been conjectured that the canonical genetic code evolved from a simpler primordial form that encoded fewer amino acids [e.g., Crick, F. H. C. (1968) J. Mol. Biol. 38, 367-379]. The most influential form of this idea, "code coevolution" [Wong, J. T.-F. (1975) Proc. Natl. Acad. Sci. USA 72, 1909-1912], proposes that the genetic code coevolved with the invention of biosynthetic pathways for new amino acids. It further proposes that a comparison of modern codon assignments with the conserved metabolic pathways of amino acid biosynthesis can inform us about this history of code expansion. Here we re-examine the biochemical basis of this theory to test the validity of its statistical support. We show that the theory's definition of "precursor-product" amino acid pairs is unjustified biochemically because it requires the energetically unfavorable reversal of steps in extant metabolic pathways to achieve desired relationships. In addition, the theory neglects important biochemical constraints when calculating the probability that chance could assign precursor-product amino acids to contiguous codons. A conservative correction for these errors reveals a surprisingly high 23% probability that apparent patterns within the code are caused purely by chance. Finally, even this figure rests on post hoc assumptions about primordial codon assignments, without which the probability rises to 62% that chance alone could explain the precursor-product pairings found within the code. Thus we conclude that coevolution theory cannot adequately explain the structure of the genetic code.

The historical factor: the biosynthetic relationships between amino acids and their physicochemical properties in the origin of the genetic code.

Two forces are in general, hypothesized to have influenced the origin of the organization of the genetic code: the physicochemical properties of amino acids and their biosynthetic relationships. In view of this, we have considered a model incorporating these two forces. In particular, we have studied the optimization level of the physicochemical properties of amino acids in the set of amino acid permutation codes that respects the biosynthetic relationships between amino acids. Where the properties of amino acids are represented by polarity and molecular volume we obtain indetermination percentages in the organization of the genetic code of approximately 40%. This indicates that the contingent factor played a significant role in structuring the genetic code. Furthermore, this result is in agreement with the genetic code coevolution hypothesis, which attributes a merely ancillary role to the properties of amino acids while it suggests that it was their biosynthetic relationships that organized the code. Furthermore, this result does not favor the stereochemical models proposed to explain the origin of the genetic code. On the other hand, where the properties of amino acids are represented by polarity alone, we obtain an indetermination percentage of at least 21.5%. This might suggest that the polarity distances played an important role and would therefore provide evidence in favor of the physicochemical hypothesis of genetic code origin. Although, overall, the analysis might have given stronger support to the latter hypothesis, this did not actually occur. The results are therefore discussed in the context of the different theories proposed to explain the origin of the genetic code.

On the Relationships between the Genetic Code Coevolution Hypothesis and the Physicochemical Hypothesis

This paper analyzes the relationships between the genetic code coevolution hypothesis and the physicochemical hypothesis by means of a comparative study of the precursor-product amino acid pairs on which the former hypothesis is based. Even if the coevolution between the biosynthetic relationships of amino acids and the organization of the genetic code is not questioned in this paper, the results and the arguments used lead us to believe that the selective pressures considered essential by the physicochemical postulates, played a more active role than that of the precursor-product relationships in defining the allocation of these amino acids in the genetic code. It is furthermore pointed out that the two evolutionary hypothesis might be aspects of the same selective pressure, and thus difficult to differentiate.